AI is reshaping financial services by enhancing efficiency, reducing costs and unlocking new revenue opportunities. With $97 billion in projected investment by 2027, firms must address risks like misinformation and data bias while prioritising governance, regulation and workforce reskilling to ensure responsible, secure and effective AI adoption.

The report outlines AI’s growing use in finance—especially in underwriting, fraud detection, and customer support—highlighting regulatory challenges around explainability, governance, and data security. It discusses evolving global guidance and the need for risk-based, proportionate oversight, particularly as generative AI gains traction in high-impact applications.

This report examines the synergies between artificial intelligence, data governance, and privacy, highlighting international collaboration opportunities. It identifies key regulatory frameworks, interoperability standards, and policy recommendations to address shared global challenges and promote responsible AI deployment while safeguarding data privacy across jurisdictions.

This report systematically reviews ethical challenges in the digital business world, focusing on the intersection of digitalisation, corporate responsibility, and technology adoption. It highlights ethical dilemmas, such as AI transparency and sustainability, emphasising the need for tailored ethical guidelines to foster trust, innovation, and social responsibility in digital transformations.

The report explores the potential of blockchain technology in financing infrastructure projects. It evaluates blockchain's capabilities in enhancing efficiency, transparency, and accessibility in infrastructure tokenisation, while addressing challenges like regulatory constraints, market adoption, and technical barriers. The findings highlight both opportunities and limitations for integrating blockchain into infrastructure financing.

The report discusses the rapid adoption and integration of artificial intelligence (AI) in the financial sector, driven by advancements in technology and increasing operational efficiency. Key risks include dependencies on third-party providers, market correlations, and cyber vulnerabilities. Generative AI's accessibility could amplify systemic risks, necessitating enhanced regulatory frameworks, vigilant monitoring, and robust governance to ensure financial stability amid evolving AI technologies.

Generative AI enables the rapid creation of synthetic content, offering both opportunities and risks. This report examines challenges like disinformation and fraud, outlines technical and regulatory strategies, and explores trade-offs with privacy. Techniques discussed include watermarking, provenance tracking, and legal frameworks, aiming to enhance transparency while safeguarding privacy.

The report outlines a vision of interconnected financial ecosystems powered by digital innovation. By leveraging technologies like tokenisation and unified ledgers, it aims to create a user-centric, inclusive financial system that lowers costs, improves access, and increases efficiency globally.

The report explores the transformative role of AI in the financial sector, focusing on financial intermediation, insurance, asset management, and payments. It highlights both opportunities and challenges, including implications for financial stability and the need for upgraded financial regulation to manage the risks associated with AI's growing influence.

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 paper explores practical research issues associated with accidents in machine learning and artificial intelligence (AI) systems, due to incorrect objectives, scalability, or choice of behaviour. The authors present five research problems in the field, suggesting ways to mitigate risks in modern machine learning systems.

This report advocates for creating a high-level, G20 framework using a set of principles for the introduction and management of big data and AI in the workplace. The paper identifies main issues and suggests two paths towards adoption.

This report provides 10 principles for ethical artificial intelligence. From transparency in decision-making to ensuring a just transition and support for fundamental freedoms and rights, the report aims to empower workers and maintain a healthy balance of power in the workplace.

The adoption of AI has more than doubled, with a peak of 58% in past years. The report highlights the importance of best practices and investing in AI as it is shown to bring financial returns. However, the majority of organisations are not mitigating risks associated with AI despite increasing use.

The Japanese Society for Artificial Intelligence has released ethical guidelines that aims to protect basic human rights and promote the peace, welfare, and public interest of humanity. The eight guidelines include: contributing to humanity, abiding by laws and regulations, respecting others' privacy, being fair, maintaining security, acting with integrity, being accountable and socially responsible, and communicating with society and self-development.

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.