The FCA Sets Out Its Plan for AI Agents That Give Advice and Then Act on It

On 19 October 2026 Jessica Rusu, the FCA's Chief Data, Information and Intelligence Officer, gave a speech at the Bloomberg UK Policy Series. She described AI as moving "from technology that helps us understand and decide, to technology that can increasingly act on our behalf". Agents, she said, can search across products, manage payments and investments, and transact directly with other agents.

The main points for agentic advice:

1. Consumers are already taking advice from AI. Four in five less-experienced investors aged 18 to 40 have used AI to help with investing. Only 40% of consumers know they have no recourse if advice from a general-purpose AI tool goes wrong.
2. A clearer boundary, and disclaimers. Consumers are turning to general-purpose models for financial information and advice, and regulated firms are plugging their services into AI platforms. The FCA says this can blur the boundary between regulated and unregulated activity, and that the answer is "not simply to expand our remit, but to make the existing boundary clearer". It is calling on AI providers to help consumers understand the limits of AI-generated financial information through clear, proportionate and consistent disclaimers, ideally at the point where the information is given.
3. A trusted framework for agentic finance. Greater autonomy changes the risk: a poorly governed agent could cause harm at much greater speed and scale. The FCA will work with industry, other regulators and frontier AI labs to develop a trusted framework for agentic finance, seeking clear approaches to agent identity, delegated authority, accountability and execution. No timeline or legal form is given.
4. AI failures and near-misses. The FCA's rules already require firms to report major incidents, and the speech says this must extend to significant AI failures and near-misses. Agentic systems also need continuous, conditional assurance, because a system that was safe at deployment can behave differently later.
5. Good and poor practice, published the same day. The FCA's accompanying publication on AI in financial services gives examples from firms. They include a central inventory of AI agents with a named owner for each, set points where the AI hands over to a person or stops, and a firm that had to redesign its product when the provider retired its model.

The speech also covers the FCA's own use of AI. This includes AI tools to oversee around 60,000 anti-money laundering firms joining its remit in 2028, an agent acting as a market first responder for transaction reporting and the machine-readable Handbook API.

Read the FCA speech · AI in financial services: good practice and areas for improvement