Navigating the challenges of AI regulation
Navigating the challenges of AI regulation
How regulators worldwide are responding to AI, and what businesses developing, deploying and using it must prepare for
About this report
Artificial intelligence is moving faster than the rules designed to govern it. Regulators are trying to close the gap between rapid technological change and effective oversight. They face a lack of consensus on how to define AI, the opacity of “black box” systems, and the difficulty of policing technology that routinely crosses borders. The result is a fragmented global landscape. The EU has a prescriptive AI Act, the UK relies on a principles-based, regulator-led model, the US has a patchwork of state laws, and several countries are moving away from planned mandatory frameworks.
This whitepaper from LexisNexis Regulatory Compliance maps the current state of AI regulation in the UK and globally, covering the EU, US, China, Australia and New Zealand. It examines the regimes already shaping AI governance today, from the Online Safety Act and the Data (Use and Access) Act to FCA, PRA, ICO and MHRA expectations. It also looks ahead to proposed legislation such as the Frontier AI Bill and explores the frameworks emerging for responsible AI. It closes with practical guidance on what the evolving regulatory environment means for businesses and how compliance teams can stay ahead of it.
What you’ll learn
- How the UK’s five AI principles are being applied through existing regulators, and what the FCA, PRA and Bank of England expect from financial services firms using AI
- Which current UK regimes already affect AI systems, including the Online Safety Act 2023 and the Data (Use and Access) Act 2025, and what planned legislation such as the Frontier AI Bill and the AI Growth Lab could mean for firms
- How the EU AI Act’s risk-based approach compares with the fragmented US landscape, China’s generative AI rules and Australia’s shift toward a more flexible framework
- The key challenges facing regulators, including defining AI, the black box problem, bias and discrimination, and jurisdictional complexity
- The practical steps businesses can take to build responsible AI practices, strengthen accountability and keep pace with regulatory change across jurisdictions