Artificial intelligence (AI) can support the climate transition by reducing global emissions by up to 5.4 GtCO₂e annually by 2035 in the power, food, and transport sectors, surpassing its own energy footprint. Strategic government action is essential to ensure AI accelerates low-carbon solutions equitably and effectively.

The report discusses the use of unstructured data and AI, particularly large language models (LLMs), in investment processes. It discusses the benefits of fine-tuning these models to improve investment strategies and includes a case study on using AI in ESG investing.

This toolkit aims to provide investors with guidance on how to navigate the intersecting terrain of AI and human rights. It covers the various aspects of AI implementation that have potentially significant implications for human rights, and how investors can engage with companies on these issues. Its focus is on emerging risks and opportunities for investors in the context of rapidly evolving technologies and the ethical challenges they pose.

This report provides actionable insights for investors exploring the integration of Responsible AI (RAI) in their investment decisions. It offers a framework to assess the environmental, social, and governance (ESG) implications of Artificial Intelligence (AI) usage by companies. The report includes case studies of globally listed companies and a set of templates to support investors in implementing the framework.

This framework is a guide to promote safe, secure and transparent use of AI systems. The Framework provides four key functions – govern, map, measure and manage - with further categories and subcategories for risk management in AI systems.

AI offers great positive impacts and risks. This report helps to understand the risks associated with developing and using AI tech. Scoping exercise identifies opportunities and threats across sectors. Six core ESG considerations including trust and security, data privacy, and sentience are evaluated for potential impact.

This report examines the use of artificial intelligence technologies to analyse environmental, social and governance ("ESG") data for investments in emerging markets. It gives a detailed account of an experiment conducted to determine the effectiveness of such technologies in analysing the ESG performance of emerging markets issuers.