Tag: artificial intelligence

  • The Global Risks Report 2026 by World Economic Forum

    The Global Risks Report 2026 by World Economic Forum

    About the paper

    The World Economic Forum’s Global Risks Report 2026 examines global risks across 2026, 2028 and 2036, framing the period as an “age of competition” shaped by geo-economic confrontation, societal fragmentation, technological acceleration and environmental stress.

    It is a mixed-methods report based on the Global Risks Perception Survey of over 1,300 experts worldwide, the Executive Opinion Survey of over 11,000 business leaders in 116 economies, and foresight input from 161 experts through interviews and workshops conducted between May and November 2025.

    Length: 102 pages

    More information / download:
    https://www.weforum.org/publications/global-risks-report-2026/

    Core Insights

    1. What is the report’s central argument about the global risk landscape in 2026–2036?

    The report’s central argument is that the world is entering an “age of competition” in which cooperation is weakening just as global risks are becoming faster, more interconnected and more systemic. The report does not present predictions, but rather a set of plausible risk trajectories intended to support prevention and preparedness.

    Its core diagnosis is that geopolitical and geo-economic rivalry are no longer separate risk categories; they are becoming organising forces that shape the entire risk landscape. Trade, finance, technology, supply chains and infrastructure are increasingly treated as instruments of power. This creates a world in which confrontation replaces collaboration, and where multilateral institutions struggle to manage cross-border problems.

    The report’s tone is notably pessimistic. Half of surveyed experts expect a turbulent or stormy global outlook over the next two years, rising to 57% over the next decade. Only 1% expect a calm outlook across either time horizon. The implication is that instability is not viewed as a temporary disruption, but as a structural condition of the coming decade.

    2. Which risks dominate the short-term outlook, and why?

    In the immediate and two-year outlook, geo-economic confrontation is the dominant concern. It is identified as the top risk most likely to trigger a material global crisis in 2026, selected by 18% of respondents, followed by state-based armed conflict at 14%. Over the two-year horizon, geo-economic confrontation is also ranked as the most severe risk.

    This reflects the report’s view that economic instruments are increasingly being used for strategic advantage. Sanctions, tariffs, investment controls, technology restrictions, supply-chain weaponisation and resource competition are no longer peripheral policy tools; they are becoming central features of international rivalry. The report argues that this threatens the core of the interconnected global economy.

    Other short-term risks cluster around the same underlying instability. Misinformation and disinformation ranks second over the two-year horizon, societal polarisation third, extreme weather fourth, and state-based armed conflict fifth. Cyber insecurity, inequality and erosion of civic freedoms also feature in the top 10. This shows that the report sees short-term risk as a combination of geopolitical confrontation, social fragmentation and information disorder.

    Economic risks also rise sharply in the two-year outlook. Economic downturn and inflation each rise eight places compared with the previous year, while asset bubble burst rises seven places. The report links these concerns to debt pressures, volatile markets, potential AI-related investment bubbles and the broader uncertainty created by protectionism and geo-economic rivalry.

    3. How does the long-term risk outlook differ from the two-year outlook?

    The long-term outlook shifts from geopolitical and economic confrontation towards environmental and technological risks. Over the 10-year horizon, extreme weather events rank first, followed by biodiversity loss and ecosystem collapse, critical change to Earth systems, misinformation and disinformation, and adverse outcomes of AI technologies. Half of the top 10 long-term risks are environmental.

    This creates one of the report’s central tensions: environmental risks are being deprioritised in the short term even though they remain dominant in the long term. The report notes that most environmental risks decline in the two-year ranking and also show reduced short-term severity scores compared with the previous year. Yet over 10 years, environmental risks remain the most severe category.

    The report’s interpretation is that immediate geopolitical, economic and societal pressures are crowding out longer-term collective priorities. In practical terms, climate and biodiversity risks remain existential, but political attention is being pulled towards wars, protectionism, inflation, debt, social unrest and technological disruption.

    This is one of the report’s most important implications: the world may be paying less attention to the risks that experts still see as most severe over the coming decade.

    4. What role do technology, AI and quantum developments play in the report’s risk assessment?

    Technology is presented as a source of enormous opportunity and systemic risk. In the short term, the report is most concerned with misinformation and disinformation, cyber insecurity and the way digital technologies amplify social polarisation. Misinformation and disinformation ranks second in the two-year outlook, while cyber insecurity ranks sixth.

    AI becomes much more important over the long term. “Adverse outcomes of AI technologies” rises from #30 in the two-year outlook to #5 in the 10-year outlook — the largest upward shift across all 33 risks surveyed. The report highlights several possible consequences: labour-market disruption, higher inequality, loss of purpose and social belonging, information chaos, concentration of economic power, and risks from military uses of AI.

    The report’s AI chapter is especially concerned with a scenario it describes as “jobless productivity”: productivity rises because of AI, but employment opportunities shrink or become more unevenly distributed. This could deepen inequality and social polarisation, particularly if middle-class and white-collar work is disrupted faster than societies can adapt.

    Quantum technologies are treated as a more distant but potentially severe frontier risk. The report highlights the possibility that quantum computing could undermine current cryptographic systems, threatening digital authentication, data privacy and trust infrastructure. It also warns that quantum leadership could become another domain of strategic rivalry, widening economic and geopolitical divides.

    5. What does the report imply about cooperation, governance and resilience?

    The report’s underlying message is that cooperation is becoming harder at precisely the moment when it is most needed. Multilateralism is described as under pressure from declining trust, protectionism, weakening rule of law and the rise of more adversarial national strategies.

    The report does not argue that cooperation has disappeared. Rather, it suggests that cooperation will need to look different. In a more fragmented world, global treaties may be harder to achieve, so the report points to coalitions of the willing, minilateral agreements, public-private partnerships, multi-stakeholder engagement, public awareness, education, R&D and corporate resilience strategies as practical mechanisms for risk reduction.

    The report’s perspective is pragmatic rather than optimistic. It assumes that the current order is weakening, but not that collapse is inevitable. Its conclusion is that resilience will depend on rebuilding trust, protecting institutional capacity, investing in adaptive infrastructure, preparing societies for technological disruption, and finding new forms of cooperation even amid competition.

    The most important strategic implication is that risk management can no longer be treated as domain-specific. Geopolitics affects economics; economics affects social trust; social distrust affects governance; technology affects all of them; and environmental risks continue to intensify in the background. The report’s core warning is that leaders must prepare for compounding risks, not isolated crises.

  • State of PR 2026 by Meltwater

    State of PR 2026 by Meltwater

    About the paper

    The paper is a global survey-based industry report on how PR and communications professionals are navigating resourcing pressure, measurement, AI, media relations, collaboration and future skills.

    The report is original survey research based on more than 1,100 international PR professionals, including almost 500 from the United States, 100 from Canada and respondents from across the world, with Europe described as particularly well represented.

    The fieldwork method, sampling approach and timeframe are not clearly specified in the report.

    Length: 56 pages

    More information / download:
    https://www.meltwater.com/en/blog/state-of-pr

    Core Insights

    1. What is the central picture the report paints of the PR industry in 2026?

    The report presents PR as an industry caught between familiar old pressures and a new wave of technological disruption. On the one hand, many of the profession’s core challenges remain highly recognisable: lack of resources, difficulty measuring impact, managing stakeholders, getting journalists to respond and doing more with less. On the other hand, AI, social media, data and changing audience behaviour are reshaping the environment in which those classic challenges now have to be solved.

    The report’s strongest overarching argument is that PR is becoming more strategically important, but still struggles to prove that importance in business terms. It explicitly links this to generative AI: as LLMs increasingly influence how brands are described and discovered, earned media and public narratives may become even more central to brand visibility. In that sense, the report positions PR not as a shrinking discipline, but as one whose relevance could grow if it can modernise its tools, metrics and internal influence.

    At the same time, the report is clear that the profession has not fully made the shift from activity-based communication to business-aligned communication. Many teams are still judged by volume and reach of media placements, while challenges around ROI, business KPIs and leadership understanding remain persistent. The conclusion frames the core issue as one of alignment: between PR and leadership on strategy and metrics, between PR and marketing on execution, and between human creativity and AI in daily workflows.

    2. What are the main operational challenges facing PR professionals?

    The most frequently cited challenge is insufficient resources, named by 24% of respondents. Measurement follows closely, with 21% identifying measuring impact and ROI as a top challenge. Managing stakeholder expectations comes next at 16%, followed by getting responses from journalists at 12% and adopting new technologies at 10%.

    This distribution matters because it shows that the profession’s biggest pressures are not only external. The difficult media environment is part of the story, but the larger picture is organisational: PR teams are under-resourced, expected to prove impact, and often dependent on leaders who may not fully understand the value or mechanics of communications work.

    The report reinforces this with budget data. A majority expect PR budgets to stay flat, while only 21.3% expect an increase and 17.3% expect a decrease. Budget decisions are also often made outside the PR function: 36.7% say the CEO decides PR spending, while 19.2% say a C-level marketing leader does. Only 32.6% say a C-level PR or communications executive makes these decisions.

    Time pressure is another recurring theme. The biggest time sinks are reactive work such as crisis response and urgent requests, cited by 27.9%, and content creation, cited by 27.5%. Measurement and reporting account for another 20.3%. The report’s implied diagnosis is that PR teams are stuck in a reactive operating model, spending too much time on urgent execution and too little on strategic, higher-value work.

    3. How mature is the industry’s approach to measurement and business impact?

    The report suggests that PR measurement remains stuck between aspiration and reality. Many teams understand that they need to connect communication to business outcomes, but their most common metrics still lean heavily towards activity and visibility.

    The most important metrics for evaluating PR success are the number of media placements and reach/impressions, both at 20.9%. Social media engagement follows at 11%, while more business-relevant or interpretive metrics such as website traffic/conversions, message pull-through, share of voice and sentiment analysis rank lower. This supports one of the report’s central criticisms: the industry is still often measuring what is easiest to measure rather than what best demonstrates business value.

    The measurement section makes this even clearer. When asked about challenges, 34.7% cite aligning metrics to business KPIs, and 27.8% cite proving PR’s value to leadership. Another 22.4% point to over-reliance on outdated metrics such as impressions and AVE. Although nearly three quarters say they have at least some of the tools needed to connect PR activity to wider business outcomes, only 32.1% say they fully have those tools; 39% say they only partially do.

    The report’s perspective is therefore not that measurement is impossible, but that PR measurement is underdeveloped and uneven. It implies that the profession needs more sophisticated reporting, closer linkage to business objectives and better executive-facing narratives about what PR contributes.

    4. How is generative AI affecting PR work, and what concerns does it raise?

    Generative AI is presented as both a practical tool and a major strategic disruptor. A majority of respondents say AI is already integrated into communication workflows: 13.3% describe it as highly integrated and 42.1% as somewhat integrated. Only 9.8% say it is not integrated at all.

    Current use is heavily concentrated around content work. The most common applications are external content creation, content optimisation and review, campaign brainstorming, internal content creation, writing press releases and crafting media pitches. Measurement and reporting are much lower at 2.1%, which suggests that many teams still use AI primarily as a production assistant rather than as a strategic analysis or intelligence tool.

    The report also highlights a gap between adoption and governance. While 36.2% say their organisation has a formal AI policy and 26.4% say one is in development, 31.4% say they do not have one. This makes AI governance one of the more practical risks in the report: usage is becoming normal before policies, training and operating models are fully mature.

    The biggest concern about AI is that it may reduce the need for human talent, cited by 28.6%. Other concerns include shrinking communications budgets and reducing PR’s seat at the table. Interestingly, concerns about accuracy and content quality appear very low in the report’s results, which may suggest either that respondents are less worried about quality than job security, or that the survey options did not fully surface deeper concerns around misinformation, ethics and brand risk.

    Looking ahead, AI dominates the future-facing findings. AI integration is the top skill PR professionals believe they will need over the next five years, and navigating new technologies such as AI is seen as the biggest future challenge. AI as a tool for content creation and data analysis is also identified as the emerging trend likely to have the greatest impact on PR.

    5. What are the most important implications for PR leaders and communication teams?

    The report’s main implication is that PR teams need to become more strategically aligned, more data-literate and more operationally efficient. The conclusion explicitly argues that success in 2026 and beyond will depend on using powerful new tools without losing the human skills that make PR valuable: storytelling, relationship-building and creativity.

    For PR leaders, the most immediate implication is the need to speak more directly in business language. Since resources and budgets are major concerns, and since budget decisions often sit with CEOs or marketing leaders, PR teams need to show clearer links between communication activity and organisational outcomes. The report repeatedly suggests that better reporting and business-aligned metrics are essential not only for measurement, but for influence.

    A second implication is that PR needs stronger collaboration across the organisation. Respondents already collaborate most often with executive leadership and marketing, but they want more involvement from leadership, customer experience, marketing and product development in communications strategy. The main barriers are misaligned priorities, departmental politics or silos, and lack of communication. This points to a broader strategic role for PR, but also to the difficulty of securing that role inside complex organisations.

    A third implication is that AI cannot simply be treated as a content shortcut. The report encourages teams to operationalise AI, formalise policies, invest in tools and training, and use AI to reduce time spent on repetitive or low-value tasks. The opportunity is not just faster content production, but freeing up capacity for more rewarding and strategic work.

    Finally, the report implies that the human fundamentals of PR remain durable. Media relevance, timeliness and reporter relationships are still the most important factors in securing coverage. Individual email remains by far the most effective pitching channel. LinkedIn is the most valuable professional social platform. These findings suggest that while the tools are changing rapidly, the profession’s underlying value still depends on judgement, relationships, relevance and trust.

  • What is AI reading? by Muck Rack

    What is AI reading? by Muck Rack

    About the paper

    The paper is a mixed-methods, proprietary analysis from Muck Rack on how web-enabled generative AI models cite sources in response to realistic prompts.

    The report says it analysed more than 1,000,000 links generated by Gemini, Perplexity, Claude and ChatGPT between July and December 2025, across a large prompt set spanning multiple industries; the number of prompts and the geographic scope of the data are not clearly specified in the report.

    Length: 35 pages

    More information / download:
    https://generativepulse.ai/report/

    Core Insights

    1. What is the report fundamentally trying to understand about AI citation behaviour?

    The report is trying to map what kinds of sources generative AI systems cite, how often they cite them, and what seems to influence those choices. It is not mainly a consumer study or a survey of users. Instead, it is an observational analysis of AI outputs and their linked citations across multiple models. Muck Rack frames this as relevant to Generative Engine Optimisation (GEO) and to PR and communications teams that want to understand how brands surface in AI-generated answers.

    At a practical level, the report studies citation behaviour across several dimensions: source type, recency, authority, industry specificity, and the balance between earned and owned media. It also emphasises that model behaviour is unstable and can change as systems are updated, so the findings should be treated as a snapshot rather than a fixed rulebook.

    The deeper argument is that AI visibility is shaped by media ecosystems, not just by a brand’s own website. For broad discovery-style prompts, the models appear to lean heavily on earned media and reputable third-party coverage; for narrower factual questions, owned channels become more important. That distinction is one of the report’s most important strategic takeaways.

    2. What does the report find about the kinds of sources AI cites most often?

    The central finding is that non-paid and earned media still dominate AI citations. The report states that about 94% of links cited by AI are non-paid media and that 82% of cited links come from earned media. Journalistic sources alone account for about a quarter of all citations. On the chart on page 5, the mix is shown as 24.7% journalistic, 24.5% third-party corporate/blog earned, 14.4% aggregators/encyclopaedic sources, 12% first-party corporate/blog owned, 7.3% academic/research, 6.7% government/NGO, 6% press release, and 4.3% social/UGC.

    That matters because it pushes against the idea that AI answers are driven mainly by brand-owned content. The report argues that traditional journalism remains highly influential, with journalistic citations holding fairly steady in the 20–30% range even though they fell slightly versus July.

    The findings also suggest that models do not all rely on the same handful of publications. The page 9 table shows different “top media outlets cited” for Claude, ChatGPT and Gemini, with only limited overlap. Reuters appears prominently for ChatGPT, while Gemini’s list includes Forbes, Investopedia and PC Magazine, and Claude’s includes U.S. News & World Report, Nature and Yahoo Finance. The report’s interpretation is that AI models pull from a diverse set of high-authority outlets, not one universally dominant list.

    3. According to the report, what makes content more likely to be cited by AI?

    The report highlights three main factors: authority, freshness, and relevance to the query domain. It explicitly says outlet authority matters, both broadly, through high-domain-authority publishers such as Reuters, and more narrowly, through specialist sources for specialist topics. It also says niche outlets remain important for industry-specific queries.

    Freshness is a major part of the story. The report says that half of all citations are to material published in the last 11 months, and that the highest citation rate occurs within the first seven days after publication. For Claude and ChatGPT, roughly 4% of all citations come from the last week, 5% from the last two weeks, and 8% from the last month. That suggests AI systems disproportionately reward timely coverage, especially soon after publication.

    The report also claims that press release structure matters. On page 15, the infographic says cited press releases have about twice as many statistics, 30% more action verbs, 2.5 times as many bullet points, mention more unique companies/products, and have a 30% higher rate of objective sentences than non-cited releases. That implies that structure and information density may affect machine readability and citation likelihood, although the report does not provide a full technical methodology for how those textual features were measured.

    4. What changes and trends does the report identify between July and December 2025?

    One of the report’s strongest messages is that AI citation behaviour is not stable. It repeatedly says that models are constantly tuning their citation mix, and page 19 gives concrete examples: ChatGPT reduced its reliance on Wikipedia, Gemini briefly spiked on YouTube in November, and Reuters gradually increased in importance across models.

    Several category-level shifts stand out. First, press release citations increased materially. The report says press releases overall rose from 1.2% to about 6% of citations from July to December, while direct citations to PR Newswire, Business Wire and GlobeNewswire rose from 0.2% in July to 1% in December, which it describes as a fivefold increase.

    Second, third-party corporate/blog citations declined. The report says this category fell by 35%, dropping from 37% to 24%, and links that decline partly to reduced reliance on management consulting content.

    Third, the report notes shifts in sector-specific citation patterns. For example, education queries are said to lean more towards .gov and .org sources than in July; healthcare is dominated by NGO and government sources, with Gemini as a partial exception because it uses YouTube; travel queries now mix in more Reddit and YouTube for some models; and technology queries appear to cite fewer unique outlets than before.

    5. What are the report’s main implications for PR, media relations and brand visibility in AI?

    The report’s practical conclusion is that earned media drives discovery in AI, while owned media matters mainly for fact-finding questions. It gives examples: broad prompts such as what coffee maker to buy are influenced by reputable earned coverage, whereas specific questions such as warranty details tend to pull from owned documentation. The report explicitly says owned content is important, but only for certain question types.

    For PR teams, this means AI visibility is not just an SEO or website issue. It is a media strategy issue. The report argues that for a given brand, much of the relevant AI citation coverage comes from a relatively small set of outlets: page 16 says 50% of a brand’s coverage can come from only 20 outlets. But it also warns there is no universal magic list; each brand has its own citation-driving mix.

    A particularly provocative implication appears on page 17: the overlap between the journalists most pitched by brands and those most cited by AI is only 2% on average. If that figure holds up, it suggests many media relations habits are poorly aligned with how AI systems actually construct answers. In other words, the report implies that PR professionals may need to rethink not just message discipline, but who they target, what formats they produce, and how quickly they publish.

    One note of caution: the report is useful, but the methodology remains somewhat thin in places. It clearly states the models used, timeframe, and the volume of links analysed, but it does not clearly specify the number of prompts, the exact sampling design, or the geographic boundaries of the dataset. So the strategic patterns are valuable, but some claims should be treated as directional rather than definitive.

  • Future of Professionals Report 2025 by Thomson Reuters

    Future of Professionals Report 2025 by Thomson Reuters

    About the paper

    Thomson Reuters’ Future of Professionals Report 2025 examines how AI and GenAI are affecting legal, risk, compliance, tax, accounting, audit and trade professionals, with a particular focus on strategic AI adoption and ROI.

    It is an original survey-based report, drawing on 2,275 responses gathered in February and March 2025 from professionals across firms, corporations, government and in-house functions.

    The geographic scope is international, with responses from the US, Canada, UK, Mainland Europe, Middle East, Africa, Latin America, Asia, and Australia/New Zealand.

    Length: 31 pages

    More information / download:
    https://www.thomsonreuters.com/en/c/future-of-professionals

    Core Insights

    1. What is the central argument of the report?

    The report argues that AI adoption has moved from experimentation to strategic differentiation. Thomson Reuters’ core claim is that the decisive question is no longer whether professional organisations should adopt AI, but whether they do so deliberately, visibly and in alignment with broader business goals.

    The report frames a widening divide between organisations with a clear AI strategy and those relying on informal or ad hoc adoption. Organisations with visible AI strategies are presented as significantly more likely to experience AI-related benefits, including revenue growth, productivity gains and stronger operational performance. By contrast, organisations without a strategy are portrayed as at risk of falling behind within a few years.

    This is not just a technology argument. The report repeatedly emphasises that AI must be connected to organisational purpose, workflow redesign, leadership behaviour, talent strategy and individual professional development. AI is described as an enabler of broader transformation rather than a standalone tool.

    2. What evidence does the report provide that AI is already affecting professional work?

    The report provides several data points showing that AI has already become a major force in professional services and related corporate functions.

    Most prominently, 80% of respondents believe AI will have a high or transformational impact on their profession within five years. At the same time, 53% say their organisation is already experiencing at least one type of benefit from AI adoption. The most common benefits are efficiency, productivity, faster response times, reduced errors, cost reduction and freed-up time.

    The report estimates that AI could save professionals around five hours per week, or 240 hours per year. In the foreword, Thomson Reuters states that for legal professionals this represents an average annual value of around $19,000 per professional, contributing to a combined annual impact of $32 billion in the US legal and tax/accounting sectors.

    However, the report also identifies a gap between expected long-term impact and current organisational change. While 80% expect AI to have a major impact within five years, only 38% expect high or transformational change in their own organisation this year, and 30% believe their organisation is moving too slowly.

    3. What distinguishes organisations that achieve stronger ROI from AI?

    The report’s main explanatory model is the “AI Success Pyramid”, which identifies four layers required for stronger AI returns: strategy, leadership, operations and individual users.

    The strongest lever is strategy. Organisations with a visible AI strategy are described as 3.5 times as likely to experience at least one form of ROI compared with organisations that have no significant AI adoption plans. They are also almost twice as likely to report revenue growth from AI compared with organisations adopting AI informally.

    Leadership is the second layer. Respondents whose leaders lead by example are 1.7 times as likely to see AI benefits. Organisations investing in AI-powered technology are twice as likely to report benefits, while those adding new governance roles are also more likely to experience positive outcomes.

    Operational change is the third layer. The report argues that organisations need to redesign workflows, roles, delivery models, services and pricing structures. This is where AI moves beyond personal productivity and begins to change how professional work is produced and delivered.

    The fourth layer is individual adoption. Professionals with good or expert AI knowledge are 2.8 times as likely to see organisational benefits as those with basic or no knowledge. Regular users of AI tools are 2.4 times as likely to report benefits compared with non-regular users. This makes individual AI literacy a strategic issue, not merely a personal skill upgrade.

    4. What risks, barriers and tensions does the report identify?

    The report identifies several barriers to more robust AI adoption. The largest barrier to investment is demonstrable accuracy, cited by 50% of respondents. This is followed by available budget, data security, ethical concerns and implementation resources.

    Accuracy is especially important because professional work often carries high stakes. The report notes that 91% of professionals believe computers should be held to higher standards of accuracy than humans, including 41% who say AI outputs would need to be 100% accurate before being used without human review. This reinforces the report’s view that human oversight remains essential.

    The report also highlights a new concern: overreliance on AI at the expense of professional skill development. Almost a quarter of respondents identify this as a negative consequence of concern. This is a subtle but important shift from earlier fears of job loss towards worries about deskilling, judgement and long-term professional capability.

    Another major tension is misalignment between organisational and individual adoption. Some professionals have personal AI goals but are unaware of any organisational strategy, meaning they are being encouraged to adopt AI without clear guidance. Conversely, some organisations have AI strategies but professionals lack personal AI goals, creating an implementation gap.

    The report also describes the “jagged edge” of AI adoption: uneven adoption across regions, functions, organisations and demographics. For example, some organisations invest heavily but see low individual usage, suggesting wasted investment and weak change management. Others see high individual usage but low organisational investment, which may create risks if employees rely on public tools without proper safeguards.

    5. What does the report imply for the future of professional work?

    The report implies that professional value will increasingly depend on the ability to combine domain expertise with AI fluency. It does not argue that AI replaces professional judgement. Instead, it argues that modern professionals will use AI to augment core abilities such as research, writing, analysis, communication, project management, technical expertise and higher-order thinking.

    The “modern professional” in the report is someone who can use AI as a working partner: to analyse patterns, compare regulations, draft documents, summarise complex material, explain specialist issues in accessible ways, manage deadlines and explore scenarios. The traditional professional skillset remains important, but the report suggests that it will increasingly be mediated and amplified by technology.

    The report also points to a significant skills gap. Forty-six percent of respondents report skills gaps within their teams, with the largest gap in technology and data skills. Technical domain expertise is also a concern. This means the future challenge is not only AI adoption but reskilling across multiple levels of the organisation.

    The report’s final implication is competitive: organisations and professionals that act deliberately are likely to gain advantage, while those that wait may lose relevance. For organisations, this means connecting AI to strategy, governance, workflow and value creation. For individuals, it means developing AI proficiency through formal training, experimentation, peer learning and active involvement in how AI is developed and used.

  • The New CCAO and CCO Mandate by United Minds

    The New CCAO and CCO Mandate by United Minds

    About the paper

    The paper examines how Chief Corporate Affairs Officers and Chief Communications Officers are adapting to political volatility, cultural complexity, economic uncertainty, and AI-enabled communications work.

    It is an original qualitative research report based on semi-structured, in-depth interviews with CCOs and CCAOs from Fortune 1000 companies, conducted over two months in early 2025; the exact number of participants is not clearly specified in the report.

    The geographic scope includes both U.S.-based and European corporate affairs leaders.

    Length: 8 pages

    More information / download:
    https://webershandwick.com/news/new-ccao-and-cco-mandate-navigating-a-new-era-of-corporate-leadership

    Core Insights

    1. What is the central argument of the report?

    The report argues that the corporate affairs and communications function has not retreated in importance as companies have pulled back from the more visible social-issue positioning of the early 2020s. Instead, CCAOs and CCOs have become less publicly visible but more strategically central inside the enterprise.

    The core claim is that corporate affairs leaders are now expected to help companies navigate a volatile intersection of business, politics, culture, stakeholder expectations, employee sentiment, and reputation risk. Their mandate is no longer simply to explain corporate decisions after the fact. They are increasingly expected to help shape those decisions before they are made.

    The report frames this as a shift from communications as a reactive function to corporate affairs as a source of enterprise foresight. The ideal corporate affairs function, according to the report, helps leaders anticipate risk, understand stakeholder dynamics, interpret political and cultural signals, and protect the company’s licence to operate.

    2. How is the CCAO/CCO role changing in relation to business strategy?

    The report’s first major theme is that corporate affairs leaders are becoming proactive business partners. Their value increasingly lies in their ability to translate political, regulatory, cultural, and stakeholder signals into business implications.

    This means they are not only advising on messages, positioning, or crisis response. They are helping business leaders understand where external pressures may require changes to products, operations, stakeholder engagement, or risk management. One example in the report describes a policy-related issue around a consumer product where corporate affairs brought data to the business, prompting an eight-week sprint that helped resolve product issues and changed the relationship between corporate affairs and the product leader.

    The report presents corporate affairs leaders as “orchestrators” across functions. Because they sit close to the CEO agenda and have an enterprise-wide view, they can connect information from legal, policy, HR, product, finance, operations, communications, and external stakeholders. Their strategic value comes from synthesising those signals into business intelligence.

    The practical recommendation is to build formal cross-functional intelligence networks and develop ways to quantify external risk in financial terms. In other words, corporate affairs must be able to speak the language of business impact, not only the language of reputation.

    3. Why does political complexity matter so much in the report?

    Political volatility is one of the report’s defining conditions. The authors locate the research in the early 2025 U.S. context, following Donald Trump’s second inauguration and first 100 days in office. The report says companies are operating in a climate shaped by executive orders, economic volatility, hyper-partisanship, and sudden political attention.

    The report argues that this has forced corporate affairs leaders to rethink public engagement. Companies are moving away from broad social activism and towards brand protection, business-aligned issue engagement, and risk management. The task is no longer simply “Should we speak out?” but “Where does engagement serve the business, where does silence reduce risk, and where is private dialogue more effective than public positioning?”

    One especially important idea is the “audience of one” problem: the risk that a single powerful political figure can draw attention to a company and create operational, reputational, or regulatory consequences. Corporate affairs leaders are therefore developing scenario plans, rapid-response frameworks, and more cautious approaches to political communication.

    This also changes the advisory role of corporate affairs. The report suggests that CCAOs and CCOs are becoming voices of restraint and judgement within executive teams, helping leaders distinguish between noise, bargaining tactics, genuine risk, and issues that require action.

    4. How does the report redefine crisis and reputation management?

    The report argues that crisis management is no longer an exceptional capability. It has become a baseline expectation. In a “permacrisis” environment, corporate affairs teams must apply crisis tools continuously, not only when a discrete crisis breaks out.

    This changes the role in two ways. First, crisis work now extends beyond media response. Corporate affairs teams are expected to help solve the underlying problem, coordinate across business functions, and prevent issues from escalating. Secondly, the report says corporate affairs leaders must make the financial case for proactive reputation management.

    One quoted example describes a corporate affairs leader asking for $2.5 million for a campaign during a contentious situation and using analysis to show that the potential return was 12 times the investment. The point is that reputation work becomes more credible in the C-suite when it is connected to profit protection, revenue risk, regulatory exposure, or operational continuity.

    The implication is that corporate affairs must move from “the team that handles crises” to “the function that helps prevent avoidable business risk”. The report recommends crisis prevention scoring, financial modelling of reputational risk, and closer collaboration with finance and analytics partners.

    5. What does the report say about employees and AI as part of the new mandate?

    The report treats employee communication as a continuing priority, but one that has become more delicate. Employees are described as one of the most important stakeholder groups, especially during uncertainty. At the same time, internal communication now has to navigate political polarisation, regulatory sensitivity, DEI-related scrutiny, and the risk that different employee groups may interpret corporate messages very differently.

    The report therefore points to a more cautious, “sanitised” form of transparency. Companies may still communicate openly, but in ways designed to avoid partisan signalling or unnecessary exposure. The authors recommend mapping internal stakeholder intersections and using tools such as message testing to understand differences within the employee base.

    AI is presented as a practical accelerator for the corporate affairs function. The report says AI is being used for tasks such as preparing Q&As, analysing large volumes of stakeholder content, vetting influencers, monitoring media and misinformation, supporting strategic planning, and improving data analysis. Rather than presenting AI mainly as a replacement threat, the report frames it as a way to free communications professionals from routine work and move them towards more strategic advisory roles.

    However, the report also makes clear that AI adoption is a change-management issue. Teams need clarity on what should remain human-led, what can be AI-assisted, and what ethical guardrails are needed around bias, accuracy, and appropriate use.

    Overall conclusion

    The report’s main message is that the CCAO/CCO mandate is expanding from communications execution to enterprise-level judgement. Corporate affairs leaders are being asked to help companies interpret volatility, anticipate risk, advise CEOs, manage political exposure, support employees, use AI responsibly, and convert stakeholder intelligence into business decisions.

    Its most important contribution is the framing of corporate affairs as a foresight function. Its main limitation is methodological: while the qualitative design is described in some detail, the report does not clearly specify the number of interviewees, which makes it harder to judge the breadth of the evidence base.

  • The Ipsos AI Monitor 2025 by Ipsos

    The Ipsos AI Monitor 2025 by Ipsos

    About the paper

    The paper is a 30-country survey about public understanding of AI, trust, perceived risks, and expectations for AI’s impact on work, content, brands, economies and everyday life.

    It is original survey research conducted by Ipsos via its Global Advisor online platform and, in India, its IndiaBus platform, between 21 March and 4 April 2025, with 23,216 adults across 30 countries; India used a mixed face-to-face and online approach.

    The methodology is clear, but Ipsos notes that some country samples are more “connected” than nationally representative, and that the 30-country average is an unweighted average across markets rather than a population-adjusted global figure.

    Length: 57 pages

    More information / download:
    https://www.ipsos.com/en-dk/ipsos-ai-monitor-2025

    Core Insights

    1. What is the central tension in public attitudes towards AI?

    The report’s central argument is that public opinion on AI is defined by a tension Ipsos calls the “Wonder and the Worry of AI”. People recognise AI’s potential and expect it to become embedded in many areas of life, but they also feel nervous about its consequences.

    At the 30-country average level, 52% say AI products and services make them excited, while 53% say they make them nervous. That means excitement and anxiety are not opposing camps so much as overlapping reactions: many people appear to hold both views at once.

    This tension is also geographically uneven. The Anglosphere — the US, Great Britain, Canada, Ireland and Australia — is described as more nervous than excited. European markets sit in a middle zone, with moderate excitement and less intense nervousness. Several South-East Asian markets are much more positive, while Japan is presented as an outlier: neither especially excited nor especially nervous.

    The broader meaning is that AI is not being received as a simple “innovation story”. People expect progress, but they are not automatically confident that the benefits will be fairly distributed, responsibly governed, or socially benign.

    2. How much do people understand AI, and how does knowledge vary by country?

    A majority say they understand AI at a general level, but fewer say they understand where AI is actually being used.

    Across the 30 countries, 67% agree that they have a good understanding of what artificial intelligence is. However, only 52% say they know which types of products and services use AI. That gap matters: people may feel familiar with AI as a concept while still being unsure where it is embedded in everyday services.

    There are large country differences. Indonesia, Thailand and South Africa are among the highest on claimed understanding of AI, while Japan is lowest. For knowing which products and services use AI, Indonesia and Thailand again rank high, while Belgium, Japan and Canada are at the lower end.

    This suggests that “AI literacy” is not just a question of awareness. The public may know the term, recognise the general idea, and still lack practical understanding of where AI is operating in search, marketing, recruitment, news, advertising, disinformation, customer service or workplace tools.

    3. What does the report reveal about trust in AI, companies and governments?

    Trust is one of the report’s most important fault lines. People are not simply asking whether AI is useful; they are asking who controls it, who regulates it, and whether organisations using it can be trusted.

    Only 48% across the 30-country average say they trust companies using AI to protect their personal data. Trust is much higher in countries such as Indonesia, Thailand and India, while Sweden, Canada, Japan, France and the United States sit much lower. The net trust measure is only slightly positive at the global country average level, which signals a fragile trust environment for brands and platforms.

    Governments are trusted somewhat more than companies in this context: 54% say they trust their government to regulate AI responsibly. But this also varies dramatically. Singapore, Indonesia, Malaysia and Thailand are high-trust markets, while the United States, Japan, Hungary, Great Britain and Canada are much lower. Ipsos suggests that low trust in government regulation may help explain higher nervousness in some markets, especially the US.

    One striking finding is that people say they trust AI more than people not to discriminate or show bias. At the 30-country average, 54% trust AI not to discriminate or show bias, compared with 45% who trust people not to discriminate or show bias. That does not mean people think AI is neutral; rather, it suggests that public trust in human fairness is also weak.

    The strongest trust-related consensus is disclosure. Seventy-nine per cent agree that products and services using AI should have to disclose that use. This is one of the clearest implications for organisations: transparency is not a niche concern but a mainstream expectation.

    4. How do people feel about AI-generated content, advertising and brand use?

    The report shows a clear public distinction between expecting AI-generated content and preferring it. People believe AI will be widely used, but they still prefer human-created content in most cases.

    For example, 79% think AI is likely to be used for online search results, and only 28% say they are uncomfortable with that use. That suggests search may be one of the more socially acceptable AI applications. By contrast, people are much more uncomfortable with AI-generated political ads, AI-written news stories, AI screening job applicants, and AI used to create or target disinformation.

    When asked about content preferences, the public consistently favours human-driven content. Seventy per cent prefer human-driven online news articles or websites; 71% prefer human-driven photojournalism; 67% prefer human-driven movies; 62% prefer human-driven advertising; and 60% prefer human-driven customer marketing websites.

    For brands, the picture is mixed and potentially risky. People are split on whether AI use would make them trust companies more or less. At the 30-country average, AI-enhanced product images produce 34% more trust and 38% distrust; AI-written product descriptions produce 33% more trust and 42% distrust; AI-created advertising images or video produce 30% more trust and 38% distrust; and AI-written product reviews produce 29% more trust and 36% distrust.

    The implication is that AI use in marketing is not automatically reputationally damaging, but it is not automatically efficiency-positive either. Brands may gain from AI where it improves usefulness, speed or relevance, but they risk distrust when AI is perceived as deceptive, synthetic, manipulative or insufficiently disclosed.

    5. What future impact do people expect AI to have on jobs, economies and everyday life?

    People expect AI to become more important in daily life, but their expectations are uneven across domains.

    A majority already feel AI has affected them: 52% say AI products and services have profoundly changed their daily life in the past three to five years. Looking ahead, 67% say AI will profoundly change their daily life in the next three to five years. So AI is not viewed as speculative; it is already part of people’s lived experience and expected to intensify.

    On work, the findings are ambivalent. Globally, 59% think AI is likely to change how they do their current job in the next five years, but only 36% think it is likely to replace their current job. Even more importantly, people are more optimistic about their own job than about the wider labour market. Among those with a job, 38% think AI will make their own job better, while 16% think it will make it worse. But for the job market overall, only 31% think AI will make it better, while 35% think it will make it worse.

    This “my job versus the job market” distinction is one of the report’s most useful insights. People may believe they personally can adapt, benefit or remain protected, while still worrying about broader labour disruption.

    The same pattern appears in other future-facing areas. People are optimistic that AI will improve efficiency: 55% say it will make the amount of time it takes to get things done better, compared with only 10% who say worse. They are also more positive than negative about entertainment options and health. But they are much more concerned about disinformation: only 29% think AI will make the amount of disinformation on the internet better, while 40% think it will make it worse.

    Economically, the global country average is cautiously positive: 34% think AI will improve their country’s economy, while 23% think it will worsen it. Ipsos argues that countries most excited about AI tend to be countries where people are also more likely to believe AI will benefit the economy. In other words, enthusiasm appears tied not only to technology itself, but to whether people believe AI will produce visible, shared economic benefits.

  • Trends – Artificial Intelligence by BOND

    Trends – Artificial Intelligence by BOND

    About the paper

    The report is a mixed-methods, chart-led secondary analysis of artificial intelligence trends, compiled by BOND from a wide range of public and private company data, market research, government sources and additional non-public insights.

    It does not present one unified survey or a single fieldwork sample, so the total number of respondents, cases or participants is not clearly specified in the report; those figures vary by source and chart.

    The geographic scope is global, with a strong emphasis on the United States and China, alongside regional and country-level comparisons.

    BOND Capital and Mary Meeker have not released AI trend reports in years other than 2025. The 2025 “Trends – Artificial Intelligence” edition marked a revival of Meeker’s trend series after a six-year gap, evolving from her famous annual “Internet Trends” reports that ran from 1995 to 2019

    Length: 340 pages

    More information / download:
    https://www.bondcap.com/reports/tai

    Core Insights

    1) Why does the report argue that AI change is happening faster than ever?

    The report’s central argument is that AI is not simply another technology cycle but a compounding force built on top of existing internet infrastructure, massive digital datasets, better chips, improving models and intense capital deployment. BOND presents AI as accelerating faster than earlier technology waves because the rails were already in place: billions of connected users, decades of data accumulation and a ready-made global digital distribution system. That is why the report repeatedly frames the current moment as unprecedented in pace and scope, spanning technical, financial, social, physical and geopolitical change all at once.

    It also argues that AI differs from earlier waves because it arrived into a world that was already organised, connected and digitally mature. In the report’s telling, the internet took years to build the conditions for mass diffusion, whereas generative AI could scale immediately on top of them. This makes AI both a product of prior technological compounding and a new multiplier on top of it. The report therefore treats AI as a step-change in how information is accessed, created and distributed, rather than as a simple continuation of software history.

    A further reason the report sees change as unusually fast is that the race is not only commercial but geopolitical. It repeatedly links AI progress to strategic competition, especially between the US and China, and suggests that this rivalry is intensifying investment, product release cycles and the urgency of deployment. In that sense, speed is presented not just as a market phenomenon but as a consequence of state-level and corporate competition feeding each other.

    2) What evidence does the report provide that AI adoption and usage are scaling at an exceptional rate?

    The report uses ChatGPT as its clearest proxy for AI adoption and argues that its scale-up has been historically extraordinary. One headline figure is that ChatGPT reached an estimated 800 million weekly active users by April 2025. Another is that BOND compares ChatGPT’s path to 100 million users with earlier consumer platforms and concludes that it reached that threshold far faster than services such as Netflix, LinkedIn, Instagram and TikTok. The argument is straightforward: AI is not merely growing quickly; it is outpacing the adoption curves of landmark digital products.

    The report also stresses how global that adoption is. One of its most striking comparisons is that around 90% of ChatGPT app users were outside North America by year three, whereas the internet took roughly 23 years to reach a similar share. That comparison underpins one of the report’s biggest claims: unlike earlier foundational technologies that spread outwards from the US over a long period, AI reached a global audience almost immediately. The geographic focus here is explicitly worldwide, though the report notes that availability constraints in places such as China affect the underlying app data.

    Beyond end users, the report points to rising developer adoption and ecosystem participation. It highlights 6 million developers in NVIDIA’s ecosystem and says Google reported more than 7 million developers building with Gemini, up fivefold year on year. This matters because the report is not only describing consumer enthusiasm; it is also arguing that the builder base around AI is widening quickly, which in turn supports more products, more infrastructure demand and more downstream usage.

    3) How does the report explain the economics of AI, especially the tension between rising investment and falling usage costs?

    A key theme in the report is that AI economics are pulling in two directions at once. On one side, training and infrastructure costs are high and still rising. BOND highlights very large capital expenditure by major US technology firms and shows the “Big Six” reaching $212 billion in capex in 2024, up 63% year on year. That supports the report’s broader claim that AI requires enormous spending on compute, data centres and model development.

    On the other side, the report argues that the cost of using AI is falling sharply for customers and developers. Its framing is that while frontier training remains expensive, inference is becoming cheaper and cheaper, which leads to wider access, more experimentation and increasing convergence in model performance. In other words, the barriers to building frontier systems remain high, but the barriers to using AI tools are falling. That combination is central to the report’s optimism about continued adoption.

    The report also makes clear that monetisation remains unresolved. One illustrative chart compares estimated revenue and compute expense for a leading US-based AI LLM company and shows strong revenue growth alongside very large compute losses. That supports a more nuanced economic reading: AI demand is real, but profitability is not yet settled. The report therefore presents the current phase as one in which consumers and enterprise users are benefiting from rapid improvement and falling usage costs, while producers are still absorbing heavy investment burdens.

    4) What does the report suggest about competition, monetisation and the global balance of power in AI?

    The report presents competition in AI as both fierce and structurally destabilising. It emphasises that incumbents, startups, open-source communities and state-backed ecosystems are all competing at once. One reason monetisation looks fragile, in BOND’s view, is that open-source momentum and Chinese advances are placing pressure on the pricing power and defensibility of leading US model providers. The report therefore does not portray the current leaders as secure winners. Instead, it describes a market in which advantage can erode quickly.

    That point becomes especially clear in its competitive charts. BOND shows relative desktop user-share shifts across leading LLMs and highlights the emergence of a Chinese model within a short period. It also repeatedly returns to US–China rivalry as a defining strategic frame, suggesting that AI leadership may translate into broader geopolitical influence. In this sense, the report sees AI not just as a commercial contest over products and margins, but as a contest over standards, platforms and long-term international dependence.

    At the same time, the report is not purely alarmist. Its perspective is broadly pro-innovation and cautiously optimistic. It argues that intense competition may accelerate progress, widen access and keep the field dynamic, even if it also increases uncertainty. But its assumptions are clear: AI is now a strategic domain, leadership matters, and no company or country can assume its position is fixed.

    5) What broader implications does the report identify for work, society and the physical world?

    The report argues that AI is moving beyond chatbots and software assistance into the “physical world” and the workplace. One example it uses is autonomous mobility in San Francisco, where an autonomous taxi provider’s operating-zone market share rises sharply over the period shown. That chart is meant to illustrate that AI is no longer confined to digital interfaces; it is beginning to reshape real-world services, logistics and robotics-related applications.

    On work, the report says change is already visible rather than merely speculative. A chart on US IT jobs shows AI-related postings rising strongly while non-AI postings decline over the same indexed period. The implication is not simply that more technology jobs are appearing, but that the composition of demand is changing. BOND’s broader argument is that AI is likely to reconfigure the nature of work, the skills that employers value and the kinds of roles that expand or contract.

    The report also addresses social implications in a wider sense. It includes a benefits-and-risks section that acknowledges the promise of AI for productivity, science and material abundance, while also flagging risks such as surveillance, persuasion, employment disruption, biased decision-making, cybersecurity problems and safety-critical misuse. That matters because the report is not making a narrow market-growth case. It is arguing that AI is becoming a civilisation-scale force whose effects will be economic, political and societal at the same time.

    Taken together, the report’s conclusion is that AI’s significance lies in its breadth. It is changing information flows, business competition, labour demand, public power and physical systems all at once. That is why BOND treats this moment less as a discrete technology story and more as a large-scale transformation in how economies and societies operate.

  • Reimagining Tomorrow by Global Alliance for PR and Communication Management

    Reimagining Tomorrow by Global Alliance for PR and Communication Management

    About the paper

    The report is an original global survey of how PR and communication professionals are adopting, governing, and thinking about AI in their work.

    It is based on 473 responses collected between 18 February and 17 April 2025, using a mix of multiple-choice and open-ended survey questions; the geographic scope is global, with respondents from Africa, EMENA, North America, Australia/New Zealand, Asia-Pacific, and South and Central America, although the report notes self-selection bias, regional variation, and an overrepresentation of smaller organisations.

    Length: 21 pages

    More information / download:
    https://globalalliancepr.org/reimagining-tomorrow-ai-in-pr-and-communication-management/

    Core Insights

    1) What is the central argument of the report about AI in PR and communication management?

    The core argument is that AI adoption is already widespread in the profession, but governance, ethics, training, and strategic leadership have not kept pace. The report presents PR and communication as a profession at an inflection point: practitioners are using AI enthusiastically, yet the structures needed to guide that use responsibly are still underdeveloped. On page 3, the report’s summary makes this tension very clear: 91% are allowed to use AI, but only 39.4% of organisations have responsible AI frameworks, and 38.3% have no constraints at all. It also argues that the profession’s most valuable future contribution is not merely technical implementation, but shaping ethical frameworks, governance structures, and stakeholder communication about AI.

    The interpretive section on page 4 pushes that point further. It says the real opportunity for PR and communication teams is to elevate their strategic role by helping organisations develop and implement responsible AI, rather than remaining focused on tactical use. In other words, the report is not anti-AI; it is pro-adoption but strongly argues that adoption without guardrails is risky and professionally shortsighted.

    2) What does the survey reveal about how widely AI is being used, and how organisations are managing that use?

    The survey shows that AI use is already mainstream in the field. According to the report, 91% of respondents say AI is allowed in their organisations, and among the 9% who say it is not allowed, 52.8% admit they use it anyway as “shadow AI.” That alone suggests that AI adoption is not waiting for formal permission structures. Access is also relatively broad: 65.2% say all team members in PR and communication have access, while 24.3% say access is restricted to select individuals and 10.5% say it is limited to leaders only.

    At the same time, management of AI is patchy. The report says 38.3% of organisations have no constraints or restrictions in place, 37.5% rely on approved company-wide tools, 35.8% allow staff to explore freely, and only 18.3% have formal processes for AI tool recommendation and approval. Organisational support is also middling: the average support rating for implementation is just 2.78 out of 5, which the report explicitly describes as moderate but insufficient. That is an important finding because it shows that permission to use AI is much more common than meaningful support for using it well.

    So the picture is not one of controlled institutional rollout. It is closer to democratised but uneven adoption: people have access, many are experimenting, but the quality of support, governance, and process is inconsistent.

    3) Where is the biggest gap between current AI practice and what PR professionals believe their role should be?

    The biggest gap lies between tactical activity and strategic responsibility. The report says PR and communication professionals see governance and ethics as their top priorities: 33.3% rank formal AI governance structures as the number one priority, and 27.3% rank training for ethical, safe, and transparent AI use as the top priority. Yet their actual involvement patterns do not fully reflect those priorities. The report’s alignment analysis shows that teams are often more involved in technical implementation than in the activities they themselves consider most strategically important.

    This mismatch is described in detail on page 9. The report highlights the largest misalignments in lower-value technical areas such as AI certification programmes, where the gap is 80.6%, and advising on complex prompts and use cases, where the gap is 60.4%. By contrast, the smaller gaps are in ethical AI use and formal AI governance, which suggests these are the areas closest to the profession’s intended role. The report interprets this as a resource allocation problem: teams are spending time where they are currently needed, but not necessarily where they believe they create the most value.

    This matters because it reframes the profession’s future. The report is effectively saying that PR should not define its AI contribution by being good at prompts or faster outputs. It should define it by governance, ethics, risk, literacy, stakeholder engagement, and strategic counsel.

    4) What specific weaknesses does the report identify in governance, confidence, and stakeholder communication?

    The report identifies three especially important weaknesses.

    First, governance remains thin.

    Only 39.4% of organisations have a responsible AI guideline, policy, or framework. Even where such frameworks exist, they are far from universal, and coverage is uneven. Among organisations that do have guidelines, the most common elements are ethics/law, governance/standards, security/privacy, and risk/reputation. The report also notes that because of skip logic, those framework-content percentages apply only to the subset of respondents whose organisations already have guidelines, not to the entire sample.

    Second, ethical confidence is limited.

    Only 26.2% say they feel very confident evaluating the ethical implications of AI in their roles; 60.5% are only somewhat confident, and 13.3% are not confident. The report treats this as a major training opportunity, not a marginal issue. That reading is reinforced by respondents’ own definitions of responsible AI, which emphasise ethics, beneficial use, human oversight, verification, and transparency.

    Third, stakeholder communication is surprisingly weak.

    Given that communication is the profession’s core function, the report finds it striking that fewer than half communicate about responsible AI approaches to stakeholders, 46.9% communicate about AI ethics, and only 35.6% communicate about AI governance structures. The most common topic communicated is simply how to use AI tools, at 53.6%, which the report interprets as evidence of a tactical rather than strategic focus. This is one of the report’s sharpest critiques: PR professionals are not yet communicating about AI in the way their own strategic position would suggest they should.

    5) What broader implications does the report draw for the future of the profession?

    The report suggests that AI will reshape the profession significantly over the next five years, pushing it away from routine production work and towards more strategic, advisory, and governance-oriented roles. Respondents predict shifts “from content creator to content facilitator,” more focus on strategy, more automation of routine tasks, possible workforce reduction, increasing regulatory complexity, and a risk of depersonalisation or diminished creativity.

    The concern side is equally strong. On page 13, respondents describe the main threats as job displacement, reduced creativity, authenticity problems, misinformation, and loss of human interaction. That combination shows the profession is not simply optimistic about efficiency gains; it is also worried about relevance, trust, and the erosion of distinctly human value.

    The report’s conclusion is that the profession can either be diminished by AI or elevated by it. Elevation depends on moving beyond content creation, building stronger governance and ethical frameworks, investing in training, communicating more actively with stakeholders, and positioning PR as a strategic advisor on responsible AI implementation across the organisation. Its recommendations to professionals and organisations alike all point in that direction. So the deeper implication is not just that AI will change communications work, but that it may redefine what counts as valuable communications leadership in the first place.

  • Communicating with Robots, Connecting to People by the Scriptorium Initiative

    Communicating with Robots, Connecting to People by the Scriptorium Initiative

    About the paper

    The whitepaper argues that AI will fundamentally reshape corporate communications over the next decade, especially through synthetic stakeholders, predictive systems, mass personalisation, and a renewed premium on human authenticity.

    Methodologically, it appears to be an expert whitepaper built on secondary analysis and illustrative examples rather than original empirical research; no fieldwork method, sample size, timeframe for data collection, or respondent base is clearly specified.

    The geographic focus is framed as global, but the evidence cited draws from a mix of U.S.-centric examples and selected international references, so the precise geographic boundaries of the underlying data are not clearly specified in the report.

    Length: 14 pages

    More information / download:
    https://page.org/knowledge-base/communicating-with-robots-connecting-to-people-nanne-bos-aegon/

    Core Insights

    1. What is the whitepaper’s central argument about how AI will change corporate communications?

    The central argument is that AI will not merely improve existing communication workflows but will transform the entire logic of corporate communications. The paper says the profession has already moved beyond asking whether AI will change communications and must instead focus on how that change will unfold. It frames AI as both a technological and geopolitical force, and suggests that the speed, scale, and sophistication of communication will be radically altered by systems such as GPT-4, Claude, and Grok.

    At the same time, the paper insists that the core purpose of corporate communications will remain stable. It explicitly says that communicators will still need to build trust, deepen understanding with stakeholders, maintain licence to operate, and influence behaviour. In other words, the mission stays the same, but the mechanisms and operating environment change dramatically.

    The whitepaper therefore presents AI not as a side issue or a tool trend, but as a structural shift that changes who receives messages, how they are interpreted, how fast they circulate, and what communicators are actually responsible for. Its five predictions are meant as a framework for navigating that transition while staying anchored in enduring communication goals.

    2. What does the paper mean by “synthetic stakeholders”, and why does it see them as so significant?

    The idea of “synthetic stakeholders” is one of the paper’s most important claims. It argues that, by the mid-2030s, people will increasingly rely on personal AI agents as their main interface with organisations. These agents will not simply summarise information; they will filter, verify, interpret, negotiate, and sometimes even decide on behalf of the human stakeholder. That means journalists, investors, employees, regulators, and customers may no longer engage with corporate communication directly, but through AI intermediaries.

    The report sees this as significant because it changes the locus of trust. Instead of stakeholders primarily trusting brands, institutions, or traditional media, they may trust their own AI agents more. That has major implications for reputation and influence. If AI agents become the gatekeepers of credibility, then communicators must create messages that are readable, interpretable, and verifiable by machines as well as by humans.

    The paper also links synthetic stakeholders to the “death of the single narrative”. It argues that AI agents will personalise information so extensively that there will no longer be one broadly shared version of a corporate story. Different stakeholders may receive materially different framings based on personal history, biases, preferences, and risk profiles. The implication is that communication becomes less about controlling one public narrative and more about maintaining coherence and credibility across many parallel, AI-mediated realities.

    3. How does the whitepaper describe the shift from mass communication to mass conversations and from reactive to predictive communications?

    The paper’s second and third predictions work together. First, it says the old broadcast model of one-to-many messaging is ending. In its place, organisations will engage in “mass conversations”: millions of simultaneous, AI-mediated, highly personalised interactions with stakeholders. These conversations will supposedly be context-aware, emotionally intelligent, and adapted to each person’s needs, role, behaviour, and preferences. Investors, employees, and customers would all receive tailored communication rather than standardised messages.

    This matters because the communicator’s role changes from crafting a single message to designing adaptive systems. The report suggests future communicators will define narrative models, supervise tone calibration, and audit huge numbers of micro-interactions. So communication becomes less a matter of publishing and more a matter of orchestrating intelligent, ongoing relationship management at scale.

    The move from reactive to predictive communications goes even further. The paper argues that AI will enable organisations to anticipate reputational risks, stakeholder disengagement, morale problems, or regulatory friction before they are visible through conventional means. It imagines AI systems that simulate possible stakeholder reactions, run communication scenarios in parallel, forecast trust impact, and identify likely virality or misinformation risks. In this model, communications becomes a foresight function rather than just a response function.

    Taken together, these two predictions describe a future in which corporate communication is continuous, personalised, and anticipatory. The communicator is recast as a strategist and overseer of adaptive systems, rather than primarily as a writer, spokesperson, or campaign manager.

    4. Why does the paper argue that human authenticity will become more valuable as AI becomes more powerful?

    The paper’s fourth prediction is that AI abundance will increase, not reduce, the value of human authenticity. Its reasoning is straightforward: as generative AI floods the information environment with cheap, abundant, low-value content, audiences will become more resistant to anything that feels synthetic or manipulative. The report refers to this as a coming “synthetic content crisis” and says AI filters will increasingly screen out content that lacks originality, emotional value, or resonance.

    In response, the communication that cuts through will be the communication that feels genuinely human. The paper highlights three qualities that will matter most: emotional depth, ethical clarity, and human voice. It argues that trust will increasingly attach to visible human sincerity rather than to polished, scaled, anonymous messaging. This is why it says communicators will become “custodians of authenticity” in a synthetic age.

    Importantly, the whitepaper does not frame this as an anti-AI argument. Instead, it advances the idea of “co-intelligence”: AI handles scale, complexity, translation, and real-time personalisation, while humans contribute judgment, moral reasoning, emotional nuance, vulnerability, and authenticity. So the paper’s conclusion is not that AI replaces human communication, but that the distinctively human elements become more strategically valuable as machine-generated communication proliferates.

    5. What are the report’s main implications for the future role, structure, and ethics of the communications function?

    The paper argues that the communications function will become AI-native. That means the department of the future will look very different from the traditional press-office or corporate affairs structure. Routine content production will increasingly be automated, while human professionals move into roles focused on oversight, orchestration, ethics, and strategic narrative design.

    It predicts new specialist roles such as:

    • AI Narrative Designers
    • Predictive Strategists
    • Communication Ethicists
    • and even Chief Narrative Intelligence Officers.

    It also says existing silos between internal communication, PR, investor relations, and brand strategy will weaken, giving way to a more unified narrative function powered by integrated AI systems. Teams may become smaller in headcount but more specialised in capabilities, drawing on disciplines such as linguistics, data science, behavioural psychology, and ethics.

    Ethics is a major theme here. The report repeatedly warns that predictive communications and AI-generated influence raise serious questions about manipulation, informed consent, transparency, and accountability. It therefore argues that strong governance frameworks will be essential, including explainable AI, clarity about data sources and model logic, and disclosure around synthetic humans or AI-generated messages. High-stakes moments such as layoffs, mergers, or crises are still presented as fundamentally human occasions in which AI should assist rather than replace human communicators.

    The deeper implication is that the future communicator is not just a better prompt writer or AI user. The role becomes more strategic, more cross-functional, and more ethically exposed. The paper’s perspective is that AI raises the bar for human communicators: they will need more judgment, more empathy, and more moral authority, not less.

  • State of Global Workforce 2025 by Gallup

    State of Global Workforce 2025 by Gallup

    About the paper

    The report synthesises Gallup’s annual global employee-experience research, combining Gallup World Poll data with additional random samples of working populations in the United States and an opt-in web component for China.

    It is an original quantitative research report based on surveys of employed adults aged 15+; the 2024 findings draw on 227,347 employed respondents collected from April to December 2024, within a wider 2009–2024 trend dataset of 5,490,517 respondents across more than 160 countries and areas.

    Methodological details are clearly stated, though some country results are suppressed where sample sizes are too small.

    Length: 141 pages

    More information / download:
    https://www.gallup.com/file/workplace/659528/state-of-the-global-workplace-2025-download.pdf

    Core Insights

    1) What is the central argument of the report about the state of the global workplace in 2025?

    Gallup’s central argument is that the global workplace is at a critical moment: employee engagement and wellbeing have deteriorated just as organisations are entering a period of major transformation driven by AI and broader workplace disruption. The report frames this as a leadership challenge rather than a purely economic or technological one. Leaders must decide whether to use this moment to strengthen management, reconnect teams and improve performance, or risk further decline.

    The report’s headline evidence is stark. Global employee engagement fell from 23% to 21% in 2024, only the second decline in the past 12 years and equal in size to the fall recorded during the year of COVID-19 lockdowns. Gallup estimates that this drop cost the global economy US$438 billion in lost productivity. At the same time, global life evaluation among employees fell to 33%, suggesting that workers’ overall sense of wellbeing has weakened as well.

    So the report is not merely saying that people feel a bit less positive about work. It is arguing that the workplace is becoming more fragile at exactly the point when organisations need resilience, adaptability and trust.

    2) What does the report identify as the main driver of declining engagement and wellbeing?

    Gallup is unusually direct: the main driver is managers. The report says manager engagement fell from 30% to 27%, while individual contributor engagement stayed flat at 18%. No other major worker category saw as large a decline. Young managers under 35 saw a five-point drop in engagement, and female managers saw a seven-point drop.

    The same pattern appears in wellbeing. Older managers saw a five-point decline in wellbeing, while female managers again recorded a seven-point drop. Individual contributors, by contrast, improved slightly on life evaluation. Gallup therefore presents managers as the pressure point where workplace strain is showing up first and most intensely.

    The report links this to the accumulation of post-pandemic disruption: retirements and turnover, the hiring boom and bust, rapidly restructured teams, tighter budgets, supply chain issues, changing customer expectations, digital transformation, AI tools, and new employee expectations around flexibility and remote work. Managers sit in the middle of all of that. In Gallup’s telling, they have become the human shock absorbers of organisational change.

    3) Why does manager engagement matter so much for organisational and economic performance?

    Gallup’s answer is that managers are the single biggest determinant of team engagement. The report states that 70% of team engagement is attributable to the manager. That means problems at management level do not stay there. They cascade downward into team morale, effort, productivity and retention.

    The report stresses that engaged employees are more productive, less absent, better at building customer relationships and more effective at generating results. It also notes that countries with less engaged managers tend to have less engaged individual contributors. So this is not just an internal HR issue. Gallup connects manager disengagement to broader business performance and even GDP growth.

    That is why the report repeatedly warns that if manager engagement keeps falling, the damage will not stop with managers and will not stop with engagement. Gallup presents manager burnout as a leading indicator of wider organisational decline: poorer performance, more absenteeism, more turnover, weaker team cultures and reduced economic output.

    4) What do the global and regional data reveal about the current pattern of employee experience?

    At global level, the picture is mixed but troubling. In 2024, 21% of employees were engaged, 62% not engaged and 17% actively disengaged. Only 33% were classified as thriving in life overall, while 40% reported daily stress, 23% daily sadness and 22% daily loneliness. Half of workers were watching for or actively seeking a new job.

    The regional pattern is highly uneven. On engagement, the highest regional levels were in the United States/Canada and Latin America/Caribbean, both at 31%, while Europe ranked last at 13%. On thriving, Australia/New Zealand led at 56%, followed by Latin America/Caribbean at 54% and the United States/Canada at 52%, while South Asia ranked lowest at 15%. Europe is notable for combining relatively high life evaluation with the lowest engagement, suggesting that people may feel comparatively well in life while still feeling detached from work.

    The emotional pattern is also revealing. Stress is especially high in the United States/Canada, Australia/New Zealand, East Asia and the Middle East/North Africa. Loneliness is highest in Sub-Saharan Africa and South Asia, while anger and sadness are most elevated in South Asia and parts of the Middle East/North Africa. Meanwhile, Europe has the lowest regional engagement but also among the lowest levels of anger and loneliness. This suggests that disengagement is not always accompanied by emotional volatility; in some regions it may look more like resignation or detachment.

    Another notable point is the work-location breakdown. Globally, exclusively remote employees show the highest engagement at 31%, compared with 23% for hybrid workers and 19% for on-site non-remote-capable workers. Hybrid and on-site remote-capable workers have the highest thriving scores at 42%, while fully remote workers report the highest loneliness, sadness and stress. So the report hints that flexibility may boost engagement and wellbeing in some respects, but also carries emotional trade-offs.

    5) What actions does Gallup recommend leaders take in response?

    Gallup’s prescription is focused almost entirely on rebuilding management capability. The report lays out three actions.

    First, ensure all managers receive training. Fewer than half of the world’s managers, 44%, say they have received management training. Gallup argues this is the most achievable intervention and says managers who receive training are half as likely to be actively disengaged as those who do not.

    Second, teach managers effective coaching techniques. Gallup cites evidence that participants in manager training focused on best practices saw up to 22% higher engagement than non-participants, their teams saw engagement rise by up to 18%, and manager performance metrics improved by 20% to 28%, with effects lasting nine to 18 months after training.

    Third, invest in ongoing manager development to improve wellbeing. The report says manager training can raise manager thriving from 28% to 34%, and when that training is paired with active encouragement for development, thriving rises to 50%. Gallup therefore treats manager development not just as a performance tool but as one of the most effective wellbeing investments leaders can make.

    This leads to the report’s broader conclusion: the role of the manager needs to be rethought. Gallup argues that improving manager engagement is the key lever for reversing declining productivity, improving employee wellbeing and unlocking a much larger economic upside. It estimates that if the world’s workplace were fully engaged, US$9.6 trillion could be added to the global economy, equivalent to 9% of global GDP.

    Overall, the report’s message is clear: the workplace problem is not simply that employees are tired or dissatisfied. It is that the management layer is under strain, and unless leaders strengthen it deliberately, the costs will spread through teams, organisations and economies.

  • Global Foresight 2025 by the Atlantic Council

    Global Foresight 2025 by the Atlantic Council

    About the paper

    The report is a mixed-methods foresight study on what the world may look like in 2035, combining an expert survey, short horizon-scanning essays on six under-the-radar “snow leopards,” and three written future scenarios.

    The original research element is a survey of 357 geostrategists and foresight practitioners drawn from the Atlantic Council’s networks, fielded in late November and early December 2024, with respondents spread across sixty countries plus the United States and representing every continent except Antarctica; the survey sample, however, skewed US-based, male, and older.

    Length: 84 pages

    More information / download:
    https://www.atlanticcouncil.org/content-series/atlantic-council-strategy-paper-series/global-foresight-2025/

    Core Insights

    1. What overall picture of the world in 2035 does the report present?

    The report presents a distinctly darker-than-light global outlook. Its central message is that many leading strategists expect the next decade to be shaped less by steady progress than by heightened instability, strategic rivalry, institutional weakness, and accumulating systemic risks. The report explicitly says that 62 percent of respondents think the world in ten years will be worse off than today, while only 38 percent think it will be better off.

    That pessimism is not absolute. The report notes some areas of guarded optimism, especially around artificial intelligence and climate cooperation. A majority of respondents think AI will have a net positive impact on global affairs over the next decade, and about half foresee expanded cooperation on climate change. But those brighter notes are outweighed by broader anxiety about war, nuclear risk, democratic decline, and geopolitical fragmentation.

    Structurally, the report is trying to do more than predict single outcomes. It says foresight cannot provide certainty, but it can help readers understand the forces already driving change and the possible consequences of those forces over the coming decade and beyond. That framing matters: this is not a forecast claiming “this will happen,” but an effort to map where expert opinion sees the heaviest risks and most consequential uncertainties.

    So the overall picture is of a world entering 2035 under pressure from several overlapping dynamics at once:

    • hard-power rivalry
    • erosion of the postwar order
    • weak prospects for conflict resolution
    • technological disruption
    • and climate-linked stress.

    The report’s worldview is therefore not just pessimistic but systemic: it suggests that multiple domains of instability are reinforcing each other.

    2. Which geopolitical and security risks do surveyed experts see as most likely to shape the next decade?

    The headline risk is major war. The report’s most striking finding is that 40 percent of respondents expect another world war by 2035, defined as a multifront conflict among great powers. It adds that this war could go nuclear and could extend into space, with 48 percent expecting nuclear weapons to be used by at least one actor in the coming decade and 45 percent expecting direct military conflict in space.

    The report identifies China and Russia as the main vectors through which a broader conflict could emerge. On China, 65 percent of respondents think Beijing will try to retake Taiwan by force within the next decade, a sharp rise from the previous year’s survey. On Russia, 45 percent think Russia and NATO will engage in direct military conflict, also a significant increase year-on-year. In other words, the report suggests that expert concern is moving away from abstract rivalry and toward concrete expectations of military confrontation.

    Another major concern is bloc formation. Just under half of respondents expect China, Russia, Iran, and North Korea to become formal allies by 2035, and many foresee a world divided into China-aligned and US-aligned blocs. The report treats this as a potentially war-amplifying trend rather than merely a diplomatic realignment. Respondents who foresaw both bloc division and formal alliance-building were much more likely also to expect world war.

    Nuclear proliferation is another core risk. The report says 88 percent of respondents expect at least one new country to obtain nuclear weapons in the next decade. Iran is by far the most cited likely new nuclear power, but expectations also rose for South Korea, Saudi Arabia, and Japan. On use, Russia and North Korea are seen as the most likely current nuclear powers to launch a nuclear strike.

    The report also shows pessimism about existing conflicts. On Ukraine, only 4 percent think the war will end on terms largely favourable to Ukraine; most expect either terms favourable to Russia or a frozen conflict. On the Middle East, respondents are much more optimistic about Israeli-Saudi normalisation than about Israeli-Palestinian peace. More than 60 percent expect the current status quo of occupied Palestinian territories to persist by 2035.

    Taken together, these findings suggest the report sees the coming decade as one in which escalation risks are rising across several theatres at once, while the mechanisms for resolving those conflicts appear weak.

    3. How does the report assess the future of US power, alliances, multilateral institutions, and democracy?

    The report’s view of the United States is nuanced: it still sees the US as the likeliest dominant military power in 2035, but a weaker and more uncertain leader in other domains. Seventy-one percent of respondents expect the US to remain militarily dominant, and 58 percent still see it as the leading technological innovator. But fewer expect it to dominate economically, diplomatically, or in soft power, and confidence has dropped across several of these measures compared with the previous year.

    That matters because the report implies that US power is increasingly relative rather than comprehensive. It is not presenting a picture of outright American collapse, but of a more limited United States operating in a multipolar world. Three-quarters of respondents expect the world in 2035 to be multipolar, with multiple centres of power.

    Alliances remain part of that picture, but with more uncertainty than before. A majority still expect the US to maintain its alliance network in Europe, Asia, and the Middle East, yet this figure fell sharply from the previous survey. At the same time, almost half expect Europe to achieve greater “strategic autonomy” by taking more responsibility for its own security. So the report suggests a future in which alliances may persist, but under new terms and with more burden-sharing or hedging.

    On multilateral institutions, the mood is much grimmer. Large majorities expect the United Nations, the UN Security Council, and the World Trade Organization to be less capable of solving problems by 2035 than they are today. The World Bank and IMF fare somewhat better, while respondents are relatively more hopeful about regional groupings such as ASEAN, the EU, and even BRICS. That pattern reveals an important assumption in the report: global governance is likely to weaken, while regional or alternative formations may gain relative importance.

    The report is similarly downbeat on democracy. Nearly half of respondents think today’s democratic recession will worsen into a democratic depression by 2035, while only 17 percent foresee a democratic renaissance. It also says 65 percent expect global press freedom to decrease. So the report does not treat democratic backsliding as a side issue; it sees it as one of the defining trends of the next decade.

    There is also a gender dimension to that pessimism. Women in the survey were more negative than men across several questions, especially about nuclear use, democratic decline, rights curtailment, and future US dominance. The report interprets this as reflecting persistent inequalities and the unequal burden crises place on women.

    4. What overlooked “snow leopards” does the report argue could have outsized future impact?

    One of the report’s most distinctive features is its “snow leopards” section: six under-the-radar developments that may not dominate headlines now but could become highly consequential. This is the horizon-scanning part of the report, and it broadens the analysis beyond headline geopolitics.

    1.The first is the threat that non-state actors could attack undersea cables.

    The report argues that the global digital and financial system depends heavily on these cables and that they are vulnerable not only to states but also to militant groups or terrorists. Its core point is that a relatively low-cost attack on critical subsea infrastructure could produce outsized disruption across communications, finance, and military operations.

    2. The second is enhanced geothermal systems.

    The report presents this as a low-carbon energy source with major underexploited potential, noting that if technological and cost barriers fall, it could become a significant contributor to electricity generation in the United States. This is framed not merely as a climate story but as a strategic energy-development story.

    3. The third is a new carbon-capture material, COF-999, described as a yellow powder that could dramatically reduce the cost and resource intensity of pulling carbon dioxide from the air.

    The report does not claim this solves climate change, but it treats the discovery as an example of the sort of scientific breakthrough that could shift the economics of mitigation.

    4. The fourth is rewilding.

    Here the report argues that land abandonment, urbanisation, changing food systems, and ecological restoration could together make much more land available for rewilding, with implications for biodiversity, carbon capture, tourism, and land use. It also notes trade-offs and possible backlash, so this is presented as a consequential but contested trend.

    5. The fifth is quantum batteries.

    The report uses this as an example of a frontier technology that may transform energy storage, with particular attention to medical devices, emergency systems, and electric mobility. The point is not that the technology is ready now, but that its eventual impact could be large if the science translates into scalable applications.

    6. The sixth is Gen Z’s vulnerability to misinformation.

    This may be the most sociologically revealing of the snow leopards. The report challenges the assumption that digital natives are naturally better at navigating false information, arguing instead that heavy social media exposure, algorithmic feeds, parasocial influence, and weak verification habits may leave this generation especially susceptible. The long-term implication is that future elites may enter positions of power with distorted information habits and weaker trust.

    Across all six, the deeper message is that the future will not be shaped only by visible great-power rivalry. It may also be shaped by overlooked vulnerabilities, scientific breakthroughs, and social shifts that sit below the surface until they suddenly matter.

    5. What do the report’s three scenarios suggest about the range of possible global futures—and what is the report ultimately trying to make readers understand?

    The report ends with three scenarios for 2035:

    1. “The reluctant international order”
    2. “China ascendant”
    3. and “Climate of fear.”

    These are explicitly presented not as predictions but as plausible futures designed to stimulate thinking. That distinction is crucial. The scenarios are a tool for exploring interaction effects between present-day trends, not for declaring which future is most likely.

    “The reluctant international order” imagines a world in which the rules-based international order has neither collapsed nor been revitalised. Cooperation persists because major powers and non-state actors still need it, even if they engage reluctantly and pragmatically. This scenario suggests that messy, improvised, partial cooperation may be more realistic than either liberal renewal or total breakdown.

    “China ascendant” imagines a world in which Beijing becomes the dominant global power, not through one dramatic rupture but through a slow shift enabled by US inwardness, economic influence, institutional repositioning, and strategic patience. The point here is that geopolitical transformation need not come through open war; it can happen gradually through hedging, institutional drift, and changing perceptions of who is reliable and effective.

    “Climate of fear” imagines a world where worsening climate instability drives migration, political conflict, democratic stress, and escalating interest in radical responses such as geoengineering. This scenario shows the report’s assumption that climate change is not just an environmental issue but a force multiplier affecting politics, conflict, mobility, governance, and public fear.

    Taken together, the three scenarios reveal the report’s deeper purpose. It is not merely asking, “What will happen?” It is asking readers to think about how today’s choices, vulnerabilities, and neglected signals can combine into very different but still plausible futures. That is why the report mixes survey data, horizon scanning, and narrative scenarios. It wants to move the reader from passive consumption of trends to active strategic imagination.

    The underlying perspective is clear: the future is not predetermined, but it is being shaped now by decisions on deterrence, alliance maintenance, institutional reform, climate action, technology governance, and democratic resilience. The report’s central implication is therefore strategic rather than descriptive: if leaders fail to act early on compounding risks, the darker futures it sketches become more plausible.

  • Future of Professionals Report 2024 by Thomson Reuters

    Future of Professionals Report 2024 by Thomson Reuters

    About the paper

    Thomson Reuters’ Future of Professionals Report 2024 examines how AI and GenAI are reshaping professional work across legal, tax, accounting, global trade, risk, fraud, compliance, government, and corporate C-suite roles.

    It is original survey research based on 2,205 responses collected through 15–20 minute surveys, with respondents across the United States, UK, Canada, Mainland Europe, Latin America, Asia-Pacific, Africa, and the Middle East/North Africa.

    The report is heavily AI-focused because respondents identify AI as the dominant force currently driving change in professional services.

    Length: 37 pages

    More information / download:
    https://www.thomsonreuters.com/en-us/posts/technology/future-of-professionals-2024/

    Core Insights

    1. What is the central argument of the report?

    The report argues that AI and GenAI are now the dominant forces reshaping professional work, not as distant possibilities but as practical technologies already influencing strategy, workflows, value creation, pricing models, and career expectations.

    The strongest evidence is that 77% of respondents believe AI will have a high or transformational impact on their work over the next five years, up from 67% in the 2023 report. The report presents this as a shift from speculative concern to more concrete expectation: professionals are no longer merely wondering whether AI matters; they are beginning to understand where and how it will affect their daily work.

    The report’s tone is notably optimistic. Thomson Reuters concludes that AI can make professional work more efficient, productive, and fulfilling. It repeatedly frames AI as a way to release professionals from routine or labour-intensive tasks so they can focus on judgement-based, strategic, client-facing, and higher-value work.

    However, the report does not argue that AI adoption will be automatic or risk-free. Its central argument is conditional: AI can be a force for good, but only if organisations combine adoption with responsible use, human oversight, data security, transparency, training, and new business models.

    2. How are professionals currently using AI, and what does this reveal about adoption maturity?

    Current AI use appears practical but still relatively early-stage. Respondents most commonly use AI-powered technologies for drafting documents, summarising information, conducting basic research, preparing communications, reviewing documents, and generating first drafts.

    The report says 50% of respondents who have used AI as a starting point describe its output as “a basic starting point” where they still need to do most of the work. Another 28% say it provides “a strong starting point” that mainly requires editing. This suggests that AI is already useful, but professionals still see it primarily as an assistant rather than an autonomous producer of reliable final work.

    The main barriers among non-users are also revealing. Concerns centre on accuracy, data security, ethics, uncertainty about what AI can be used for, and uncertainty about how to access it. The report notes generational differences too: Gen Z professionals have tried AI at higher rates, while baby boomers show lower current usage but surprisingly ambitious expectations for future AI assistance.

    The adoption picture is therefore mixed: AI is already embedded in common professional tasks, but many users still regard it as a productivity aid that requires significant human review. The report’s own interpretation is that trust will depend on transparency, benchmarking, responsible innovation, and better user education.

    3. What productivity and value gains does the report expect from AI?

    The report’s most concrete productivity claim is that AI could free up four hours per professional per week within one year, eight hours within three years, and twelve hours within five years. Based on an assumption of 48 working weeks per year, that would equal roughly 200, 400, and 600 hours respectively.

    This is one of the report’s most important findings because it connects AI adoption to organisational strategy. Freed-up time is not presented simply as a cost-saving mechanism. Respondents say they would use additional time for work-life balance, client work, long-term projects, business development, process improvement, strategic planning, research, training, and better workload management.

    The report also distinguishes between efficiency and value. More than half of professionals are excited about AI because of time savings and productivity improvements, but 39% are most excited about AI’s ability to add new value to their work. Examples include handling large volumes of data more effectively, improving client response times, reducing human error, enabling advanced analytics, and supporting better decision-making.

    This distinction is crucial. The report does not merely say AI will help professionals do the same work faster. It argues that AI may allow professional services to change what kind of work is done, what quality of service is delivered, and where professionals focus their expertise.

    4. What risks, ethical concerns, and governance needs does the report identify?

    The report identifies several persistent concerns:

    • accuracy of outputs
    • data security
    • ethical use
    • overreliance on AI
    • inadequate human judgement
    • and unclear accountability.

    These concerns are especially important because the professions covered in the report often involve legal, regulatory, financial, compliance, or high-stakes advisory work.

    Professionals draw a clear ethical boundary around full AI autonomy in high-stakes professional judgement. More than 95% of legal and tax respondents say it would be a step too far for AI to represent clients in court or make final decisions on complex professional matters. Legal professionals are particularly resistant to AI providing legal advice, while respondents in tax, risk, fraud, and compliance appear somewhat less opposed to AI involvement in strategic advice.

    The report finds no single consensus on responsible AI use, but several principles recur. Almost two-thirds of respondents see data security as vital, both for prompts and outputs. A similar share see compulsory human review as critical. Other important elements include transparency about data sources, clarity on which tasks AI may be used for, bias mitigation, deletion of personal data, and standards for training data.

    On enforcement, respondents favour certification processes for AI systems and standards developed by professional or industry bodies. Government regulation, company guidelines, whistleblowing, and algorithm audits are also mentioned, but the report presents certification and professional standards as the leading options.

    5. What are the broader implications for professional careers, leadership, and business models?

    The report’s broader implication is that AI will shift the nature of professional work rather than simply eliminate it. Fear of widespread job loss appears less prominent than in the previous year’s report. Instead, 85% of respondents believe new or additional roles will be created to manage broader AI use.

    The human skills expected to become more important include problem-solving, creativity, judgement, strategic thinking, and the ability to manage AI responsibly. The report therefore frames the future professional not as someone replaced by AI, but as someone who must become better at using AI while preserving human expertise.

    For leaders, the report implies that AI adoption is not just an IT project. It affects talent strategy, operating models, pricing, client value, workflow design, risk management, and organisational culture. Leaders are advised to assess skills, invest in training, create responsible AI principles, run pilot projects, scale successful use cases, and explore how AI can open new sources of stakeholder value.

    The pricing implication is especially significant for professional services firms. Many respondents expect hourly-rate pricing to decline over the next five years. As AI makes routine work faster, firms will need to explain why clients should still pay premium fees for work completed more efficiently. The report argues that firms must move towards value-based pricing and become better at articulating the value AI adds beyond speed.

    The conclusion is optimistic but demanding: AI can make professional careers more fulfilling and organisations more competitive, but only for those that actively embrace the technology, redesign work around it, and take responsibility for its limits.

  • Future of Professionals Report 2023 by Thomson Reuters

    Future of Professionals Report 2023 by Thomson Reuters

    About the paper

    Thomson Reuters’ Future of Professionals Report 2023 examines how AI, especially generative AI, is expected to transform professional work across legal, tax and accounting, risk, compliance, corporate and government settings.

    It is original survey research based on a web survey conducted in May–June 2023 among more than 1,200 professionals, with about half based in the US and most of the rest in the UK, Canada and Latin America.

    The report combines survey findings with Thomson Reuters’ own interpretive commentary, so it should be read as a research-based thought leadership report rather than a neutral academic study.

    Length: 36 pages

    More information / download:
    https://www.thomsonreuters.com/en-us/posts/technology/future-of-professionals-2023/

    Core Insights

    1. What is the central argument of the report?

    The report’s central argument is that AI will not merely make professional work faster; it will reshape the value proposition of professional services. Thomson Reuters presents AI as a catalyst for transformation across three linked dimensions: productivity, professional value, and responsible adoption.

    The productivity argument is the most immediate. Professionals expect AI to help with operational efficiency, research, document review, drafting, administrative work, risk identification, regulatory monitoring and client communication. The report repeatedly frames AI as a way to remove repetitive or low-value work so that professionals can spend more time on higher-value advisory tasks.

    The deeper argument is about the future role of professionals. The report suggests that “Professional 2.0” will be less defined by routine technical execution and more by judgement, strategic advice, client service, specialisation, and the ability to use AI effectively. It argues that AI will shift professionals from doing more work manually to orchestrating, checking, interpreting and adding value to AI-enabled work.

    The report is optimistic, but not naïvely so. It recognises fears around accuracy, job loss, ethics, data security, regulation, work-life balance and professional identity. However, Thomson Reuters’ overall position is clear: AI will not replace highly trained professionals wholesale, but professionals who use AI will outcompete those who do not.

    2. How do professionals expect AI to affect productivity, client service and business performance?

    Professionals in the report are broadly positive about AI’s operational potential. A key headline finding is that 67% expect AI or generative AI to have a transformational or high impact on their profession over the next five years. That makes AI the most significant trend tested in the study, ahead of economic recession and the cost-of-living crisis.

    The report identifies several productivity gains. In law firms, AI is expected to help with large-scale data analysis, non-billable administrative work, time recording, research and document-related tasks. In tax and accounting, respondents see potential in analysing deductions, income streams, tax scenarios and future tax results. In corporate and government departments, AI is expected to streamline internal processes, reduce external spend, improve research and speed up document review.

    Client service is another major theme. Respondents expect AI to improve the speed, clarity and consistency of communication. The report mentions AI helping draft and edit client communications, translate complex ideas into plain language, identify client needs arising from regulatory change, and support faster internal advice. For in-house teams, the report suggests that AI may strengthen their role as business partners by helping them provide more consultative, growth-oriented advice.

    However, the financial consequences are less clear. Firms may become more profitable if AI reduces costs and frees professionals for higher-value work. At the same time, clients may use AI as a reason to push fees down, move more work in-house, or turn to alternative legal service providers. The report does not claim certainty here; it explicitly notes that the “financial victor” remains uncertain.

    3. What evidence does the report provide that AI will change professional roles, skills and career paths?

    The report argues that AI will fundamentally alter who does professional work, what skills are valued, and how people enter and progress within the professions.

    One of the strongest findings is that 64% of professionals believe AI will make their professional skills more highly valued, while 33% fear that AI could contribute to the demise of their profession or reduce demand for their skills. This tension runs throughout the report: professionals see opportunity, but also existential risk.

    The report expects new career paths to emerge. It suggests that some work currently performed by credentialed professionals may shift to paralegals, junior professionals, enrolled agents, legal tech consultants, operations specialists or other non-traditional roles. It also anticipates more hybrid roles combining professional expertise with technology, data science, IT, security, regulatory and AI skills.

    Training is presented as one of the clearest areas of change. Almost 90% of respondents expect basic mandatory AI training for all professionals within five years, and 87% expect everyone to need training in new skills. The report also predicts changes in how junior professionals are trained and in the nature of university or college education.

    A particularly important nuance is that AI may reduce traditional entry-level work. More than half of respondents expect a decline in entry-level roles over the next five years, yet a majority also expect the total number of professionals in their firm or department to increase. In other words, the report does not predict simple job destruction. It predicts a reshaping of the professional labour market: fewer traditional junior tasks, more specialised or AI-enabled roles, and greater need for adaptability.

    4. What are the main concerns, risks and barriers identified in the report?

    The report identifies several overlapping concerns.

    The biggest fear is accuracy. A quarter of respondents cite compromised accuracy as their greatest concern. This is especially important because professionals work in fields where errors can have legal, financial, ethical or regulatory consequences. The report stresses that AI outputs must be checked by humans rather than accepted at face value.

    Job loss and professional displacement are also major concerns. Nineteen per cent cite widespread job loss as their biggest fear, while 17% cite the demise of the profession. Some respondents fear that AI may “dumb down” professional judgement if people rely on machine-generated answers without understanding the underlying reasoning.

    Ethics and data security are also prominent. Fifteen per cent cite data security as their biggest fear, and another 15% cite loss of ethics. The report connects these concerns to the need for transparency, explainability, trustworthy sources, professional standards and regulation.

    The biggest barrier to change is cultural rather than technical. The report says 83% of professionals cite risk aversion or fear of change as a top-three barrier within the professions. Lack of technology skills, lack of investment, partnership models, and lack of diversity of thought are also identified as obstacles.

    Finally, the report is ambivalent on wellbeing. AI could reduce long hours, lower the risk of errors, and remove mundane work. But some respondents fear it could increase pressure, reduce human connection, worsen engagement, or create anxiety about disposability. The report therefore treats wellbeing as both a potential benefit and a risk depending on how AI is implemented.

    5. What is Thomson Reuters’ perspective, and what are the implications of the report?

    Thomson Reuters’ perspective is strongly pro-adoption, but framed around responsible implementation. The company argues that AI should be embraced decisively, but with guardrails around trust, ethics, transparency, accuracy, regulation and human oversight.

    Its assumptions are visible throughout the report. Thomson Reuters assumes that AI adoption is inevitable, that productivity gains will be substantial, and that the professions will be reshaped rather than destroyed. It also assumes that the highest-value professional work will remain human-centred: advice, judgement, client relationships, ethics, interpretation and strategic thinking.

    The report’s implications are significant. For firms, it suggests a need to rethink pricing, services, staffing models, training and competitive advantage. For in-house departments, it suggests an opportunity to move from cost centres to growth enablers, particularly if AI helps them deliver more consultative advice and bring more work in-house. For individual professionals, the implication is that passive adaptation will not be enough. They will need to develop AI literacy, deepen expertise, understand their own value proposition, and learn how to work with AI rather than around it.

    The broader conclusion is that trust will be the decisive condition for AI adoption in professional work. Without confidence in accuracy, data security, ethics and explainability, the promised productivity gains may not materialise. With the right governance, however, the report argues that AI can improve productivity, increase professional value, create new roles, support better client service and potentially improve wellbeing.