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 IPPR paper examines how social media platforms have shifted from user-led spaces to algorithm-driven, influencer-dominated environments through 'sticky gatekeeping'. A UK survey found only 18 per cent of feed posts were personal content. The report recommends regulatory reform, algorithmic transparency, and development of a public social media platform.

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.

This NBER working paper quantifies the environmental costs of US data centre electricity use in 2025. Using facility-level data for approximately 2,800 data centres, it estimates gross external damages of $24.6 billion from air pollution and greenhouse gas emissions, with Texas and Virginia accounting for 30% of the national total.

This BHRC report examines how top US companies are responding to mounting pressure on human rights standards. It identifies three corporate pathways: active deregulatory lobbying by Big Oil and Big Tech, quiet retreat from human rights commitments, and continued adherence. Survey data from April 2026 reveals significant reductions in human rights staffing and budgets.

The 2025 RDR Index Big Tech Edition ranks 14 major technology companies on governance, freedom of expression, and privacy. Microsoft leads overall with 50%, followed by Alphabet at 49% and Meta at 47%. Scores are also assessed across eight thematic lenses, including algorithmic transparency, security, and targeted advertising.

Ranking Digital Rights' 2026 Telco Giants Edition scores 12 major telecom companies on governance, freedom of expression, and privacy. Telefónica leads overall with 57%, while Ooredoo ranks lowest at 14%. Historical data from 2017 to 2026 shows varied progress, with scores dipping in 2020 due to new indicators.