Bridging the advice gap: using AI to deliver wealth advice at scale
The advice gap is widening. Only 9% of UK adults accessed professional financial guidance in the 12 months to May 2024, around 4.7 million people, which leaves most households making complex financial decisions without expert support.
The gap carries a wider societal risk. As Chancellor of the Exchequer, Rachel Reeves noted:
"Too many people are missing out on the support they need to build a more secure financial future for themselves and their families…"
Reforms are underway, but a second challenge is emerging: the adviser population is ageing. The number of advisers over 60 rose from 4,823 to 6,210 as of February 2024, with fewer younger advisers entering the profession. Demand for advice continues to grow at the same time, driven in part by recent economic changes. Following last autumn's budget, Unbiased reported significant increases in enquiries: general tax planning rose by 72.5%, estate planning by 70.3%, and pensions and retirement planning by 9.8%. These figures reflect the growing complexity of financial needs and the pressure on advisers to meet client demand.
This was the focus of The Big Shift webinar, Mind the Advice Gap, which explored practical ways to deliver wealth advice at scale. Artificial intelligence (AI) took centre stage. It can help firms widen access to advice and improve the client experience, but it is often misunderstood and misapplied.
Many firms adopt AI as a quick fix for isolated pain points, such as automating manual tasks, without considering the wider picture. AI works best as a strategic investment in reshaping the business for the future. That starts with a clear problem statement, reliable and well-structured data, and the skills needed to run an AI-enabled business. Without these, solutions fail to scale and the same problems return later.
Where firms sit on the Gartner Hype Cycle
The webinar looked at where firms currently sit on the Gartner Hype Cycle for Emerging Technologies. Most are at the peak of inflated expectations or moving into the trough of disillusionment, which is to be expected in a fast-moving market where many are still learning how to apply AI well.
Despite the attention AI receives, many firms lack a clear plan for how to use it. Implementation often begins with the technology rather than the problem it is meant to solve. Without clean, structured data and a well-defined goal, even the most advanced tools struggle to deliver meaningful results: projects stall, processes stay inefficient and the expected benefits do not materialise.
The more useful question is why a firm is adopting AI, before which tool it chooses. The goal might be to reduce manual effort in back-office processes, improve decision-making through better analysis, or free up adviser time by streamlining workflows.
One example is using AI to scan historic client data and identify households at risk of falling behind on their financial goals. Advisers can then focus on the clients where an intervention would have the greatest impact, rather than reviewing thousands of records by hand. This depends on the underlying data being accurate, structured and accessible.
Strategic priorities to deliver wealth advice at scale with AI
Moving beyond the Hype Cycle calls for a clear and deliberate approach. Adopting new tools in isolation rarely delivers lasting value. The firms that succeed embed AI within wider transformation across data, people and operations.
Several priorities emerged during the webinar for firms looking to embed AI in their operations.
Executive ownership | AI is a business transformation, not a standalone technology project, and it needs visible leadership. Senior executives set the direction, maintain alignment and connect AI to the wider objectives of the business. |
A clear data strategy | A strong data strategy is the starting point for any effective AI initiative, and without one there is no reliable way to manage, govern or scale AI responsibly. Firms need to define how data will be collected, organised and maintained before introducing advanced technology. |
Clarity on the problem to solve | Technology should follow purpose. Whether the aim is to increase adviser capacity, improve onboarding or identify clients who may need support, the use case needs to be clear from the outset. |
Data quality | AI outcomes depend on the quality of the inputs. Inconsistent, incomplete or fragmented data limits what AI can deliver, while clean, structured and well-maintained data supports better insight, more reliable automation and greater confidence in decisions. |
Updated due diligence | Traditional procurement processes were not designed with AI in mind. These tools raise new questions around data access, usage, storage and explainability, and firms need updated frameworks that reflect those risks and meet regulatory and ethical expectations. |
A structured view of readiness | The Alirity AI Readiness Assessment (AAIR) helps organisations assess their current position across data, people, governance and culture, and decide where to focus next. |
Skills at every level | AI brings new knowledge requirements across the organisation. Building confidence and capability, from senior leaders to operational teams, helps people engage with these technologies effectively. |
Clear and empathetic communication | AI brings change, and that change needs careful management. Open, honest conversations about how roles and responsibilities may evolve build trust and support a smoother transition. |
Putting AI into practice
AI can broaden access to advice, improve client outcomes and make better use of adviser time, but the impact depends on how it is applied. Grounded in clear priorities, supported by strong data and led with intent, it can help firms deliver advice at greater scale and with greater confidence.
Progress depends on the technology and equally on the clarity, capability and care with which it is implemented.
How Alirity can help
Alirity is a transformation partner for organisations working through complex change. The team supports organisations in regulated sectors, including financial services, as they respond to the pressures of digital and AI transformation, combining delivery expertise, sector knowledge and proprietary methods.
If you are exploring how to scale advice or adopt AI, contact charlie.symonds@alirity.com.
You can also try the Alirity AI Readiness Assessment (AAIR), a free platform that helps organisations benchmark their readiness for AI adoption and focus effort where it matters most.
