Fifty-five per cent of Brits check their finance apps every single day. Four in ten have at least three such apps installed on their phones. Now, fresh research suggests 345 in every 1,000 of those users would feel comfortable letting artificial intelligence offer them financial advice.
The figures emerge from Apadmi’s Finance App Report 2026, which surveyed 1,000 users about their relationship with money-management software. The Manchester-based mobile development firm found that 34.5 per cent would trust AI to deliver personalised financial guidance or enhance their experience—a threshold that suggests the technology has crossed from novelty into potential mainstream acceptance.
That’s a notable shift.
Traditional financial advisors have spent decades building trust through face-to-face meetings and regulatory oversight. Now, more than a third of app users are willing to bypass that human intermediary entirely, letting algorithms interpret their spending patterns, forecast expenses, and recommend actions. The implications stretch across high-street banks, challenger fintech firms, and wealth management platforms—all racing to integrate AI features whilst navigating Financial Conduct Authority guidelines on automated advice.
Yet the research also exposes a tension. Whilst users express openness to AI-powered insights, their immediate priorities remain stubbornly practical. Nearly half—48.5 per cent—said faster performance would most improve their finance app experience. Another 23.5 per cent ranked an easy-to-use interface as the most crucial feature when choosing which app to download.
Speed and simplicity, in other words, still trump sophistication.
The daily dependency figures help explain that priority. When 54.7 per cent of users are opening finance apps every day—checking balances before morning coffee, reviewing transactions during lunch breaks, transferring money before bed—lag time becomes intolerable. A brilliant AI recommendation means little if the app takes eight seconds to load or buries key functions three menus deep.
Still, 17.07 per cent of respondents said they want additional financial insights and tools within their apps. That’s roughly one in six users actively seeking more than basic balance checks and transaction histories. They want spending pattern analysis. Expense forecasting. Tailored recommendations based on their financial behaviour. The kind of proactive guidance that AI promises to deliver at scale—without the £150-per-hour fee that human advisors typically charge.
Caitlin Meechan, Growth Director at Apadmi, framed the findings as a balancing act. “These findings show that people are becoming increasingly comfortable with AI playing a role in how they manage their finances,” she noted. “As finance apps become a daily tool for many users, there’s growing demand for more intelligent features that can help interpret spending habits, surface useful insights, and support better financial decision-making.”
She added: “At the same time, the fundamentals still matter. Users expect finance apps to be fast, intuitive and reliable, and that remains key to building trust. From there, providers have the opportunity to layer in smart, personalised features that enhance the experience and help people feel more in control of their finances.”
The report arrives as major banks and fintech challengers scramble to deploy AI features without triggering regulatory concerns or user backlash. Monzo, Revolut, and Starling have all introduced spending insights and budgeting tools that rely on machine learning. Traditional banks including Barclays and HSBC have rolled out AI-powered chatbots and fraud detection systems. None yet offer full-scale AI financial advice—the regulatory threshold for “advice” remains high, requiring FCA authorisation and human oversight.
What’s less clear is how the 65.5 per cent who wouldn’t trust AI with financial advice break down demographically. Are they older users more comfortable with human advisors? Risk-averse investors who’ve read too many headlines about algorithmic failures? People who’ve had poor experiences with chatbots? The survey data doesn’t drill into those segments, leaving providers to guess which barriers are surmountable and which represent hard limits.
The performance findings carry their own implications. If nearly half of users cite speed as their top improvement priority, many current apps are clearly falling short. That’s a solvable problem—faster servers, optimised code, better caching—but it requires investment. For smaller fintech startups, choosing between building flashy AI features and fixing load times becomes a resource allocation dilemma.
Apadmi, whose clients include Domino’s, Chelsea FC, the NHS, and Argos Financial Services, positioned the report as a snapshot of where consumer expectations currently sit. The firm develops mobile apps across retail, sport, healthcare, and financial services—sectors where AI adoption is accelerating but user patience for buggy implementations remains thin.
The multi-app reality complicates the picture further. With 40 per cent of users juggling three or four finance apps, the competitive pressure intensifies. A sluggish app loses users to faster alternatives within days. An AI feature that misfires—recommending an investment that tanks, or misinterpreting spending patterns—can erode trust faster than a dozen successful interactions can build it.
For now, the 34.5 per cent threshold represents opportunity rather than mandate. Providers can experiment with AI-powered features knowing a meaningful segment of users are receptive, whilst recognising that most still prioritise basic functionality over advanced capabilities. The challenge lies in delivering both—intelligent insights wrapped in interfaces that load instantly and never confuse.
Whether that trust figure climbs or plateaus will depend partly on how early AI implementations perform. One high-profile failure—an algorithm that drains someone’s savings through flawed advice, or a data breach that exposes AI-analysed financial profiles—could reverse the trend quickly. Trust, particularly around money, accumulates slowly and evaporates fast.
The full report is available for download on Apadmi’s website, though the headline figures already sketch the landscape: daily dependence growing, AI acceptance rising, performance expectations unmet. The gap between those realities will define which finance apps thrive over the next two years and which get deleted in frustration.
