Has AI in Fintech Become Powerful Enough to Replace Financial Advisors?

Artificial intelligence has already made its presence felt throughout a vast range of industries, but perhaps none more so than in the fintech landscape. With investors already beginning to lean heavily on agentic AI for insights, are the days of human financial advisors numbered? There’s little doubt about the sheer scale of the ongoing AI revolution in fintech. Data suggests that the global artificial intelligence in fintech market size was valued at $36.96 billion in 2025 and is projected to grow to $241.67 billion by 2034, representing a CAGR of 23.2%. With the rise of large-language models (LLMs) and a conversational means of bridging financial literacy gaps, it’s become natural for more investors to look to AI models for advice. According to a Pew Research Center study last year, 34% of US adults and 58% of those under 30 have already used ChatGPT, a share that’s roughly doubled in the span of two years. However, there’s also a worrying increase in the volume of US adults making a loss on their investments as a result of bad advice from AI chatbots. In a 2025 survey of 2,000 investors in the United States, 19% reported losing more than $100 by following financial advice from an artificial intelligence chatbot. For Gen-Z investors, the figure was even more concerning, rising to 27%. But while LLMs have struggled to meet investor expectations, the story appears to be different for purpose-built robo-advisors and the implementation of advanced AI tools in the world of fintech and wealth management. Now positioned as a low-cost and dynamic alternative to human financial advisors, could artificial intelligence really emerge to provide greater levels of growth for portfolios and expert-quality investment advice? Let’s take a deeper look at a technology that has the potential to disrupt investing as we know it. The Arrival of AI Investing This isn’t a case of speculating about the future of a technology that’s yet to emerge. We’re already in the midst of the age of AI in fintech, and for all the hallucination risks and bogus advice that chatbots have been prone to serving users, there are plenty of examples of artificial intelligence functioning exceptionally well. “Some platforms use AI to rebalance your investments based on your goals and risk tolerance,” highlights a Wealthify rundown of artificial intelligence in the financial sector. “In March 2023, Finder.com launched a ChatGPT-managed investment fund with 38 stocks. Over two years, the fund surged by 41.97%, outperforming the UK’s top 10 funds, which gained just 27.63%. At its peak, it beat the competition by almost 23 percentage points.” “Top performers included NVIDIA (up 377.44%), Meta (up 253.6%), and Netflix (up 208.93%). ChatGPT clearly picked some winners, sparking growing interest in AI for investing.” How did ChatGPT outperform the United Kingdom’s leading funds? According to a study published in July 2026, Financial advice behaviour: humans versus AI , artificial intelligence co-advisors have the ability to deliver more scalable and affordable advice. Authored by Ylva Baeckström, senior lecturer at King's College London, the study found that human financial advisors are more prone to projecting their own portfolios onto clients, while AI advice is largely dependent on the model used, with findings suggesting that ChatGPT is the least biased option compared to Gemini-biased projections, which collapse when removing advisor demographics. LLMs were also found to be more conservative than human advisors, with lower Sharpe ratios that deliver up to 18% lower 20-year terminal wealth. But lower costs mean that AI has more room to excel while human advisory fees erode any possible excess gains, with a 20-year breakeven fee of 1.03 p.a. Dynamic Profiling As Baeckström noted in her study, AI is excelling at providing impartial portfolio management, and with the help of machine learning (ML), the technology is helping robo-advisors to become better aligned than ever with the personal financial goals of investors. Notably, ML is supporting innovations in dynamic profiling among robo-advisors. This means that more investors can benefit from a hyper-personalized level of risk tolerance when it comes to building their investments. Algorithms can analyze real-time spending habits, income changes, and behavioral interactions to craft a highly accurate investor profile that can evolve as our expectations change. This is vital in bridging investment gaps that have discouraged would-be investors from taking their first steps in moving out of savings-oriented portfolios. In a 2025 YouGov poll, 65% of UK adults who claimed to be unwilling to invest using Stocks and Shares ISAs listed risk as a contributing factor. In delivering a more accessible level of personalization that’s more reliable and cost-effective than human advisors, AI can make inroads in overcoming these fears among would-be investors. Real-Time Rebalancing Another advantage that ML holds is that it’s an always-on tool that processes massive datasets in real-time and scours historical trends to accurately forecast market movements. This allows the technology to dynamically adjust asset classes as a means of mitigating emerging challenges and improving risk-adjusted performance at scale. This opens the door to rapid response times for investors in a way that allows their portfolios to remain profitable even when unexpected events are occurring that human advisors may be slower to react to, especially when juggling multiple client portfolios. Although machine learning assistance in the investment landscape will only be as efficient as the datasets it’s trained on, artificial intelligence tools are already growing their use cases in supporting investors with varied financial capabilities and expectations, no matter what their needs are. The Future of Investing At this stage, it’s important to acknowledge the limitations of AI. As we’ve already seen, ChatGPT and its hallucinations can cause a large proportion of investors to make losses based on the advice of LLMs. However, we’re also seeing plenty of evidence that, when correctly deployed, artificial intelligence can serve as a dynamic, low-cost alternative to human financial advisors that can not only help to provide greater access to investment opportunities but also lower the inhibitions of those wary of taking steps into the world of investing. As the technology matures, we’re likely to see far more adaptable ways for individuals to manage their wealth on their own terms. While human advisors will still have a role to play in providing bespoke support for clients, particularly HNW individuals who prioritize reliability and consistency, artificial intelligence will play a leading role in providing critical investment services to individuals, no matter their wealth and risk tolerance.