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.

Global Nature Watch is an AI-powered Earth monitoring platform developed by the World Resources Institute and Google. It provides near-real-time data on land-use changes across various ecosystems to support nature-based risk assessment and environmental reporting.

This report evaluates climate change mitigation and adaptation strategies for data centres using the ClimaTech database. It assesses the effectiveness of decarbonisation across three scopes and analyses resilience measures for flood, storm, heat, and wildfire risks, providing quantitative performance metrics for various technological solutions.

This report examines the intersection of artificial intelligence and sustainability transitions, detailing opportunities and risks across environment, energy, labour, finance, and democracy. It proposes a three-layered governance framework and a phased roadmap for global scientific alignment, interim safety measures, and a binding international framework convention to ensure societal well-being.

This research investigates the demand for explainable AI in high-stakes credit settings. It finds that decision-makers strategically avoid explanations that reveal racial or gender bias to preserve moral wiggle room. Additionally, behavioural biases cause individuals to undervalue explanations even when they complement private information and improve decision accuracy.

This report examines the hidden human costs of content moderation and data labelling in Colombia, Kenya, and the Philippines. It details systemic physical, psychological, and economic harms caused by lead firm power, informal employment, and intense target pressure, while identifying significant barriers to corporate accountability and worker rights.

This paper examines AI data centre electricity demand and its costs for ratepayers and the environment. It finds that Big Tech market capitalisations have risen far above predicted levels since ChatGPT's 2022 launch, while data centres drive up electricity prices and fossil fuel use. Regulatory reforms and innovations are recommended.

This Chatham House paper examines four trends — rising defence and dual-use investment, the growth of 'patriotic tech', the push for sovereign AI, and concerns over an AI valuation bubble — that could multipolarise the global AI race, and offers recommendations for private sector preparedness.