What is the Fintech AI Bubble?

In early 2026, it may be very well impossible to navigate the fintech space without hearing about the latest way AI is being utilised by the big industry players. Towards the tail end of 2025, amid a flurry of headlines around AI, we also began to hear murmurs of the dreaded “AI bubble.”

What is a bubble?

 

The AI bubble, reminiscent of the dot-com bubble from the late 90s - early 00s, refers to the growing gap between the level of hype and investment into AI, and the proven business value being delivered. Before the dot-com bubble, the world had seen other bubbles come and go, from railroads in the 1840s to radio in the 1920s.

 

With no expectation, comes no disappointment

A bubble is not defined by a technology being useless, fraudulent or overly used. Rather, a bubble forms over time when expectations of value outpace the timelines of its value coming into clear fruition. People become overly excited about the potential of what it could be, rather than what it is at this moment. With that, capital is placed based on the narrative momentum rather than the real-world, operational proof of the technology.

 

What makes the current AI bubble feel different in fintech is not just the pace of innovation, but the sense of urgency attached to adoption for technology vendors. For many firms, AI is no longer seen as an add-on, but instead, something that must be implemented now, or risk your firm falling behind and becoming irrelevant.

At the same time, the way AI is actually being used on the ground is moving more slowly than the headlines suggest. Rolling AI into existing systems and day-to-day workflows is rarely straightforward, especially in areas like fintech where regulation and risk play a central role. While the technology itself continues to develop quickly, real and consistent usage tends to lag behind the expectations created by marketing and media coverage.

 

What do buyers think?

The immediate consequence of this urgency is unnecessary noise. Clients are faced with an overwhelming amount of AI claims, making it harder to distinguish actual usefulness of the technology from marketing buzz. “AI-powered” has become an all-too-familiar tagline for vendors, which may lose its meaning if every platform and device is powered by AI, now being seen as a baseline rather than a signal of revolutionary technology.

 

For the big decision-makers in the industry, this environment introduces an additional layer of complexity. Beyond assessing what a platform offers today, buyers are now having to work harder to separate what is actually live from what is still being built. In many cases, this means reading between the lines of product announcements and roadmaps. Over time, this naturally leads to a more cautious response to AI messaging, rather than the excitement seen in earlier stages of adoption.

 

In fintech especially, where trust and reputation matter, as millions of dollars are on the line, this fatigue can slow decision-making even when AI has the potential to deliver real benefits.

 

So, what can we expect from the AI bubble?

As the market settles, the way people talk about AI is likely to change. Big, sweeping claims will start to matter less, with more attention paid to whether the technology actually delivers practical value.

 

Clients will likely spend less time asking whether a platform “uses AI” and more time digging into how it is being used, what problems it genuinely helps solve, and whether it works within their existing processes.

 

AI capabilities that are clearly communicated, smoothly integrated into products offerings, and tied to specific use cases are much more likely to survive the bubble pop untouched. AI can be just another form of more intelligent automation, typically used in the back- and middle-office in capital markets. We cannot say if this bubble will pop, although all ‘good’ things do eventually come to an end at some point, but regardless, it is clear the hype around AI is slowly forming into caution, as the industry needs to see the technology in action before reacting. In this case, seeing is believing.