This report assesses the capacity of artificial intelligence and robots to automate ageing workforces across 135 economies. While automation could offset demographic pressures, its effectiveness is limited because ageing often occurs in sectors with low automation potential, such as health and agriculture, particularly in several fast-ageing advanced economies.

This research analyses AI provider liability for dual-use models enabling both cyberattacks and defence. It demonstrates that while liability can improve welfare by reducing contest resources through higher prices, it may increase harm by weakening precautions. Market competition and guardrail incentives significantly influence optimal liability shares.

This report explores emerging themes in digital-era public financial management (PFM) for 2026. It examines the integration of artificial intelligence, digital public infrastructure, and earth observation to improve fiscal oversight, tax administration, and public welfare, while highlighting risks from declining international aid and proprietary software lock-in.

This research examines the environmental and social impacts of rapid data centre expansion in the United States. It highlights how generative AI infrastructure disproportionately burdens marginalised communities through pollution, increased utility costs, and resource depletion. The authors call for a "more human pace" centred on environmental justice.

Research using a global energy-economy model indicates that AI-driven productivity gains increase net annual CO2 emissions by 0.47–1.8 gigatonnes under parallel adoption. Enabled emissions from fossil sectors consistently exceed avoided emissions from renewables. Achieving net reductions requires renewable productivity gains to be four to five times greater than fossil gains.

This report distils lessons from 25 organisations on leveraging technology to strengthen human rights due diligence in value chains. It categorises various tools, provides case studies, and outlines practical steps for responsible AI adoption, emphasising that technology must complement, rather than replace, human judgement and meaningful stakeholder engagement.

This report assesses digital traceability systems for critical raw materials, evaluating their architecture, feasibility, and impact. It emphasises aligning downstream regulatory demands with upstream producer realities, recommending that traceability should support due diligence and inclusion—particularly for artisanal mining—rather than serving as a standalone compliance burden.

This report analyses sustainable investment trends for 2026, examining physical climate risk, the energy transition, and Asia’s leadership. It addresses the influence of artificial intelligence on power demand and emission targets, alongside structural challenges in the health care and food production sectors, highlighting resilience and adaptation as key priorities.

This report examines the dramatic tenfold increase in solar geoengineering funding between 2020 and 2025. It highlights the dominance of US and UK tech billionaires and government agencies in financing research, raising concerns about transparency, democratic oversight, and the marginalisation of Global South interests in climate policy.

This report analyses supply chain resilience and industrial policy through the lens of economic security. It evaluates market failures in supply chain investment, examines cases of Chinese economic coercion, and assesses Japanese semiconductor subsidies for TSMC and Rapidus, emphasizing the roles of diversification, existing industrial clusters, and international research collaboration.

This research analyses Japan's position in the East Asian electronics supply chain using network science. While Japan remains a vital upstream supplier of components and equipment, its dominance in mainstream semiconductors has declined. Conversely, Japanese firms maintain strong leadership within automotive clusters and unique electronics-automation-utilities ecosystems.

This research examines how automating technology affects white-collar career dynamics and human capital. It identifies a potential 'human-capital trap' where automation reduces entry-level learning. The paper recommends targeted taxes on automation and subsidies for task-frontier expansion to maintain long-term welfare and professional skill development.

This report examines how artificial intelligence is transforming capital markets by shifting the industry from informational scarcity to analytical abundance. It introduces a structural framework involving capability, adoption, substitution, and recomposition, exploring alternative future states and the evolving nature of fiduciary accountability, market stability, and professional expertise.

This research provides international data on firm-level artificial intelligence adoption across the US, UK, Germany, and Australia. While current impacts on employment and productivity are small, senior executives predict a 1.4 per cent productivity boost and a 0.7 per cent reduction in employment over the next three years.

This research investigates AI-managed household portfolios, finding that large language models recommend undiversified portfolios concentrated in high-momentum, large-cap technology stocks. While returns may exceed market benchmarks, they do not provide abnormal returns when adjusted for risk characteristics. Recommendations are primarily driven by media attention rather than investment skill.

Research demonstrates that Large Language Models exhibit purpose-conditioned bias when informed of downstream tasks. Goal-aware prompting leads to in-sample overfitting and inflated performance before knowledge cutoffs. Results indicate that disclosing objectives compromises neutrality, necessitating the separation of measurement and evaluation in AI-assisted workflows to ensure statistical validity.