Why the Academy believes the next 6–12 months should be a period of serious business-model review for financial advisers.
By Steve Conley | Academy of Life Planning | 24 October 2026
There is a reassuring response to research showing younger investors using AI.
“Our clients are older.”
It sounds like a reason to carry on. Increasingly, it looks like an assumption that needs testing.
AI is already being used by people in their fifties, sixties and seventies. It is being used by wealthy people. And it is being used by people who already pay for financial advice.
Some are preparing questions. Some are exploring alternatives. Some are checking what their adviser has told them.
The client may still attend the annual review, appreciate the relationship and pay the fee. But the way they reach a decision may already have changed.
At the Academy of Life Planning, our view is that the next 6–12 months will prompt many advisers to rethink their model. We believe firms should begin that process now, using their next annual review cycle to understand and respond to changing client capability.
That is our strategic judgement, rather than a deadline established by a survey. Here is the evidence behind it.
It is already happening beyond the under-40s
The FCA’s August 2026 research found that four in five less experienced investors aged 18–40 had used AI for help with investing. Around two-thirds expected to use it more over the following year.
That matters. But it does not describe every age group, and it should not be presented as though it does.
For older consumers, look at Lloyds Banking Group’s August 2026 analysis:
- 47% of 55–64-year-olds had used AI for personal finance.
- 35% of 65–74-year-olds had done so.
This is broad personal-finance use. It does not mean those people have built comprehensive financial plans or delegated investment decisions to a chatbot.
It does mean that age alone is a weak reason to assume clients will leave AI outside the planning relationship.
“My clients are older” tells us their age. It does not tell us how they now think, research or decide.
Wealth does not insulate the adviser either
Boring Money’s September 2026 research brings the discussion directly into the advised market.
Among advised clients:
- 34% with £500,000–£1 million in investable assets had used AI for financial support.
- 44% with more than £1 million had done so.
These are people with an adviser already.
The same release reports that 9% of advised clients use AI regularly to inform financial decisions. That is a different measure from having tried it, and the distinction matters.
We should neither inflate experimentation into permanent behavioural change nor dismiss experimentation as irrelevant. Trying a new way of understanding money is how people discover what they can increasingly do themselves.
The older-consumer and wealthy-client studies examine different populations. Together, they challenge two comfortable assumptions: that AI is mainly for the young, and that paying for advice removes the reason to use it.
Your advice is becoming part of a wider conversation
Wealthtime commissioned the lang cat to survey 175 UK advice professionals. Its August 2026 findings reported that:
- 63% had clients using AI in relation to financial advice.
- 59% said clients used AI to prepare questions before meetings.
- 50% reported clients using AI to check or validate advice.
- 44% said clients used AI to research advice firms.
- 35% reported clients generating their own financial or investment recommendations.
Those percentages refer to advisers reporting client behaviours. They are not estimates of the proportion of all UK consumers doing each activity.
The finding is still powerful: half of surveyed advisers reported clients using AI to check or validate advice.
The adviser’s explanation can now be the beginning of another conversation. A client can ask an AI system:
“What assumptions underpin this recommendation?”
“What alternatives should I understand?”
“What would change if I retired later, spent less or helped my children now?”
The quality of the answers will vary. AI can make errors, miss context and reinforce a misleading premise. So can humans.
In my experience, AI checking human work picks up more mistakes than humans checking AI work.
Human advice deserves scrutiny too. Clients now have another way to ask questions, compare explanations and challenge assumptions—and that changes the relationship.
Using superintelligence to become superintelligent
If you like, clients are using superintelligence to become superintelligent.
I use that phrase to describe an ambition for human capability, rather than a technical claim that today’s systems have achieved superintelligence.
The opportunity is to extend a person’s ability to understand, question and act.
Access to an answer does not automatically create understanding. Understanding does not automatically produce good judgement. A confident mistake remains a mistake.
That is precisely why professional support can remain valuable.
But its value increasingly needs to be explained in terms of what it helps the person become capable of doing.
Can you help someone recognise a weak assumption? Reconcile competing goals? Understand consequences? Make a decision they can explain and own?
These are substantial contributions to a person’s life.
Agentic AI could accelerate the shift
AI services are moving beyond answering individual questions towards carrying out sequences of work.
OpenAI’s ChatGPT agent combines research with actions such as working on spreadsheets. Claude’s Research feature conducts multiple searches, following up findings and exploring different angles.
These capabilities matter because practical independence involves work as well as information: gathering evidence, comparing options, organising records and testing scenarios.
Our expectation is that increasingly capable agents will make more of that work accessible to individuals.
The surveys cited here do not establish how quickly agentic AI is increasing financial use. That remains a hypothesis to test. But waiting for a perfect adoption curve would leave firms learning about changing demand after clients have already experienced it.
Building a more efficient practice with AI is only part of the response. Advisers also need a proposition for clients who use AI themselves.
Use the next annual review cycle
Why start within 6–12 months?
Because a firm can use that period to listen, experiment and adapt while relationships are strong.
Wealthtime reported that only 2% of surveyed advisers had lost a client because of AI. That gives little support to claims of an immediate exodus. It does offer an opportunity to respond before dissatisfaction or departures become the main source of feedback.
| Timing | Concrete change |
|---|---|
| Next 3 months | Ask clients whether they use AI, for which financial tasks, and what they find useful or confusing. Record results by age and wealth. |
| Within 6 months | Pilot meetings that welcome clients’ AI research and help them examine evidence, assumptions and alternatives. |
| Within 12 months | Review the service proposition, pricing and between-meeting support using what clients actually value and can increasingly do themselves. |
Ask openly. A client should feel comfortable saying they checked your explanation.
Measure more than whether clients used a tool. Ask what they learnt, what they could do independently and where human support made a difference.
A client who needs less help with one task may value more help with a difficult decision. The service needs room to evolve with them.
Design for the more capable client
At the Academy, we are developing an approach around continuous personal capability and episodic professional support.
The Academy provides learning and community. Academy OS provides the AI operating system. The Total Wealth Planner provides human support when the person needs it.
The aim is to help people operate their own lives with greater understanding, confidence and control.
Through our Practice Management Circle “Trailblazers” sessions, professionals can explore how to build propositions around that changing relationship: what to offer, how to demonstrate value in the age of AI and how to serve people whose capabilities continue to grow.
If you are an Academy member, join the Practice Management Circle to work through that transition with us.
The next annual review should review more than the client’s plan. It should review your assumptions about the client.
They may already be more capable than your business model allows for.
Remember, customers use AI too!
Sources and research notes
- FCA: Young investors trust AI more than TV or celebrities, 27 August 2026. Research concerns less experienced investors aged 18–40 who own or are considering investments.
- Lloyds Banking Group: Britain’s most AI-savvy generation has a financial confidence gap, 25 August 2026.
- Boring Money: Over 2 in 5 advised clients with over £1 million have used AI for financial support, 17 September 2026. Report draws on three surveys, including 1,107 advice clients with £100,000+ assets. Wealth-subgroup sample sizes are not disclosed in the public release.
- Wealthtime: Research reveals over a quarter of financial advice clients are using AI tools, 27 August 2026. Survey of 175 UK advice professionals; findings reflect adviser reports and estimates.
- OpenAI: ChatGPT agent release notes.
- Anthropic: Use research on Claude.
These studies use different populations and definitions. They establish existing use and changing expectations; they do not provide a single comparable national growth rate or prove that most firms will change their models within a year.
Background Notes
Millions of UK consumers already use AI for financial help, but there is no single reliable national figure—and the evidence does not establish a consistent growth rate. Recent surveys range from 13% for supporting financial decisions to around 51–56% for broader financial questions and money management. Those measures should not be treated as interchangeable.
What the UK research shows, as at 24 October 2026
| Research | Reported usage | What it measures |
|---|---|---|
| OneFamily, June 2026 — survey of 2,000 UK adults | 13%, equivalent to 7.1 million adults | Having used an AI chatbot to support a financial decision. Among users, 39% used it for budgeting or tracking spending and 34% for choosing investments. |
| Capital One, September 2026 — survey of 2,000 UK adults | 13% | Asking AI for personal finance information or advice in the previous year. |
| Finder, June 2026 fieldwork — nationally representative survey of 2,000 adults | Around 31%, estimated at 16.9 million adults | Having used generative AI for personal finance advice. |
| Aqua, September 2026 fieldwork — nationally representative survey of 2,000 adults | 50.8% ever; 35.2% weekly; 10.6% daily | Self-reported use of AI for “financial advice”. |
| STRAT7, April 2026 study | 55% | Using AI platforms for financial questions, at least sometimes. |
| Lloyds Consumer Digital Index, November 2025 | 56%, estimated at 28.8 million adults | Using AI to help manage money in the previous 12 months, including budgeting, saving and financial education. |
Sources: OneFamily; Capital One; Finder. OneFamily Aqua; STRAT7; Lloyds. Aqua
These are survey estimates, rather than observed user counts. They also generally use “advice” in its everyday sense: asking a money question does not establish that someone received a personalised recommendation or created a financial plan.
How fast is usage growing?
The strongest conclusion is that adoption is substantial, but its direction and speed remain uncertain.
- The clearest year-on-year comparison I found reports a decline. Finder puts usage at 40% in 2025 and approximately 31% in 2026: a fall of 9 percentage points, or approximately 23% relative to the earlier level. Its published page contains inconsistencies—30% versus 31%, and some conflicting tables—so I would describe this as a reported decline requiring methodological confirmation. Finder UK
- High current usage does not establish growth. Aqua’s finding that 35.2% use AI weekly indicates frequent use, but the published 2026 results alone cannot tell us how quickly that frequency increased. Aqua
- There is evidence of intended expansion among younger investors. FCA research published in August 2026 found that four in five less experienced investors aged 18–40 had used AI for investment help, and approximately two-thirds expected to use it more over the following year. This is a selected investor population, and an intention rather than measured growth. FCA
It would therefore be misleading to line up different organisations’ surveys and claim that usage rose from 13% to 55%. The question being asked changes the answer dramatically.
What this means for financial planning
There is evidence of use beyond simple financial definitions. Lloyds reported that 39% of its financial AI users used it for future financial planning, including pension information. However, that does not tell us how many maintain a comprehensive plan or use lifetime cashflow modelling. I did not find a defensible national estimate for those deeper planning activities. Lloyds Banking Group plc
For the Academy, my interpretation is that the important shift is already visible: people can arrive at professional support having researched, compared and explored their own financial questions. The evidence supports designing for that behaviour; it does not yet support a claim that AI is rapidly replacing planners.
A defensible statement for Academy writing would be:
UK research shows that millions of adults already use AI for financial information, guidance and decision support. Estimates range from around one in eight for specific financial decisions to roughly half for broader money management. Adoption is substantial, particularly among younger adults, but a reliable national growth rate has yet to emerge. OneFamily
Older, wealthy and advised clients
The strongest case is that AI is already changing the behaviour of older, wealthy and advised clients. Advisers do not need to believe that AI will replace them to recognise that their service must adapt.
I would use these four findings, in this order:
| Evidence | Statistic to use | Why it matters |
|---|---|---|
| Older consumers — Lloyds, August 2026 | 47% of 55–64-year-olds and 35% of 65–74-year-olds have used AI for personal finance. | Directly challenges “our clients are too old”. This measures broad financial use, rather than comprehensive planning. |
| Wealthy advised clients — Boring Money, September 2026 | 44% of advised clients with over £1 million in investable assets have used AI for financial support; 34% among those with £500,000–£1 million. | Addresses advisers’ actual target market: people with substantial assets who already have professional advice. |
| Advice relationships — Wealthtime/the lang cat, August 2026 | 63% of surveyed advisers report having clients who use AI in relation to their financial advice. | Shows the change is already entering existing client relationships. |
| Expectations — Boring Money, September 2026 | 63% of advised clients say they would be comfortable using AI for monitoring investments and flagging changes, tax opportunities or portfolio risks. | Indicates an appetite for support between meetings, although willingness is not actual adoption. |
Sources: Lloyds; Boring Money; Wealthtime. Lloyds Banking Group plc
The most persuasive evidence concerns what clients are doing.
Wealthtime’s survey of 175 UK advice professionals reported that:
- 59% said clients use AI to prepare questions before meetings.
- 50% reported clients using AI to check or validate advice.
- 44% said clients use AI to research advice firms.
- 35% reported clients generating their own financial or investment recommendations.
These are percentages of advisers reporting those behaviours, not percentages of clients. That distinction makes the argument more defensible. Advisers
The implication is significant: the adviser is increasingly joining a conversation the client has already started. Value must therefore include helping people test assumptions, understand trade-offs and make sound decisions with the information they bring.
How to justify starting within 6–12 months
I would present that timeframe as a practical business recommendation, rather than a prediction proven by the surveys.
There is a useful counterpoint: Wealthtime found only 2% of advisers reported losing a client because of AI. The evidence currently supports changing client behaviour more strongly than widespread client departure. Advisers
That gives you a credible argument: firms have an opportunity to adapt while relationships remain intact. They can use the next annual review cycle to:
| Timing | Concrete change |
|---|---|
| Next 3 months | Ask clients whether they use AI, for which financial tasks, and what they find useful or confusing. Record results by age and wealth. |
| Within 6 months | Pilot meetings that welcome clients’ AI research and help them examine evidence, assumptions and alternatives. |
| Within 12 months | Review the service proposition, pricing and between-meeting support using what clients actually value and can increasingly do themselves. |
My recommended argument
The FCA gives you authoritative evidence about younger investors. Lloyds closes the age objection. Boring Money closes the wealth objection. Wealthtime shows how the advice relationship is already changing.
Together, they support a sharper question than “Will AI replace advisers?”:
If your clients can increasingly research, compare and question for themselves, what will they value you for—and how will your service reflect that within the next year?
One qualification: Boring Money’s published release does not disclose the sample sizes within each wealth bracket. Use its figures with attribution, rather than implying precise estimates for every adviser’s client bank.
