UK finance sector urges different rules for agentic AI

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UK finance sector & agentic AI rules

Highlights

The Mills Review urges reconsideration of the UK Financial Conduct Authority's activity-based regulatory framework due to the general-purpose nature of agentic AI in financial services.
Restricting AI tools from regulated financial activities could hinder UK consumer access to advice on investments, credit, insurance, and state benefits, limiting AI's potential benefits.
Industry leaders advocate adapting regulations and creating UK-focused data sources to maintain consumer trust and competitiveness while leveraging AI's benefits in global financial markets.

Debate grows over adapting FCA oversight

As reported by Financial Times, the debate has sharpened after the “Mills Review” examined how the UK Financial Conduct Authority should respond to artificial intelligence in retail financial services. The review highlights both the need to build the foundations of agentic finance and the question of whether today’s activity-based regulatory framework should be adapted to AI tools.

The argument against simply applying the existing rule book to AI assistants is that these systems are general-purpose technologies, not tools limited to one regulated function. They are used for everything from information searches and recommendations to legal and health-related queries, raising the question of whether financial services alone should define how such systems are governed.

The view advanced in the discussion is that forcing AI tools to pull back from regulated financial areas could reduce consumer access to useful help on investments, savings, credit, insurance, tax and state benefits. That, in turn, could limit one of AI’s main benefits, broader access to expertise and information that has often been difficult for ordinary consumers to obtain.

Consumer access and UK competitiveness at stake

The case for a more flexible approach rests partly on the speed of adoption and the global nature of the technology. If UK consumers receive a more restricted version of AI than users in other well-regulated markets, they risk being left with less capable tools while demand for automated assistance continues to expand.

Rather than abandoning regulation, the proposed direction is to review whether the current framework remains effective and to consider more fundamental changes over time. Possible measures include agreeing guiding principles with providers, helping consumers understand when AI-generated financial information is regulated and building trusted UK-focused data sources so answers reflect domestic markets and consumer circumstances rather than conditions in the U.S.

The broader industry implication is that regulation could remain a trust marker even if AI tools sit outside the traditional perimeter. In that model, the UK’s reputation for high-quality oversight could become a competitive advantage while firms, consumers and regulators work to limit harm without cutting off the potential benefits of agentic AI.

In our earlier coverage of the U.S. push to formalize AI oversight, we noted plans to appoint an “AI tsar” and set up an “AI Force” as political pressure builds around model safety and the cost of powering data centers. The article also outlined how lawmakers are responding to voter concerns by shifting potential electricity-cost increases from consumers to data center operators, even as leaders signal they do not want to curb the sector’s growth.

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