11 April 2026 · 3 min read · John
Financial advisor AI use in the UK is growing fast — 75% of financial services firms now use AI in some form, up from 58% in 2022. For small IFA practices, the strongest case isn't client-facing technology. It's the hours eaten up by suitability reports, meeting notes, and compliance documentation.
That's where the numbers get interesting.
Advisers and paraplanners spend 10 to 15 hours every week on suitability reports alone. Close to 40% of working time. Tools like Aveni Assist have cut per-report time from 105 minutes to 15 minutes — an 86% reduction. Firms using AI for meeting notes report saving five to seven hours a week. One adviser took on two extra cases a month. Another dropped their outsourced admin budget entirely, saving around £8,000 a year.
These aren't projections. Firms are already seeing this.
Consumer Duty has added a compliance burden that manual processes genuinely can't keep up with. The regulation requires firms to demonstrate good outcomes across every client interaction. Traditional compliance sampling covers roughly 5% of touchpoints. AI monitoring can cover 100%. For a small firm with no dedicated compliance team, that gap is significant.
No separate AI rulebook is coming. Nikhil Rathi confirmed in December 2025 that the FCA won't introduce AI-specific rules — the technology moves too fast. Instead, AI use sits within your existing obligations: Consumer Duty, SM&CR, SYSC, and operational resilience requirements.
In practice, your AI tools need to produce traceable, audit-ready records. The FCA wants to follow your thinking from the client conversation through to the recommendation. If AI is generating suitability reports or capturing meeting notes, those outputs need to connect cleanly to the underlying interaction.
One thing worth taking seriously: 46% of firms report only a partial understanding of the AI tools they use, mostly because they're built on third-party models. For a small firm, that's a real governance risk. You need to know what your tools are doing and why.
Most AI tools for financial services are off-the-shelf products built for the broadest possible market. They're configured around someone else's workflows and someone else's compliance assumptions.
I build tools configured around your practice — your advice process, your report templates, your client communication style, your compliance requirements. The tool works the way you work, not the other way around.
For IFA firms, that typically means AI that captures meeting notes and structures them directly into your suitability report format — removing the handoff time most generic tools leave on the table. Your team isn't learning a new system. They're using something built around the one they already have.
Setup is a one-off fee. Monthly access after that. No consultancy engagements, no strategy documents. A working tool from day one.
If you want to see what this looks like for your firm, I'm happy to talk it through. Book a free 20-minute call or email me directly at john@aigura.co.uk.
Want to see how this applies to your business?
Book a free 20-minute call →The most common uses are suitability report generation, meeting note capture, and compliance monitoring. Tools like Aveni Assist have reduced suitability report time from 105 minutes to around 15 minutes — an 86% reduction documented in UK deployments.
The FCA has confirmed it will not introduce AI-specific rules. AI use by IFAs is governed through existing obligations — Consumer Duty, SM&CR, and SYSC — with the FCA expecting traceable, audit-ready records and demonstrable client outcomes.
Yes. Documented savings include five to seven hours of admin per week and avoided outsourcing costs of around £8,000 per year. For firms with more than one adviser, the productivity gains typically outweigh implementation costs.
46% of firms report only a partial understanding of the AI tools they use, largely because those tools are built on third-party models. Small IFA firms need to be able to explain what their AI is doing and why — the FCA expects that reasoning to be traceable from client interaction through to recommendation.