Eighty-seven percent of financial advisers are now using AI for administrative tasks such as note-taking, and 44% for report writing[1]. Those numbers sound impressive until you notice what they describe: AI being used to transcribe and summarise, while the expensive, time-consuming, compliance-heavy work that actually limits how many clients an adviser can serve remains largely untouched.

That is not a criticism. Starting with note-taking is sensible. It is low-risk, immediately useful, and most firms can implement it in a day. But if that is where your AI adoption stops, you are getting about 10% of the available return.

The more useful question for a firm of your size is: what does the full opportunity actually look like, and which tools can you trust in a regulated environment?

Where the real administration burden sits

Sixty point seven percent of financial advice firms use five or more separate systems[1]. That fragmentation is the root cause of most administrative overhead, not a lack of automation within any single system.

The practical consequence: an adviser moving a client through a review cycle touches their back-office platform, their cashflow modelling tool, their client portal, their document management system, and usually a shared drive or inbox on top of that. Intelliflo’s own research found that firms spend 40 hours per 100 clients on administration that should not require an adviser’s time at all[2]. That is roughly 24 minutes of overhead per client per review cycle, before a single piece of advice is given.

AI tools that sit inside one of those five-plus systems help within that system. The bigger efficiency gains come from connecting them.

What to look for in a tool before you select it

Not every AI tool is built with regulated professional services in mind. Generic tools designed for general productivity do not carry the contextual understanding of advice workflows, suitability obligations, or the audit requirements your firm operates under[3]. Before you select anything, ask these questions:

First, where does the data go? Client data used in AI tools is personal data under UK GDPR. You need to know whether it leaves your jurisdiction, who processes it, and whether the vendor’s data processing agreement is adequate. A tool that sends client fact-find data to an offshore LLM without a proper DPA is a problem waiting to happen.

Second, what is the human review step? No AI tool should produce a suitability letter, a report, or a recommendation that goes to a client without a qualified adviser reading and approving it. The AI can draft; the adviser signs off. Any tool that implies the adviser can skip that step should concern you.

Third, can you show your working? Under Consumer Duty, you need to be able to demonstrate that outcomes for clients are good. If an AI tool contributes to a recommendation or a communication, you need an audit trail of how it contributed and who reviewed the output. “The AI did it” is not a position your compliance function can defend.

Fourth, is it embedded or bolted on? Generic AI tools used in isolation require manual copy-paste between systems, which introduces error and creates unlinkable audit trails[3]. Embedded AI within your existing platform is generally more traceable, though it narrows your flexibility.

The four areas where AI delivers real return in an advice firm

Administrative transcription and meeting summaries

This is where most firms start, and rightly so. Tools that transcribe client meetings and produce structured summaries reduce the time between meeting and documented file note from hours to minutes. The risk is low, the benefit is immediate, and the human review step is obvious: the adviser reads the summary before it goes on file.

The caveat is that transcription accuracy matters more in financial services than in most industries. A misheard figure or a missed instruction in a meeting note can have real consequences. Human review is not optional even here.

Report drafting and suitability letter generation

This is where AI can save two to four hours per client case, but it is also where the compliance stakes are highest. AI-generated suitability letters require careful parameter-setting (what the tool knows about the client, what the template constraints are) and thorough adviser review before they go anywhere. The AI drafts; the adviser owns.

Intelliflo’s embedded AI is one example of tooling designed specifically for this workflow, building from the data already held in the platform. Generic tools like ChatGPT used without integration into your client data carry higher risk of hallucination and require more extensive checking.

Client onboarding and KYC

Digital onboarding can reduce KYC processing time materially in regulated financial services[4]. For a firm handling 20 or more new clients a year, that adds up. The specific gains depend on whether your onboarding process is already digital or still paper-based, and whether your selected tool integrates with identity verification infrastructure such as LexisNexis or Socure[5].

This is an area where the tool selection decision is closely linked to your compliance and AML obligations. The output of an AI-assisted KYC process is only as reliable as the data sources it draws on and the human review that closes it out.

Workflow automation between systems

This is the area most firms have not yet touched, and it is where the compound gains are. Connecting your back-office platform to your CRM, your document management system, and your client communication tools via automation (using something like n8n, Make, or Zapier) means that a trigger in one system can initiate a process across all of them, without manual re-entry.

The firms that will get the most from AI are not the ones with the best individual tool. They are the ones that have connected their systems so information flows without manual intervention.

A review reminder in your back-office platform can automatically create a task, pull the relevant documents, and send a client communication, with a human approving each step before it proceeds. That is not science fiction. It is a Level 2 integration that a firm your size can have running in a matter of weeks.

What the agentic direction means for you

The industry is moving from individual AI features toward platforms that can execute multi-step workflows across applications, what is being called agentic AI[6]. Seventy-five percent of businesses say they are interested in this; only 11 to 17% have actually deployed it[6].

The gap between interest and deployment is real. The reasons are worth understanding: 40% of agentic AI projects are cancelled before they ship, usually because of integration complexity, not a lack of good tools[6].

For a financial advice firm, this means two things. The opportunity is significant. And the sensible approach is to start with the simpler integrations, prove the value, and build from there. Committing to a full agentic platform before you have basic system integration working is how firms end up in the 40%.

What to do with this now

First, map where your advisers actually spend their time. Not a formal project. An honest conversation with two or three advisers about where their hours go in a typical client review cycle. The answer will tell you where AI would actually help.

Second, assess your system fragmentation. If you are running five or more systems, the question is not which AI tool to add. The question is whether those systems can talk to each other, and whether the AI tools you select will integrate with them or sit in isolation.

Third, start with one high-frequency, lower-risk task. Meeting transcription and file note generation is the right starting point for most firms. Get that working well, with a clear human review process, before moving to suitability letter drafting.

Fourth, before you select any tool, answer the four questions above. Data residency, human review, audit trail, and integration. A tool that fails any of those four tests is not suitable for a regulated environment, regardless of how good the demo looks.

Fifth, treat the governance requirement as fixed, not variable. AI governance obligations for regulated firms are tightening. An audit trail of AI-assisted decisions and a documented human oversight process is not a nice-to-have. Build it into your implementation from the start.

The firms getting the most value from AI right now are not the ones with the most tools. They are the ones with a clear view of where the time goes, a realistic sense of which problems are worth solving, and a governance structure that means they can defend every output.

If you want to think through what that looks like for your firm specifically, a discovery call with Cordrey Consulting is a good place to start.

This article is for informational purposes only and does not constitute regulated financial advice or a compliance opinion. Consult a qualified compliance professional for advice specific to your firm.

Sources

[1] Intelliflo (2026) ‘Why financial advisers spend more time on admin than advice’, Intelliflo Insights. Available at: https://www.intelliflo.com/insights/thought-leadership/why-financial-advisers-spend-more-time-on-admin-than-advice

[2] Intelliflo (2026) ‘How advice platform tools can give advisers their time back’, Intelliflo Insights. Available at: https://www.intelliflo.com/insights/thought-leadership/how-advice-platform-tools-can-give-advisers-their-time-back

[3] Intelliflo (2026) ‘Why embedded AI is changing the advice journey’, Intelliflo Insights. Available at: https://www.intelliflo.com/insights/thought-leadership/why-embedded-ai-is-changing-the-advice-journey

[4] Test Study (2026) ‘Digital onboarding reduces KYC processing time by 34% in regulated financial services’, internal study cited May 2026.

[5] LexisNexis Risk Solutions / Socure, data enrichment and identity verification tools for regulated financial services, referenced as examples of identity verification infrastructure available to UK-regulated firms.

[6] Digital Applied (2026) ‘Why Agentic AI Projects Get Canceled (and How to Ship)’. Available at: https://www.digitalapplied.com/blog/agentic-ai-project-cancellations-gartner-40-percent-2026