According to recent research over 50% of UK adults have used AI to manage their money in the last 12 months. The proportion of pension schemes meaningfully using AI to support those same members is a fraction of that. This is one of the most under-discussed risks in pensions today, and it cuts across both how schemes operate behind the scenes and how they engage with members directly.
The questions members are asking aren't new. When can I retire? Should I transfer out? Have I got enough for retirement?
What's new is where they're going for answers. Free, fast, conversational AI sits one tap away in browsers and mobile phones. It's confident. It tailors responses. It asks follow-up questions. And it can feel genuinely useful in a way many scheme websites simply don't.
The gap between member adoption and industry adoption isn't surprising. Schemes have regulators to consider, risk assessments and due diligence to complete, and governance to work through before anything is launched. ChatGPT, Gemini and Claude, in the context of pensions, have none of that. But the longer the gap stays open, the more these public tools become the default starting point for pension questions. Once that habit forms, it's very hard to reverse.
The headline risk isn't that AI refuses to help. It's that AI helps confidently, and even the advanced models of today can get it wrong.
There are three failure modes worth knowing about, all of them already in circulation.
Out-of-date information. Normal retirement ages, scheme rules, and contribution limits that changed years ago still surface as current answers, because the older content is still live somewhere on the internet.
Wrong scheme entirely. Pension schemes love acronyms. When a website is hard to navigate, large language models will sometimes pull information from a similarly named scheme and present it as the answer. Different rules, different options, same level of confidence.
Unscrupulous sources. Ask "should I transfer out of my DB pension," and the answer may come back warmly endorsing the idea, with the source being a firm whose business model depends on convincing you to do exactly that.
Lloyd's research suggests around 80% of users know AI might be wrong. But fewer than 10% actually click to validate the source provided. People check sources when they're unsure of the answer. A well-written, personalised, confident response doesn't trigger that instinct.
Most of the conversation about the AI gap focuses on member communications. The harder conversation is about administration.
Members never see admin systems. But they feel them every time something works, and every time something doesn't. A retirement quote that takes weeks. A transfer that stalls. A query that goes unanswered. None of those moments feel like "back office" from where the member is sitting.
And AI is almost certainly already running somewhere in your administration supply chain. The October 2025 PASA Data Working Group paper on AI in pensions administration sets out where it's showing up: virtual assistants for member enquiries, predictive analytics for behaviour patterns, fraud detection across data flows, AI-assisted document retrieval. Dentons' 2025 Laws of AI Traction Report found that the majority of global businesses have no formal AI governance strategy in place. There's no reason to assume pension suppliers are an exception.
The Pension Schemes Act 2026, the small pots consolidation programme and the pending arrival of pensions dashboards all raise the bar on what good pension adminintration looks like. Platforms like Altair are built for this kind of environment: integrated, auditable and capable of supporting the operational integrity members increasingly expect.
The same gap shows up at the member-facing end, just more visibly.
UK members are now spending their days inside apps that respond in seconds, remember them and personalise everything down to the colour of the buttons. Then they receive a 16-page benefit statement in the post. The contrast is doing real damage to the industry's standing.
The data backs this up. The Money and Pensions Service's MoneyView 2025 study identified 10.5 million UK adults as "disengaged and inactive" with their pensions, and another 6.2 million as "confused and concerned." Research from People's Pension found that 49% of employers say providers don't communicate as effectively as they could. The industry tends to frame this as a member education problem. It isn't. It's a signal that what schemes send doesn't land.
AI changes the unit economics here. Personalised, mobile-friendly, video-led communication used to be financially out of reach for most schemes. It isn't any more. Tools like Video Engage are built specifically for this: personalised video communication that meets members where they are, in formats they actually engage with.
During our joint webinar on AI in pensions with Quietroom, Chris Connelly, Chief Strategy Officer at Heywood, walked the audience through what goes on inside a properly built AI tool.
The short version: an inbound query is stripped of personally identifiable information (PII), filtered for inappropriate language and intent, routed to a controlled knowledge store with proper access controls, optionally augmented through a large language model with prompts that reinforce what it can and can't say, checked for hallucinations by cross-referencing against another model, verified for source credibility, and re-stripped of any PII before the response goes back to the user.
As Chris put it, that's the work that goes into a single, simple answer.
None of that is happening when a member opens ChatGPT and asks about their pension. This is the juxtaposition at the heart of the AI gap. The industry is doing the careful, regulated, slower work of building AI safely. Members are using tools that skip every step. And the longer schemes treat this as someone else's problem, the further the gap widens.
The first job isn't to invest in AI tools. It's to get your house in order. For trustees and scheme managers, that means three things in the near term.
First, find out where AI already sits in your supply chain. Ask your administrators, your communications providers and your technology partners directly. You may be surprised by the answers, and more surprised if there aren't any.
Next, audit what's actually live on your public website. Out-of-date PDFs, contradictory FAQs and orphaned scheme documents are now training and retrieval material for the AI tools your members are using. They have the potential to surface whether you want them to or not.
Third, decide what your governance position on AI actually is, before someone else decides it for you. Trustees who can articulate that position will be in a stronger place when the regulator, the membership or the press starts asking.
Pensions dashboards will sharpen all of this. The moment members can see all their pensions in one place, the natural next question is "what should I do with this?" When that happens, the answer they get won't necessarily come from you.
The schemes that close the AI gap won't be the ones with the most advanced technology. They'll be the ones whose administration members can rely on, and whose communications members actually open.
The themes in this article were explored in our joint webinar with Quietroom, Harnessing AI's potential while managing its risk.