Agentic AI does not automatically count as regulated financial advice in the UK. The FCA regulates activities rather than technologies. Whether an AI interaction crosses the regulatory perimeter depends on what the system does, how personalised its output is, whether it recommends a specific course of action and whether it goes on to arrange or execute it.
The issue is getting harder to separate in practice. AI agents can already compare products, use detailed information about an individual, make personalised recommendations and act on a consumer’s behalf.
The FCA’s July 2026 Mills Review calls this emerging category “advice-like support”: highly personalised financial support from AI models that sits outside the current regulatory perimeter but may look very similar to regulated advice. It recommends that the FCA examine how the advice and guidance boundary, arranging rules and financial promotion rules work in continuous AI-enabled journeys.
The debate now has two legitimate sides. More regulatory clarity could protect consumers and create a level playing field between regulated firms and general-purpose AI providers. Draw the boundary too widely or too early, however, and firms may struggle to use AI to provide cheaper and more accessible financial support.
Does agentic AI count as regulated financial advice?
The short answer is sometimes, depending on what the agent is doing.
The FCA’s regulatory framework is activity-based. Using AI does not create a separate category of financial advice, and using an AI interface does not remove an activity from regulation.
For investment advice, FCA guidance says a personal recommendation can include a recommendation about a particular investment that is presented as suitable for an individual or is based on that person’s circumstances. Those circumstances can include income, objectives, needs and risk appetite. The medium used to deliver the advice does not determine whether it falls within the definition. That creates a fairly clear position at the extremes.
Firms may need to determine which regulated activities are taking place across an entire agent-led journey
An AI tool that explains an ISA is providing information. An AI system operated by an authorised firm that considers a customer’s circumstances and recommends a particular investment as suitable may be carrying out an activity already covered by financial services regulation. The difficult area sits between those two examples. That is where agentic AI is developing fastest.
Why agentic AI makes the advice boundary harder to apply
Most digital financial journeys used to contain reasonably identifiable stages. A consumer searched for information. They compared products. They spoke to an adviser or made their own choice. They then completed a transaction. An AI agent can combine those stages in a single conversation.
A consumer could tell an agent: “I want to get a better return on my savings, but I need access to the money next year.”
The agent might then:
- Analyse the consumer’s finances
- Identify the relevant products
- Compare their features
- Decide which ones appear the most suitable
- Recommend one
- Initiate or complete the transaction
- Continue monitoring the consumer’s position afterwards
The FCA describes this development as a move towards financial services that are more continuous and delegated, with AI systems progressing from providing recommendations to taking actions within agreed parameters. Its consumer research found that one in five UK adults is already open to AI making decisions within goals they have set.
The regulatory question therefore becomes more complicated than deciding whether one chatbot response constituted advice. Firms may need to determine which regulated activities are taking place across an entire agent-led journey.
The FCA now has a term for the grey area: “advice-like support”
One of the most important concepts in the Mills Review is advice-like support.
The Review defines it as highly personalised support from frontier AI models that currently falls outside the FCA’s perimeter, but which would be treated as regulated financial advice if it fell within that perimeter.
This matters because general-purpose AI can increasingly use an individual’s own information to generate highly specific financial recommendations.
The Mills Review highlights three problems.
1. Personalisation can blur the line between guidance and advice
The FCA’s current framework already distinguishes between different levels of financial support. Under the Advice Guidance Boundary Review, for example, targeted support allows authorised firms to make suggestions to groups of consumers with common characteristics. Simplified advice can go further where a consumer needs a recommendation based on their individual circumstances.
AI changes what can happen between those categories. A general-purpose model may know considerably more about one person than a traditional guidance service does. It can combine their income, holdings, goals, transaction history and preferences and produce a highly individualised answer. The Mills Review specifically warns that these hyper-personalised recommendations may deliver advice-like support outside the regulatory perimeter.
2. Similar financial influence can carry different regulatory obligations
This creates a potential level-playing-field problem. A regulated wealth manager may face strict requirements when making personalised recommendations. A general-purpose AI platform may influence the same consumer’s financial decision without carrying equivalent obligations if the activity falls outside the perimeter.
The Mills Review calls out the risk of regulatory arbitrage, where unregulated AI platforms exert comparable influence to regulated firms without equivalent consumer protections. HM Treasury’s July 2026 Financial Services AI Adoption Plan reaches a similar conclusion. It recommends a review of financial guidance and advice-like outputs from general-purpose LLMs, including their impact on consumer outcomes, competition and the level playing field between regulated and unregulated providers.
3. Agents can move from recommending to acting
A recommendation is only one part of the issue. An agent might also submit an application, move money, arrange a transaction or route a customer towards a particular provider. The regulatory perimeter then extends into other areas. The Mills Review therefore recommends examining:
- Advice and guidance in conversational AI interfaces
- The “by way of business” test for general-purpose AI
- Financial promotions
- Arranging rules
- Continuous AI-enabled consumer journeys
This is why the debate around agentic finance is wider than whether a chatbot has technically given advice. The relevant question is increasingly, and still to be determined: what financial activity has the agent performed on the consumer’s behalf?
More to come on this in our next article.
