Global Risks Report 2024
Global Risks 2034: Over the limit
This chapter focuses on the longer-term horizon, highlighting risks that may become the most severe over the next decade. While the short-term risks landscape described in Chapter 1 may, if not addressed, contribute to these negative, longer-term outcomes, attention, planning and action today can still set us on a markedly more positive trajectory.
2.1 The world in 2034
The next decade will usher in a period of significant change, stretching our adaptive capacity to the limit. GRPS respondents are far less optimistic about the outlook for the world over the longer-term than the short term. As noted in Chapter 1, nearly two-thirds (63%) of respondents to the GRPS predict a turbulent or stormy outlook, with upheavals and an elevated risk of global catastrophes at best (Chapter 1, Figure 1.1).
Comparing the two- and 10-year time frames reveals a deteriorating global risks landscape. Thirty-three of the 34 global risks increase in severity score over the longer term, reflecting respondents’ concerns about the heightened frequency or intensity of these risks over the course of the 10-year horizon (Figure 2.1).
Environmental and technological risks are among those expected to deteriorate the most in severity over this period and dominate the longer-term global risks landscape. Nearly all environmental risks are included in the top 10 rankings for the decade ahead (Figure 2.2). Extreme weather events are anticipated to become even more severe, as the top ranked risk over the next decade. Mirroring last year’s results, the perceived severity of Biodiversity loss and ecosystem collapse worsens the most of all risks, increasing by a full two Likert points, rising from #20 in the short-term to 3rd place. Critical change to Earth systems (#2) and Natural resource shortages (#4) are also among those perceived to materially deteriorate, contributing to their entrance into the top 10 ranking of risks over the next 10 years, while the related risk of Involuntary migration rises one place to #7 over the next decade. Pollution remains in 10th place. In contrast, Non-weather related natural disasters (#33) falls close to the bottom of rankings over both time horizons, likely reflecting the nature of such a tail risk and the often geographically isolated nature of these events.
These results highlight divergent perceptions around the comparative urgency of environmental risks. Biodiversity loss and ecosystem collapse (#20 in the two-year time frame) and Critical change to Earth systems (#11 in the two-year time frame) feature in the longer-term rankings for all stakeholder groups (Figure 2.3). However, it appears that younger respondents prioritize these risks as a more urgent concern, ranking them higher in the two-year period compared to other age groups (Chapter 1, Figure 1.6). Private-sector respondents, unlike those from civil society or government, feel that most environmental risks will materialize over a longer time frame (Figures 1.5 and 2.3). This dissonance in perceptions among key decision-makers could mean the time to act may soon pass, without sufficient progress made (Chapter 2.3: A 3◦C world).
Concerns around the possible implications of recent technological developments are also clearly evident. Adverse outcomes of AI technologies is anticipated to experience one of the largest deteriorations in severity. It rapidly rises from #29 over the two-year period to #6 over the 10-year period, likely reflecting the possible systemic or even existential nature of related risks as AI penetrates economic, social and political systems (Chapter 2.4: AI in charge). Despite worsening severity scores over this time frame, the most prominent technological risks in the short term, Misinformation and disinformation and Cyber insecurity, drop in ranking but remain in the top 10 over the longer-term, at 5th and 8th place, respectively. The related risk of Societal polarization also drops from 3rd place in the short term to 9th place over the longer-term horizon.
Despite a small increase in perceived severity, the societal risk of Lack of economic opportunity falls from #6 over two years to #11 in the global rankings; however, it makes the top 10 rankings for both civil society and academia respondents over the longer-term horizon (Figure 2.3). The divergence from perceptions of the public sector – which do not rank this risk in the top 10 – coupled with the long-term, cumulative effects of a low-opportunity world on the next generation make this a risk to watch over the coming years (Chapter 2.5: End of development?). The related economic risk of Illicit economic activity is perceived to be of lower severity over both time periods. However, it is seen to be driven by several risks ranked in both the short- and longer-term top 10, suggesting it may be an underappreciated risk over the coming decade (Chapter 2.6: Crime wave).
Inflation is the only risk with a severity score predicted to improve over the next decade, and it moves from #7 to #32. In fact, most economic risks fall rapidly in comparative rankings of risk perception over the next decade, with, for example, Economic downturn dropping from #9 to #28 over the longer-term horizon. This may reflect that Geoeconomic confrontation (#16), a key driver of many of economic risks, has decreased significantly in perceived severity over both time horizons when compared to last year’s scores.[i]
Indeed, geopolitical risks are a noticeably absent from the top 10 rankings over the next decade. Interstate armed conflict exhibits the same long-term severity score as last year but falls from 5th to 15th place over the 10-year period. Similar to last year, Terrorist attacks sits in the bottom left quadrant of Figure 2.1, indicating lower perceived severity over both the short and long term. While the latest available data indicates that overall lethality remains contained compared to other risks, at 6,701 global fatalities in 2022, terrorism has the potential to spark broader conflict and unrest, such as the current conflict in the Middle East.[ii]
2.2 Structural forces
Across several spheres – geostrategic, technological, climatic and demographic – we are transitioning to a new underlying set of conditions and parameters. These shifts form the backdrop to the global risks that will play out over the next decade. This year, the Global Risks Report introduces the concept of structural forces to our analysis of global risks over the next decade.[iii] We define these as the long-term shift in the arrangement of, and relation between, the systemic elements of the global landscape. These forces have the potential to materially impact the speed, spread or scope of global risks, and will be influenced in turn by each other.
There are four structural forces that are the most materially influential to the global risks landscape. These are summarized in Box 2.1[iv] and include: technological acceleration; geostrategic shifts; climate change; and demographic bifurcation. While all four forces have global ramifications, some, such as the changing climate, are more multi-directional in their development, which could allow for several potential futures. Similarly, while all represent longer-term shifts to the structural landscape, some have the potential to manifest more quickly due to underlying variables. Geostrategic shifts, for example, may lead to a lack of alignment between powers, while technological acceleration can foster new discoveries that transform systems rapidly.
As these structural forces interact, we consider four emerging global risks and how they may evolve over the next decade:
– Earth systems: all stakeholder groups agree that Critical change to Earth systems (#2) poses one of the most severe risks faced over the next decade. Could anthropogenic (in)action and climate change push select Earth systems past the tipping point, catapulting towards a 3◦C world to which we cannot adapt?
– AI technologies: a number of Adverse outcomes of AI technologies (#6) are anticipated to rapidly rise over the next decade. Could powerful frontier technologies destabilize global economic and security dynamics and put tech – and its concentrated owners – in charge?
– Human development: featuring as a top risk over the two-year period and just out of the top 10 over the next decade, Lack of economic opportunity (#11) is a persistent but lower priority risk forglobal decision-makers over the longer-term horizon. Could closing developmental pathways leave vulnerable populations and countries, and the next generation, with little hope for a brighter future?
– Organized crime: Illicit economic activity (#31) is one of the lowest-ranked risks in the global risks network, but the convergence of several top-ranked risks could turn an under-the-radar chronic risk into a pressing crisis. Will transnational crime networks subsume fragile states and vulnerable populations, capitalizing on highly disruptive technologies and weakened state capacity?
The futures highlighted in each of the following sections is only one of a multiplicity of possibilities, and we highlight opportunities to shape a more positive path forward by acting today.
2.3 A 3◦C world
– Thresholds for large-scale and self-perpetuating changes to planetary systems are likely to be exceeded within the next decade.
– The pace and scale of climate-change adaptation efforts are already falling short, with societies increasingly exposed to environmental impacts to which they may be unable to adapt, fueling displacement and migration.
– Nascent mitigation technologies, while attractive in some respects, could have unintended environmental and social consequences, with implications for legal liabilities, geopolitical dynamics and the climate agenda.
Current trajectories of global warming mean that at least one “climate tipping point”[v] (or the threshold at which long-term, potentially irreversible and self-perpetuating change to a planetary system occurs) could be passed within the next 10 years.[vi] Under nearly all Intergovernmental Panel on Climate Change (IPCC) scenarios, the 1.5°C threshold will be crossed in the early 2030s.[vii] Based on the latest research, at least four systems are considered likely to tip at 1.5°C (Figure 2.5): low-latitude coral reefs die-off (high confidence), collapse of the Greenland and West Antarctic Ice Sheets (high confidence), and abrupt thawing of permafrost (medium confidence).[viii] There is also new evidence to suggest that the North Atlantic Subpolar Gyre circulation could additionally be placed at risk at 1.5°C, while the boreal forest, mangroves and seagrass meadows will start to become vulnerable.[ix]
With Critical change to Earth systems a new entrant to the global risks list this year, all stakeholder groups agreed that it poses one of the most severe risks faced over the next decade (Figure 2.3). While these changes emerge comparatively silently, with their effects building over the long term, impacts are felt on a systemic level, intensifying impacts to food, water and health security. Yet as the need for climate solutions become more urgent, the risk of technology-induced tipping points – such as from geoengineering – will also grow.
Breached thresholds
It remains challenging to define climate tipping points and assess their likelihood. However, the latest research increasingly suggests that long-term changes to planetary systems will be triggered over the next decade, possibly without the world realizing that the point of no return – the point of intervention - has passed. Importantly, most of the IPCC scenarios allow for temperature overshoot – however, the breaching of critical thresholds will trigger long-lasting and fundamental changes,[x] with a fresh set of climate and environmental conditions that could rewrite our collective understanding of the risks posed by climate change.
While recent research suggests that the trajectory of 1.5°C may be locked in regardless of action taken today, estimates relating to climate tipping points may be conservative or even optimistic.[xi] Most climate models, whether public, private or academic, do not adequately capture non-linear impacts. For example, the transition of the Amazon into savannah will likely be caused by a combination of climate and ecological impacts, possibly transitioning well before 3°C of warming (Figure 2.5), due to land-use changes and deforestation. [xii] Most models also fail to capture the interconnectedness of these systems: how could cascading effects from the passing of one tipping point lower the critical threshold for others? For example, melting of the Greenland Ice Sheet could lead to an influx of fresh water, destabilizing the Atlantic Meridional Overturning Circulation (AMOC) and creating conditions that melt the West Antarctic Ice Sheet faster.[xiii]
Early warning signs suggest that several systems, including the Greenland Ice Sheet, AMOC and Amazon rainforest, are losing resilience,[xiv] and it is possible that some critical thresholds have already been crossed.[xv] Indeed, not all tipping points will be observed. Some will manifest as distinct changes, such as an ocean heatwave that precipitates the collapse of coral reefs. The “edge” of these thresholds can be sharp – for example, the point at which the Greenland Ice Sheet reflects less heat than it absorbs. But not all tipping points will be visible at the current level of modelling and monitoring. The comparatively slow velocity of most critical changes to Earth systems – time between the tipping point and when impacts are fully felt – means that most will be silent, with impacts gradually building over the longer-term.
As such, climate tipping points are risks that are well-known but not necessarily well-understood. GRPS results indicate that the impacts of climate change are well-recognized by global decision-makers. However, if critical changes to Earth systems are seen as longer-term risks – with likelihoods or impacts underestimated, or simply dismissed as too uncertain – intervention may come too late to prevent cascading planetary change, hindering our ability to fully adapt to related impacts.
Limits to climate adaptation
Over the next 10 years, many economies could remain largely unprepared for these non-linear impacts of climate change. This is not the first time that abrupt changes to our planetary system have occurred: tipping points in our planet’s history have led to alternative stable states to which life has adapted over time.[xx] Rather, the risk is posed to socioeconomic structures: is the alternate state one to which we as human societies can adapt?
Climate tipping points could result in a socio-environmental crisis, intensifying current risks. GRPS respondents foresee a highly related cluster of environmental risks, with bilateral connections to Critical change to Earth systems. This includes Biodiversity loss and ecosystem collapse, Extreme weather events and Pollution, with strong potential to lead to Natural resource shortages (Figure 2.6). Alongside environmental impacts, several GRPS respondents also highlight possible socioeconomic implications, including Involuntary migration, Chronic health conditions, Infectious diseases and Economic downturn. Indeed, as explored in last year’s Global Risks Report (Chapter 2.2 Natural ecosystems), this nexus of socioenvironmental risks have the potential to accelerate climate change, through the release of emissions, and amplify related impacts, threatening climate-vulnerable populations.
The collective ability to adapt to these impacts may be overwhelmed by several factors. First, adaptation efforts are unlikely to radically progress over the next decade, particularly in the most climate-vulnerable economies. Despite persistent and extreme weather impacts, Failure of climate-change adaptation was a top-five risk in only six countries for the two-year time frame (compared to 16 in 2023). Figure 2.7[xxi] presents a regional comparison of the latest Executive Opinion Survey (EOS) results, highlighting a number of climate-vulnerable markets across developing regions (shaded orange),[xxii] but where a failure to adapt to climate change is not a relatively high concern for some. This likely reflects far more pressing challenges, including state fragility, poverty and conflict – such as in Yemen and the Democratic Republic of the Congo – but could hinder climate-adaptive action from being undertaken, in advance of these impacts intensifying further.
Indeed, adaptation efforts in developing countries could be constrained by finances, paired with the sheer scope of infrastructure investment needs over the next decade (Figure 2.8).[xxiii] As the fragility of highly-exposed, low-resilience states rises, internal conflicts and border clashes over resources could become more common (Chapter 1.4: Rise in conflict),[xxiv] and many countries could increasingly be seen as too high risk to operate or invest in (Chapter 2.5: End of development?), eroding adaptive capacities further. Related socioeconomic tipping points – such as land abandonment or the exit of investment and insurance in high-risk regions – could therefore occur even before planetary tipping points are demonstrably breached.[xxv] Advanced economies will not be insulated from some of these effects. For example, in Australia nearly 521,000 homes are predicted to be uninsurable by 2030 due to the risks of extreme weather.[xxvi]
In addition, long lead times for developing appropriate infrastructure may challenge readiness for regional or local changes that manifest abruptly. For example, the collapse of coral reef systems – which absorb more than 90% of wave energy – could leave coastal communities vulnerable to storm surges, potentially doubling annual flood damage on a global scale.[xxvii] Extreme weather, a parallel phenomenon occurring alongside planetary changes, is mutually reinforcing: the former can push a planetary system into an alternative state (for example a heatwave collapsing coral systems), while many of the climate tipping points are anticipated to shift weather patterns and increase extreme weather in turn, creating positive feedback loops of greenhouse gas emissions.[xxviii]
Together, these environmental and planetary changes could radically impact economic growth and insurability over the next decade,[xxix] driving food, water and health insecurity. Immediate impacts could reduce agricultural productivity and potentially cause simultaneous harvest failures in key regions. For example, some studies suggest that the loss of significant ice mass from the Greenland Ice Sheet could lead to droughts and agricultural loss in the Sahel region, in northern Africa, at the same time as it reduces marine primary productivity in the North Atlantic.[xxx] Although specific geographic impacts are highly complex due to the influence of multiple planetary systems, food and water insecurity are a key source of exposure – or leverage – for several global and regional powers. China, South Korea, Japan, Russia and Saudi Arabia are among the largest net importers of food and agricultural products, whereas Argentina, Australia, Brazil, Canada, New Zealand, Thailand and the United States comprise some of the largest exporters.[xxxi] At a domestic level, intensifying competition for resources could spark disputes over dwindling freshwater sources, arable land and habitable areas. On the international stage, changes to agricultural productivity and water availability could alter global trade patterns and alliances, or even become a bargaining chip in the contentious management of migration flows between host countries, adding an additional layer of complexity to shifting geostrategic dynamics.
There are also clear limits to adaptation, and tipping points will induce changes that, although longer-term in nature, are likely to overwhelm even well-implemented adaptation solutions and make relocation and migration more likely.[xxxii] For example, the Thwaites Glacier, which plays a key role in stabilizing the West Antarctic Ice Sheet, may have already passed an irreversible tipping point.[xxxiii] Although research is evolving and impact time frames are highly uncertain, this could cause a sea level rise of more than half a metre, or, through the destabilization of the West Antarctic Ice Sheet, up to 3.2 metres over longer timescales according to some estimates,[xxxiv] dramatically altering coastlines and submerging some island states (Figure 2.9).[xxxv]
Technological tipping points
As critical thresholds are breached, the pressure to act fast and at scale will mount, and the focus of the Net Zero agenda will increasingly expand beyond decarbonization, to the “reversal” of climate change through frontier technological solutions, like geoengineering.[xl] However, these nascent technologies could pose severe externalities of their own, raising complex questions around accountability.
Geoengineering solutions have the potential to counter key drivers to climate change and related environmental impacts. Some directly remove carbon dioxide from the atmosphere (for example, through direct air capture and carbon storage), while others intervene to cool the climate, such as solar radiation management (SRM).[xli] Investment in carbon capture and storage has already doubled to hit a record high of $6.4 billion in 2023, and the United States has already granted $1.2 billion in long-term funding to two Direct Air Capture hub developments in the states of Texas and Louisiana[xlii] – a bipartisan move that could survive the outcomes of the 2024 elections.
Deployment of geoengineering technologies is nuanced, posing global benefits but also presenting system-wide and localized risks. First, a growing focus on “abated” emissions (fossil fuel emissions caught through technologies) could shift capital and focus away from emissions reduction and adaptation. This complacency could take hold before carbon removal is able to sufficiently scale over the next decade, given significant infrastructure and investment requirements, resulting in an overall slowdown in climate mitigation at a critical time.
Second, dependent on the specific frontier technology in question, consequences are unknown or highly uncertain. Deployment could possibly lead to unintended changes to, for example, regional precipitation.[xliii] In addition, geological storage of carbon risks future “venting”, with potentially harmful consequences for nearby communities.[xliv] SRM could reduce the frequency and intensity of temperature extremes, but involves significant risks, like sudden termination shocks and large-scale salt and acid deposition.[xlv]
As the impacts of climate change become increasingly evident, these externalities could complicate existing questions around legal accountability for climate change. The loss and damage agenda, as well as climate-related litigation, is likely to gain speed, targeting local, state and national governments.[xlvi] However, deployment of these technologies by select actors could challenge these legal avenues, simultaneously giving rise to additional liabilities. For example, economic damage, agricultural losses or health problems from shifting weather patterns, acid rain, changes to air quality, or the spread of communicable diseases is possible under both climate change and an “engineered” climate[xlvii] – and modelled attribution could be challenging if both effects are in play. In some cases, engineered effects may exceed anticipated local impacts from climate change, leading to geopolitical tensions and possibly even cross-border conflict.[xlviii]
Acting today
Addressing the risk of critical changes to Earth systems requires an evolved approach to climate risk management and decision-making. While climate models are effective at illustrating potential hazards, vulnerabilities and exposures for decision-makers,[li] the current limitations of these tools means that we are still entering unchartered territory. Climate and economic modelling could be improved to fully consider the longer-term, non-linear and cascading impacts of Earth system changes through more powerful tools for analysing the Earth as an integrated whole, combining climate and ecological tipping points with broader planetary boundaries.[lii] Part of these efforts will require the translation of scientific findings to inform decision-making, which has proved difficult in a climate context, but may be even more challenging when overlaid with the nature context.
Indeed, around one-half of GRPS respondents highlight the need for enhanced Research and development with respect to both Critical changes to Earth systems, but also Adverse outcomes of frontier technologies, including geoengineering (Figure 2.10). These efforts could be supported through the creation of a global data commons for climate science alongside further investment in relevant equipment (such as remote sensing equipment and computing power) and ecological forecasting.
GRPS respondents feel that Global treaties and agreements have the most potential for driving action. More credible emissions reductions remain the fastest and most effective means to avoid or mitigate the likelihood of climate tipping points. However, with evidence suggesting that some of these tipping points are already locked in, the ratio of adaptation to mitigation efforts will need to be rebalanced through National and local regulation, as complementary objectives. Expanding access to existing adaptation solutions will be essential, including early-warning systems, and decentralized renewable energy (disconnected from the grid) to empower local communities. States and development banks will need to work closely together to de-risk investment for the private sector in priority areas and markets.
2.4 AI in charge
– Market concentration and national security incentives could constrain the scope of guardrails to AI development.
– Adverse outcomes of advanced AI could create a new set of divides between those who are able to access or produce technology resources and intellectual property (IP) and those who cannot.
– Deeper integration of AI in conflict decisions could lead to unintended escalation, while open access to AI applications may asymmetrically empower malicious actors.
Unchecked proliferation of increasingly powerful, genera l-purpose AI technologies will radically reshape economies and societies over the coming decade – for better and for worse. Alongside productivity benefits and breakthroughs in fields as diverse as healthcare, education and climate change, advanced AI carries major societal risks. It will also interact with parallel advancements in other technologies, from quantum computing to synthetic biology, amplifying adverse consequences posed by these frontier developments (Boxes 2.5 and 2.7). Intentional misuse is not required for the implications to be profound. Novel risks will arise from self-improving generative AI models that are handed increasing control over the physical world, triggering large-scale changes to socioeconomic structures.[liii]
Adverse outcomes of AI technologies is another new entrant to the top 10 rankings, deteriorating significantly in perceived risk severity over the longer-term horizon (Figure 2.11). Alongside the possibility of an entity achieving artificial general intelligence (AGI) – learning to accomplish any human or animal task – key concerns cited by GRPS respondents include: misinformation and disinformation (Chapter 1.3: False information); job loss and displacement (Chapter 2.5: End of development?); criminal use and cyberattacks (Chapter 2.6: Crime wave); bias and discrimination; use in critical decision-making by both organizations and states; and AI’s integration into weaponry and warfare.
To date, the precautionary principle (prudence in the face of uncertainty) has largely not been applied in the development of AI, as regulators erred on the side of innovation. However, rapidly evolving development of and reliance on advanced machine intelligence is outpacing our ability to adapt – both to understand the technology itself (the “Black Box Problem”) and to create regulatory safeguards (the “Pacing Problem”), with regulation playing catch up to the technology.[liv] The speed of advances, depth of market power and strategic importance of the industry will continue to challenge the appetite and regulatory capacity of governance institutions. Downstream risks could endanger political systems, economic markets and global security and stability.
Entrenched market concentration
GRPS respondents highlight Cyber insecurity and Technological power concentration as the only risk drivers of Adverse outcomes of AI technologies (Figure 2.12). The production of AI technologies is highly concentrated, in a singular, globally integrated supply chain that favors a few companies and countries (Figure 2.13). [lv] This creates significant supply-chain risks that may unfold over the coming decade. For example, export controls over early stages of the supply chain (including minerals), could raise overall costs and lead to persistent inflationary pressures. Restricted access to more complex inputs (such as semiconductors) could radically alter the trajectory of advanced technological deployment within a country. The extensive deployment of a small set of AI foundation models,[lvi] including in finance and the public sector, or overreliance on a single cloud provider, could give rise to systemic cyber vulnerabilities, paralyzing critical infrastructure.
Given the strategic significance of AI technologies, national security objectives will likely remain the primary objective of innovation and industrial policy in several countries in response to market concentration, shaping upstream market dynamics (Figure 2.14). States will aim for securing their supply chains, onshoring and friend-shoring where possible. For example, China is pursuing a largely independent supply chain, given export controls that block access to the most advanced semiconductor chips.[lvii] Some states may seek to capture lucrative economic gains associated with these technologies, while others will aim to address concentration, potentially at the price of innovation. Building on a history of tackling anti-competitive practices in the tech sector,[lviii] the EU plans to deploy new mechanisms to disrupt the dominance of digital “gatekeepers” and is also reportedly considering an investigation into anti-competitive practices in graphics processing unit (GPU) chips.[lix]
However, despite substantial state intervention – and in some cases, because of offensive economic policy – production will remain heavily concentrated. Barriers to entry remain high, and there are limits to the extent to which state policies can lower them. Sizeable upfront capital expenditure for innovation and infrastructure, economies of scale and scope, a niche talent pool, information asymmetries, and proprietary data pools will continue to favor established companies.[lx] Vertical integration could become more prevalent, as producers of foundation models increasingly expand to downstream uses or partner with platform companies that control online data pools or offer cloud services.[lxi]
Regulatory controls on downstream applications could entrench market power further. For example, the use of a licensing regime could embed the power of existing players, even as it enhances oversight of frontier AI.[lxii] As governments seek to manage the higher risk applications, widespread dependence on the underlying tech stack (the technologies used to develop an application) will likely lend tech leaders a disproportionate influence on legislative discourse, shaping industry norms and standards over the next decade. While downstream applications are far more competitive, upstream commercial motives – rather than public interest – could become the guiding force of AI development and deployment. This trade-off can already be seen in the distinct lack of consistent self-regulation by the industry, with responsible AI teams among the first to be subject to redundancies as the sector downsized in recent years.[lxiii] Tech companies could be left largely in charge of prices as well as privacy, and they may hold excessive sway over preventing competitive innovation.
If monopoly- or oligopoly-led profit maximization is the primary objective of AI deployment over the next decade, the consequences for applications across healthcare, education, military, legal and financial sectors will be vast. In healthcare, for example, as the volume and granularity of health data increases exponentially, the commercialization of related data pools for downstream AI applications could compromise individual privacy and erode trust in healthcare systems. In the absence of strong ethical guardrails, medical data obtained from a fitness tracker, for instance, could individualize advertising, facilitate discriminatory profiling for health insurance, or underpin new, more invasive forms of employee monitoring. Even as data access enables new healthcare solutions and early diagnosis, medical research and development could be geared towards the wealthy – those who have the resources to afford this type of pervasive daily data collection and monitoring that is then used to train AI for various applications. Additionally, the influence of upstream companies could mean that accountability for related risks, from biased algorithms to diagnostic errors, is pushed downstream in some jurisdictions, particularly in countries with more limited market power, in return for access to these technologies.
AI winners and losers
Indeed, extensive integration of AI technologies may create a new set of winners and losers across advanced and developing economies alike. The digital gap between high- and low- income countries is likely to lead to stark disparities in the societal impact – both benefits and risks – of AI technologies. The most vulnerable countries and communities in advanced and developing economies could be left further behind, digitally isolated from turbocharged AI breakthroughs in economic productivity, finance, climate, education and healthcare (Chapter 2.5: End of development?). Dominance of the Global North in tech stack development could perpetuate social, cultural and political biases, while resilience to risks posed by AI, from mis- and disinformation to criminal use, may also be lower in the Global South. Tech talent – and therefore the deep understanding of these technologies – is concentrated in limited markets, with the resulting knowledge gap making effective regulation challenging. Across countries, AI tools could be licensed or repurposed as tools of repression, where relevant norms or regulations are nascent or non-existent (Chapter 1.3: False information).[lxvii] Imbalances in military capabilities could also be entrenched, with related applications raising significant ethical and human rights concerns around accountability.
As such, access to the tech stack will become an even more critical component of soft power for rival states to cement their influence. The self-reinforcing nature of AI development is such that producers of these technologies will only become more firmly established as AI is utilized to achieve the next technological breakthrough (or the “rich-get-richer” effect).[lxviii] However, a widening array of pivotal powers could leverage their own competitive advantages in the highly concentrated value chain to obtain access to these technologies on more favorable terms, leading to novel power dynamics. This could range from suppliers of critical minerals, including Australia, Canada, Indonesia, Morocco, Viet Nam and Chile, to those that could leverage IP, such as Japan and South Korea, or capital, like Norway and Singapore. Further, a handful of states, such as India, may soon have the scale and economic might to disrupt technology development directly, with new innovations capturing market share or key stages of the value-added supply chain.[lxix]
AI escalation
The application of AI technologies to military objectives could threaten global stability over the next decade, with the integration of machine intelligence into conflict decision-making posing a severe risk.[lxxii]
AI will boost cyber warfare capabilities, enabling entire offensive and defensive systems that could act autonomously, with unpredictable impacts to networks and connected infrastructure. When it comes to kinetic warfare, global and regional powers have invested heavily in developing AI-driven weapons systems, and the degree of autonomy afforded to these is increasing: land, air and sea-based weapons can already undertake surveillance without human input.[lxxiii] Attempts have been made to establish international governance around their use; however, agreements have yet to be established.[lxxiv] Abstentions and votes against a draft UN resolution relating to autonomous weapons systems last year were notable, including China, North Korea, Iran, Israel, Türkiye, United Arab Emirates, India and Russia.[lxxv] There remains a material chance, therefore, that these systems could be empowered to autonomously take decisions on lethal actions, including goal creation and the selection of targets.[lxxvi] The potential for miscalculation in these scenarios is high.[lxxvii] For example, AI could misinterpret the “unwritten” norms of geopolitical posturing, such as flying fighter jets close to airspace or military assets of rival powers, as a material threat, initiating conflict.
The most severe risk lies in AI applications to nuclear weapons. While governments have indicated that human control will be maintained over nuclear weapon systems, in principle AI may offer the greatest defense by condensing decision time: making decisions at silicon, not biological speed.[lxxviii] At the same time, AI-enabled launch systems could erode strategic stability, given its theoretical potential to target nuclear assets and second strike capability, combined with the near impossible detection of its development by rival states.[lxxix] If states incorporate AI into nuclear weaponry, this would significantly raise the risk of accidental or intentional escalation over the next decade, with potentially existential consequences.
In contrast to the upstream tech stack, the downstream application of AI is a more competitive market. Despite being among the most powerful of emerging dual-use technologies, the economic and technical barriers to accessing frontier AI are significantly lower than for its technological counterparts, such as geoengineering and quantum computing. Many GRPS respondents highlight concerns around sudden and widespread access to generative AI applications, given that access to the internet effectively equates to access to these models. Malicious actors can leverage a superhuman breadth of knowledge to conceptualize and proliferate dangerous capabilities, from misinformation and malware to biological weapons (Box 2.7), threatening human rights and safety in a myriad of ways.
Acting today
GRPS respondents identify Public awareness and education as one of the most effective mechanisms to address risk preparedness and reduction of Adverse outcomes of AI technologies (Figure 2.15) and as a key tool to manage local impacts as well as build governance capacity and societal resilience. Literacy in generative AI is essential, for regulators and for broader society. AI literacy could be integrated into public education systems and trainings for journalists and decision-makers to not only understand capabilities of AI systems but also to identify trustworthy sources of information.
GRPS respondents also highlight the need for National and local regulations. While national-level efforts will not necessarily prevent the rapid global proliferation of AI and related risks, robust but flexible standard-setting can help ensure that technological development and deployment are aligned with societal needs. The application of existing legislation around intellectual property, employment, competition policy, data protection, privacy, and human rights will need to evolve to address new challenges posed by generative AI.[lxxxii] Other key areas anticipated to be addressed by various regulatory regimes over the short term include the identification of AI-generated products, blocks or limitations to the riskiest uses, and determination of liability for AI-induced harms.[lxxxiii] Solutions proposed include but are not limited to: registration and licensing of the most powerful versions of the technology, tiering access to computing power, implementation of provenance and/or watermarking systems, Know-Your-Customer procedures and mandatory incident disclosures, and creating a robust auditing and certification system.[lxxxiv]
GRPS respondents also note the role of Global treaties and agreements in the management of both Adverse outcomes of AI technologies and Technological power concentration. Several AI governance frameworks have already emerged at a global level to provide high level guidance for AI development, including the latest G7 Hiroshima Process on Generative Artificial Intelligence, as well as the Bletchley Declaration. In addition, there have already been calls for an “AI version” of the IPCC.[lxxxv] This entity could, in collaboration with the private sector, enable global scientific consensus around the risks and opportunities posed by frontier AI. Similarly, it could communicate findings to decision-makers, based on best available projections of global AI hardware and software, albeit with faster assessment cycles by necessity. Oversight could also extend to a reporting database and registry of crucial AI systems. However, the most existential of these risks will require extensive cooperation between powers, to achieve mutual restraint around the proliferation of high-impact technologies, as well as the inadvertent escalation in military AI (Chapter 3: Responding to global risks).
2.5 The end of development?
– Human development and prosperity may stall as barriers to economic mobility arise from climate, technological and geopolitical constraints.
– Deeply bifurcated labour markets could widen inequality between - and create additional risks within - developed and developing economies, as demographic structures and job demand and supply diverge.
– Living standards could recede for populations suffering entrenched unemployment and economic distress, radically reshaping political dynamics.
The world has made rapid strides across most human development indicators over recent decades, but the fragility of these collective gains is evident. In particular, the COVID-19 pandemic challenged global advancement, with visible reversals in 2020 across multiple economies and regions (Figure 2.17), as progress slid with respect to education, healthcare and poverty.[lxxxvi] Economic mobility – or the ability to improve economic status and related outcomes – is perceived to be dwindling in developed and developing economies alike, as job markets change and current education, labour and social policies become outdated against a backdrop of changing demographics.
Lack of economic opportunity is a new entrant to the global risks list. It features in the top 10 risks list over the two-year horizon and is expected to worsen in perceived severity over the longer term (Figure 2.16). Alongside Unemployment as the primary driver, GRPS respondents consider a Lack of economic opportunity to stem from a complex mix of other global risks. This includes short-term economic risks, such as Economic downturn and Inflation, and pressing societal risks such as Erosion of human rights, Intrastate violence and Societal polarization (Figure 2.18).
Without careful management of the large-scale economic transformations that are taking place, economic mobility will stall and reverse. The climate transition, advances in AI, demographic shifts and geopolitical dynamics could interact over the coming decade to cement the mismatch between the demand and supply of labour between and within countries. The consequences for societal cohesion and political outcomes are wide-reaching, threatening standards of living for a large segment of the population in many economies.
Bifurcated markets
Disruptions to labour markets are likely to escalate worldwide as a result of the two large-scale economic transformations that are concurrently taking place, driven by climate action and AI integration. These twin transitions will dramatically reshape the quality, quantity and distribution of job creation as well as job loss, driving divergent risks. Some economies and communities, isolated from job-creation and reskilling opportunities, will encounter saturated labour markets, hindering development. In others, challenges to social and labour mobility could contribute to shortages in critical industries, slowing economic transformations and progress.
Both transitions offer valuable opportunities to tackle economic inequality through the generation of new income opportunities across a range of sectors. For example, AI and Machine Learning Specialists is anticipated to be the fastest-growing job, growing by 40% (1 million jobs) by 2027, while the green transition is estimated to lead to more than 30 million jobs by 2030.[lxxxvii] Mirroring demand for renewable infrastructure, the global construction sector is expected to double in size in the 10-year period from 2020 to 2030, while related jobs, including those in trades and engineering, are among those anticipated to experience the largest growth in the coming years (Figure 2.19).[lxxxviii]
However, related job churn is likely to be significant, as these transitions displace workers in parallel, potentially leading to net job loss overall. The latest estimates anticipate structural job growth of 69 million, set against job losses of 83 million, over the next five years.[lxxxix] This level of job churn will be particularly challenging to manage, as these impacts will not be evenly distributed between or within economies. In many cases, jobs created will not be in the same location, industry or skills bracket as available or displaced workers, thus relying on labour mobility to fill them. A growing labour mismatch between countries is already evident from EOS results: Labour shortages feature in the top five risk rankings for 52 countries over the next two years, while, in comparison, Unemployment features in the top five risks in 30 countries. As shown in Figure 2.20, nearly all countries surveyed include at least one of these risks in their top 10 rankings: low- and lower-middle income countries tend to rank Unemployment higher, while upper-middle and high-income respondents are more concerned about Labour shortages.
Job creation in respective economies over the coming decade will be materially shaped by access to and selected deployment of investment for the climate and tech-related transitions. For example, both are being widely supported by governments, with funding and subsidies targeted at the domestic growth of related industries (Chapter 2.4: AI in charge). However, as capital – and therefore risk – remains costly, investment will likely become even more heavily concentrated in comparatively stable advanced economies. Inflows of public and private capital to accelerate the energy transition have been particularly pronounced in the United States, China and the EU, due to more sophisticated financing mechanisms and policy incentives.[xc]
In contrast, relatively less stable, lower-income, conflict-prone or climate-vulnerable developing economies may be seen as too high-risk for investment or operations. With many already holding sub-investment-grade credit ratings, private interest could dry up further, given heightened political, regulatory, societal and economic instability, as well as the adverse effects of climate change.[xci] Indeed, experts consulted worry that even published estimations of climate-related migration could drive capital elsewhere (Chapter 2.3: A 3◦C world). This would exacerbate existing challenges in terms of public and development financing.[xcii] Many of the Least Developed Countries (LDCs), grappling with debt distress, already face large financing gaps in reaching development goals in the medium term (Figure 2.21) – and geopolitical instability could further hinder international financial efforts to support these economies, from debt restructuring to foreign aid (Box 2.8).
This global gap between job-creating investments and willing workforces will therefore lead to divergent risks in the demand and supply of labour. The demographic dividend of some developing markets may quickly turn into a demographic dilemma in which unemployment becomes a chronic risk. In the absence of substantive domestic or foreign investment, some economies may be unable to generate sufficient green- and tech-related income opportunities to absorb a growing workforce, while other sectors also could become at risk in a low growth, high-rate, low-investment world. This is a challenge that will not be limited to the LDCs – select middle-income economies that have sought growth through an export-led model may also face substantial job erosion.[xciii] Mirroring trends in manufacturing, several countries have relied on rapid growth in digitally delivered services exports (Figure 2.22),[xciv] yet the industries and job functions most impacted by generative AI are among those most commonly outsourced and offshored, such as information technology, finance and human resources.[xcv] Although higher-value income opportunities will be created through AI augmentation, these jobs are likely to be concentrated in technologically advanced regions, building on existing divides in educational and digital literacy that cannot be bridged without investment (Chapter 2.4: AI in charge). The lower cost of labour may still incentivize offshoring to a degree; however, protectionism in digital services could strengthen. For example, stronger data localization requirements would effectively “reshore” these industries.[xcvi] As such, a more fundamental question is rapidly emerging: can manufacturing- and services-led export growth remain an accessible pathway to greater prosperity for developing countries?
In most advanced economies, the creation of “boots-on-the-ground” green infrastructure jobs could exacerbate already tight labour markets.[xcvii] This could be a severe constraint to the green transition for the largest emitters in the medium term and, given geopolitical dynamics and societal discontent, is more likely to incentivize the replacement of lower-skilled, routine jobs (muscle to machine power) than encourage immigration and improved labour mobility. Indeed, grappling with shrinking and ageing workforces, companies in advanced economies will seek to capitalize on the productivity benefits offered by AI, deploying them rapidly and at scale. Generative AI will increasingly be substituted for middle-skilled workers (biological to machine intelligence), particularly in the services sector. The rapid deployment of these technologies could crowd out human competencies within a relatively short period of time – leading to shifts from talent shortages to underemployment and unemployment in some parts of these economies and creating knock-on effects in developing economies.
Stranded people
Individual pathways to economic prosperity could also diverge because of these twin economic transitions, perpetuating technological, educational and societal divides. In the absence of effective policies encouraging reskilling alongside labour and social mobility, access to income opportunities will narrow for a widening segment of the global population, creating pockets of unemployment and economic distress that impact blue- and white-collar workers alike.
This disruption is imminent but may catch the workforce by surprise. For example, four in 10 executives believe AI will lead to net job losses this year – compared to only one in 10 employees.[xcix] EOS results point to a potential skills gap within several countries, suggesting that domestic workers will face barriers to matching job demand within the next two years. Respondents in numerous countries selected both Unemployment and Labour shortages in their top 10 rankings (Figure 2.20). This includes a range of high-, upper-middle, and lower-middle income countries, such as the United Arab Emirates, Saudi Arabia, Qatar, Türkiye, South Africa, Australia, Brazil and Argentina.
The latest estimates suggest that three in five workers will require training before 2027. However, barriers of socioeconomic class and age may hinder economic mobility, entrenching existing inequalities. For example, despite AI-driven advances in education, not all workers – between and within countries – will have access to adequate reskilling opportunities.[c] Those with the economic resources to adapt to new industries will have a better chance at maintaining economic stability and capture higher wages. Those without access to quality retraining will be forced into less stable or secure means of employment. Additionally, the automation of entry level functions could create a higher educational barrier to entry into the workforce, magnifying challenges of social mobility. Over the longer term, the jobs of higher-skilled, more expensive workers may also come under threat from both machine intelligence and machine power, with barriers arising due to skills obsolescence and atrophy, as well as advancements in technology.
If adequate social protection systems are not in place, displaced workers who struggle to re-enter the workforce could face higher rates of poverty, hunger and homelessness, particularly in the near term if costs and inflation remain higher for longer. Access to basic necessities, including healthcare and housing, could become restricted. In the absence of supported pathways to safe and secure livelihoods, more individuals could also be pushed into crime, militarization or radicalization (Chapter 2.6: Crime wave). Forced economic displacement could become more common, with individuals migrating in search of better economic opportunity and, possibly, social assistance – yet even this may be a pathway that some individuals cannot afford.
While many of these consequences may be felt most acutely in developing economies, with less fiscal space to ease the transition for individuals, these risks remain a concern in advanced economies, too. For example, workers from “dirty” sectors could become stranded in fossil fuel-dependent local economies, with few other opportunities available. Displaced older workers will exacerbate the growing strain on social systems and healthcare, creating a different but related livelihood crisis: growing retirement insecurity. Anticipated job disruption could also enable knowledge, technology, income and wealth to become even more concentrated, perpetuating cycles of poverty. An individual born into a less privileged background is likely to face formidable and potentially higher barriers to reaching their full potential, undermining notions of meritocracy and fairness that underpin stable and inclusive societies.
Stalled living standards
As the livelihoods and well-being of individuals come under threat, fiscal space and political appetite will interact to shape the response of governments in both advanced and developing economies. If these economic transformations are not managed carefully, related economic hardship could mean that metrics of human development – from poverty to access to education and healthcare – recede for large swathes of the global population. And if standards of living are not preserved for the current and next generation, societal and political dynamics could radically shift in many economies.
As outlined in last year’s Global Risks Report (Chapter 2.6: Economic stability), competing demands for investment mean that few countries are likely to have the fiscal headroom to invest in human capital for the longer term – in education and healthcare systems, components that are fundamental to the realization of economic opportunities. This will be felt most acutely in the most vulnerable markets, which as previously noted, could face a potential investment crisis with corrosive long-term impacts. As fiscal space is squeezed and private finance remains constrained, these markets will be increasingly forced to choose between, for instance, paying external debt, providing a strong and immediate safety net for struggling individuals, investing in the future growth dividends offered by climate action and technological development, managing and adapting to climate change, or shoring up the longer-term adaptive capacities of human capital through health and education systems.
In this environment, public demands for more interventionist governments may recalibrate fiscal policies, with governments facing increasing pressure to implement policies that prioritize generous safety nets and employment stability. Support for technological (automation or AI) taxes and wealth redistribution could grow.[ci] Generally, however, given debt sustainability concerns, the ability of governments to afford to mitigate the risks of climate- and AI-related job displacement on individuals – through higher unemployment benefits, more generous minimum wages or subsidies for retraining for example – will be driven partially by related productivity enhancements, leading to growth in GDP and tax revenue. As labour markets bifurcate, the ability of governments to support their workforces through these radical transformations, and maintain developmental progress and standards of living, could diverge in turn.
In economies where government efforts are – or are seen to be – inadequate, populist movements will capitalize on the disillusionment of the lower- and middle-classes, who see very little opportunity in their own and their children’s future. Although it may equally encourage innovation and entrepreneurship, an aspiration gap will fuel frustration. Digitally connected people in developing and advanced economies alike will see a better life elsewhere, but limited economic opportunities in their own environment will prevent them from accessing this level of living standards. Even small shifts in access to income and opportunity – perceived or actual – may spark protests and civil unrest and deepen anti-immigration sentiment and hate crimes against migrant populations. In the most extreme scenarios, discontent with the status quo could even push societies towards more open rebellion and calls for regime change.
Acting today
For example, while Unemployment is considered to be addressed primarily by Corporate strategies and National and local regulations (Figure 2.23), a rise in remote work and non-traditional employment arrangements, alongside technology and skills transfers, could help address global inequalities in access to economic opportunities. Current efforts to reshape the global tax regime should also target emerging sources of inequity and support developing markets in capturing a share of the next generation of value chains. The support of multilateral and international finance mechanisms could also reduce real and perceived risks in the most vulnerable countries to unlock financing flows. The expanded use of guarantees could broaden the potential private investor base – or blended finance structures, including with the support of philanthropic investors, could improve the perceived risk-return profile, opening these investment opportunities to institutional investors.[cii]
In the face of these structural shifts to the employment landscape, very few demographic groups, industries or countries can remain complacent. Recognizing that both the impacts of climate and AI on job markets will not be uniform, solutions to improve economic mobility must be tailored to address specific vulnerabilities, such as labour shortages, on an industry- and country-level basis. For example, human capital that is “stranded” by the green transition – i.e., displaced workers from carbon-intensive industries – could help address green labour shortages if geographic, economic or skills barriers can be overcome. A stronger focus on sectors that go beyond narrow definitions of tech and green, such as health, care, education, tourism, hospitality, agriculture, personal services and culture – each of which tends to favour human traits and generate large-scale employment – can also help countries support the structural transitions of their labour markets and workforces. The public and private sector will need to work together to ensure the skills transition from sunset to sunrise roles.
2.6 Crime wave
– State fragility, fueled by climate change, conflict and economic hardship, will create or widen a governance gap in which transnational organized crime can flourish.
– Technological advances will open new markets and allow crime networks to spread, and the human and economic cost of crime may rise in tandem.
– As the ease and attractiveness of these parallel economies grows, the lines between criminals and the state likely will blur.
Organized crime may continue to globalize in terms of both targets and operations, and in doing so, could become a powerful and destabilizing presence in a wider set of countries. The latest data suggests that activity has already started to rise across all criminal markets and actors (Figure 2.25).[ciii] Notwithstanding a drop in homicide rates, organized crime remains a significant contributor to lethal violence: between 2000 and 2019, it resulted in roughly the same number of killings as all armed conflicts across the world combined, at a rate of approximately 65,000 deaths per year.[civ]
Illicit economic activity is an under-the-radar risk – it ranks comparatively low in terms of perceived severity over both the two- and 10-year time horizons, at #28 and #31 respectively (Figure 2.24). While narrower than the definition adopted by the GRPS, this section will focus specifically on organized crime in light of these recent data trends to explore whether emerging geostrategic, environmental, demographic and technological forces could turn the already-chronic risk of organized crime into a pressing crisis over the next decade. Indeed, many of the perceived drivers to Illicit economic activity are among the most severe perceived risks over the short- and longer-term horizon. It is among the top 10 most connected risks in the network, seen to be driven by Economic downturn, Lack of economic opportunity, Cyber insecurity and Involuntary migration, together with Unemployment, Intrastate violence and Geoeconomic confrontation, among others (Figure 2.26).
There are three concurrent trends that will fuel crime syndicates and related illicit markets over the next decade. First, societal fragility, arising from geopolitical, socioeconomic and environmental vulnerabilities, may drive an expansion in illicit markets. In parallel, advances in technology will break down barriers to entry – borders, languages, skill sets – opening alternate revenue streams, particularly in the cyber domain, and allowing transnational criminal networks to spread. Finally, the erosion of legitimate governance may create a vacuum of power for criminal organizations to flourish, contesting fragile regimes for territorial control, or capitalizing on lucrative partnerships with state actors.
Vulnerable markets
Over the coming decade, parallel economies (or black markets)[cv] are likely to proliferate, creating lucrative revenue streams and recruitment pools for organized crime networks, as the costs of crime spread more widely to citizens.
Resource stress, conflict and economic hardship will interact to drive more pervasive demand for smuggling as well as vulnerability to criminal activities.[cvi] Demand for illegal smuggling of drugs, weapons, resources, cash, pharmaceuticals and people will increase in tandem with geopolitical, economic and environmental developments. Expanded sanctions regimes (Chapter 1.4: Rise in conflict), offensive geoeconomic policies, climate-related involuntary migration, and even anticipated price volatility in the licit economy – in food, fuel, health or critical minerals – could all drive an expansion in illegal smuggling in new geographic markets or in new products.[cvii] For example, ongoing market concentration in the tech value chain means that technology-related smuggling, including in semiconductors, is likely to continue to expand (Chapter 2.4: AI in charge).[cviii] Illegal mining of critical resources will be a major source of instability across multiple regions, from South-East Asia to Latin America, driving violence, corruption, the displacement of Indigenous populations and environmental destruction.[cix] As scarcity drives up resource value, environmental crimes such as illegal logging could drive forced labour and human rights abuses, and accelerate broader environmental impacts in turn.[cx] Similarly, the fisheries sector could increasingly attract the interest of organized crime groups. Illegal, unreported and unregulated fishing is a revenue stream that can be engaged in with relative impunity, with jurisdictional challenges hampering enforcement. The practice also complements other forms of marine trafficking, including drugs and people.[cxi]
At the same time, socioeconomic vulnerabilities arising from these same trends will heighten exposure to criminal networks. Conflict- or climate-related migration will likely drive exploitation by criminal actors engaging in, for example, child labour and cyber slavery.[cxii] Additionally, social disintegration, urban segregation, poverty and economic inequalities are all well-known potential drivers of criminal activity and could lead more people towards criminal activity.[cxiii]
Unemployment is seen to be the strongest driver of Illicit economic activity (selected by more than 40% of GRPS respondents). If poverty and unemployment become chronic concerns in countries vulnerable to livelihood crises (Chapter 2.5: End of development?), crime may become the predominant source of income and the only way to access necessities for some communities.
Cyber vulnerabilities
In parallel, rapid integration of advanced technologies are exposing a broader subset of the global population to potential digital and physical exploitation. Organized crime networks will increasingly adopt blended business models utilizing new technologies to diversify illicit funding and fragment the physical presence of organized crime. This will pose significant risks to individuals and legal businesses – and has the potential to lead to violence that challenges the power of governments and threatens the territorial control of states.[cxiv]
New tools and capabilities will open new markets for criminal networks, with cybercrime offering an increasingly low-risk and low-cost revenue stream for organized crime.[cxv] Phishing attacks, for example, can now be easily and accurately translated into minority languages using generative AI. Over the coming years, more sophisticated cyber defenses will shift targets towards less digitally literate individuals or less secure infrastructure and systems. Already prevalent in Latin America, cybercrime will continue to spread to parts of Asia and West and Southern Africa, as affluency grows and internet connectivity brings large swathes of the global population online.[cxvi]
Figure 2.27 outlines a growing concern around the risk of Cybercrime and cyber insecurity among business leaders in developing regions. It ranks among the top 10 risks over the next two years for markets already grappling with higher levels of criminality, such as Cameroon, Mali, Thailand and the United Arab Emirates. The adoption of these digitally blended models, leveraging cyber and physical revenue streams, was seen by some experts consulted to potentially lead to a drop in violence if these activities supersede alternate forms of illicit revenue, such as drug trafficking. Notably, however, the destructive influence of cybercrime puts more civilians at risk than when concentrated between criminal actors in intergang warfare, in addition to being associated with other forms of physical violence, such as human trafficking.[cxvii]
Organized crime groups will also increasingly utilize technologies[cxviii] to enable geographic expansion of their networks to strengthen strategic footholds of economic and political activity. Enabled by technology, crime networks can spread to exploit heightened demand, regulatory and enforcement gaps, and negative public perceptions of police and state legitimacy, with financing, suppliers, customers and violence originating in separate markets.[cxix] EOS results suggest that this may be an underappreciated risk among business perceptions, with more traditional forms of crime – including illicit trade and trafficking – anticipated to remain largely concentrated in Latin America and the Caribbean over the next two years (Figure 2.28). Of note are several economies, such as Nigeria, Kenya, Türkiye and Indonesia, that are already experiencing higher levels of criminality (shaded darker orange), despite Illicit economic activity not ranking as highly in risk perceptions.
Technology-enabled proliferation of illicit activities in new markets and geographies could have numerous implications at a state, company and individual level. Alongside cybersecurity concerns, it could expose businesses to a range of heightened risks, from reputational threats and regulatory scrutiny relating to financial flows and supply chains to impacts on the long-term viability and success of legitimate markets. In more extreme scenarios, geographic expansion of these criminal syndicates could also lead to political violence that challenges the power of governments, mirroring recent developments throughout Latin America and the Caribbean, such as in Haiti.[cxx] A rise in “ungoverned” spaces will also likely be seen in the growth of armed and radicalized groups and disenchanted youths in many cities throughout the developed world, threatening public safety and security.
State-enabled criminality
Growing state fragility will strengthen the ease and attractiveness of these parallel economies for a broader set of actors, either because of reduced state capacity to respond or, in some cases, blurring of the lines between criminals and the state. Indeed, the state itself could support or become susceptible to organized crime over the next decade.[cxxiii]
Fueled by fragility, more widespread corruption could create a vicious cycle whereby states are unable to rebuild the resilience to effectively counter organized crime and could instead be captured by criminal networks. For example, corruption could effectively lead to control of transportation hubs, law enforcement and parts of the public sector by organized crime groups.[cxxiv] This in turn would undermine the rule of law, distort competition and weaken economic growth further, eroding both societal trust and enforcement capacities. Figure 2.29[cxxv] depicts this symbiotic relationship, whereby criminality is generally found hand-in-hand with fragile states that have higher levels of conflict and corruption.
State “sponsorship” of illicit activities may also become more common (Box 2.11). In cyberspace, for example, commodified products (including ransomware) and services-for-hire (such as money laundering) are now easily accessible for less technically competent actors.[cxxvi] This includes procurement by states and state-backed actors to conduct espionage and foreign interference.[cxxvii] The lines between organized crime, private militia and terrorist groups will also blur. Symbiotic partnerships between states and organized crime could grow, such as in acquiring the data of investigative journalists amid a broader crackdown on information flows (Chapter 1.3: False information), in return for concessions and bilateral agreements.
State-sponsored groups may increasingly adopt blended business models, undertaking both licit and illicit activities. For example, the Wagner Group is a private military company that has been designated as a “transnational criminal organization” by the United States. The organization has a network of economic entities, including mining companies, particularly across Africa.[cxxviii] The presence of these groups could further fuel the cycle between conflict, fragility, corruption and crime, particularly where the state does not have the capacity to enforce legal rights. Not only can the presence of these groups drive lethal violence, but they also offer an economic pathway for illicit activities as other pathways stall. For example, climate change has led to a decline in arable land and fish stocks in Lake Chad, prompting some individuals to join armed groups as an alternative source of income.[cxxix]
Acting today
To effectively prevent the spread of illicit activity across both geographic and economic markets, three key areas could be tackled: the capability to launder illicit profits; communications that enable extensive criminal networks; and corruption.[cxxxi] For example, while the counter-risk of surveillance needs to be handled carefully, the dismantling of encrypted communications could be a radical tool to disrupt transnational crime networks. The takedown of EncroChat, for instance, led to 6,558 arrests and close to EUR900 million in criminal funds seized or frozen.[cxxxii] All three pillars can be tackled at multiple layers of governance; however, GRPS respondents feel that National and local regulations have the most potential for driving action on risk reduction and preparedness with respect to Illicit economic activity (Figure 2.30).
With constraints to international cooperation, there may be a shift towards unilateral, bilateral and regional agreements on crime, although these may prove less effective at addressing transnational criminal networks that transcend political alliances and country borders. GRPS respondents recognize the continued need for Global treaties and agreements to boost local efforts. While it was considered comparatively less important in the context of Cyber insecurity, the development of a UN treaty on cybercrime is seen by some to be an encouraging step, notwithstanding that it is accompanied by deep concerns around related government repression of human rights.[cxxxiii] If adopted, it would be the first framework for international cooperation on a cyber issue, addressing the prevention, investigation and prosecution of cybercrime.[cxxxiv] Alongside these efforts, a focus on socioeconomic drivers will also be essential to reduce entry pathways into, and demand for, criminal activities.
2.7 Preparing for the decade ahead
When asked about the global political outlook for cooperation on risks over the next decade, two-thirds of respondents (66%) believe that we will face a multipolar or fragmented order, in which middle and great powers contest, set and enforce regional rules and norms (Figure 2.31). Cooperation on urgent global issues, from an interrelated environmental crisis to high-speed technological advances, could be in increasingly short supply, requiring new approaches to addressing global risks. The next chapter (Chapter 3: Responding to global risks) explores different types of global risks and how to address them ahead of the next decade in a new multipolar context.
