Throughout the week in our In Focus series, we’ll be looking at how financial advice firms are using, and can use, artificial intelligence (AI) in ways that are practical, responsible and commercially valuable. With AI firmly at the centre of industry debate, we’ll hear from a range of experts who will share hands-on insights, real examples and clear guidance on how to introduce AI safely and effectively.
Joseph Twigg, CEO of Aveni, explores how AI can ease advisers’ administrative burden and strengthen Consumer Duty evidence through faster reporting and full interaction monitoring, while warning that only purpose-built, well-governed systems with strong human oversight can avoid creating new compliance risks.
The FCA’s AI Review reflects a simple starting point: AI will reshape retail financial services. The question now is how prepared firms are, and what they will be able to evidence.
The checklist is giving way to a harder question: can you prove it? Firms will need to demonstrate, clearly and consistently, that the technology they use supports good consumer outcomes, not just that they followed a process.
As supervision becomes more outcomes-focused, the compliance checklist is giving way to a harder question: can you prove it? Firms will need to demonstrate, clearly and consistently, that the technology they use supports good consumer outcomes, not just that they followed a process.
Financial advisers are under intense administrative pressure. Consumer Duty has raised the bar on documentation and evidence of good client outcomes. FCA supervision is becoming more data-driven. Research from our own implementations suggests advisers and paraplanners spend 10-15 hours each week on suitability reports alone. AI is changing that picture. But how firms approach adoption will determine whether it becomes a genuine asset or a source of new risk.
A genuine opportunity
The most immediate benefit AI offers advisers is time. Meeting transcription, suitability report drafting, CRM updates and follow-up emails all consume hours that could be spent with clients. Aveni’s own data, drawn from implementations across UK advice networks, shows that suitability report preparation time can fall from around 105 minutes to 15 minutes per report when AI is used to capture and process meeting content.
Beyond speed, there is a quality argument. AI tools trained on financial services conversations can apply consistent regulatory language, flag missing disclosures, and check draft reports against Consumer Duty requirements before a human adviser ever reviews them. One compliance team found that AI-generated reports required 40% fewer corrections than those produced manually.
For Consumer Duty, moving from manual sampling to full coverage of client interactions changes the picture entirely. Traditional QA processes review a very small percentage of calls. AI-powered monitoring can cover 100% of interactions, surfacing vulnerability signals, suitability concerns, and conduct risks that would otherwise go undetected.
Where advisers need to tread carefully
AI can deliver real value, but it can also create compliance risk if used without the right controls. In most cases, that risk comes from the same source: the wrong tool, or the right tool used in the wrong way.
Generic AI platforms were not built for regulated financial advice. They lack the domain knowledge to understand concepts like uncrystallised funds, pension lump sums, defined benefit transfer suitability, or the specific disclosure requirements under COBS 9.4. A tool that summarises effectively in a general business setting can still produce outputs that look plausible but fall short in an advice context.
If an AI tool cannot link its outputs back to the source conversation, it becomes difficult to stand behind when compliance challenges it.
Vulnerability detection needs similar care. Consumer Duty requires firms to identify and appropriately support vulnerable customers. AI tools that rely on keyword matching will miss the majority of vulnerability signals. Purpose-built systems that analyse tone, sentiment, hesitation patterns, and conversational context are materially different from general-purpose transcription tools.
Data governance matters, too. Inconsistent CRM records, incomplete fact-finds, and unstandardised documentation all lessen AI output quality. Firms that do not address underlying data quality first will likely find the technology underperforms.
Responsible adoption from the outset
The advisers and firms seeing genuine returns from AI share a few characteristics. They select AI tools built specifically for UK financial advice, with Consumer Duty requirements built into the workflow from the start. They keep human oversight at the centre, with advisers reviewing and approving every AI-generated output before it reaches a client. They take a firm-wide approach to data quality. And they involve compliance teams from the outset, so oversight is integrated rather than treated as a separate step.
The firms that succeed with AI will not necessarily be those that deploy it fastest. They will be those that can continuously prove that AI-supported journeys are fair, suitable and aligned to Consumer Duty.
The audit trail matters as much as the output. Firms that can show a complete evidence chain from client conversation to transcript to suitability report to recommendation are in a stronger position for FCA supervision than those relying on manual records alone.
AI will not replace adviser judgement. Implemented well, it can reduce administrative friction and improve the quality and consistency of the evidence firms rely on to demonstrate good outcomes.
By Joseph Twigg, CEO of Aveni
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