The Real AI Opportunity in Fintech isn’t Automation

I woke up today and started writing. After I’d written a few hundred words, I asked the paid version of ChatGPT for feedback. It provided meaningful, targeted input without rewriting what I had sent. It refreshed my energy by explaining in detail what was working and why. I applied most of the feedback and sent a revised version. It reviewed it carefully and suggested minor edits that strengthened my point without changing my voice. 

I then moved on to responding to a few consulting opportunities. For one, I hadn’t heard of the company requesting my services. Wary of scams, I asked ChatGPT if it was legitimate. It shared credible sources, validated my concern, and pointed out common LinkedIn scams to avoid. 

Does this sound familiar? 

Aren’t many of us using AI in this way - as an ever present helper that goes far beyond simple search or task completion? Whether we want to admit it or not, AI has become behaviorally similar to a trusted co-worker or confidante, offering feedback, reassurance, and support.  

When we talk about AI, we usually focus on its ability to process enormous amounts of data and produce precise answers. Especially in fintech, the conversation centers around operational efficiency, automation, and scale. This is how generative AI demonstrates “intelligence”: by doing in seconds what would take humans hours. 

What we talk about far less is the emotional connection many of us have formed with these tools. Through language, AI can encourage, clarify, reassure, and respond with empathy. It meets human needs that we once assumed only other people could.

Here’s why this matters. 

We are at a turning point in how AI is shaping digital experiences, including in banking. We cannot afford to ignore how these tools make people feel.  Many of us once felt the same way about user experience that some leaders now feel about AI. 

In the 1990s and early 2000s, the priority was simply enabling digital transactions. How the experience felt seemed secondary. Over time, we learned that usability, trust, and emotional response were just as important as functionality. Today, UX is a discipline, a profession, and a strategic advantage.

We did not unlock the full value of digital banking until we understood that experience mattered as much as automation. In the same way, we will not unlock the full value of AI until we stop treating it as the product itself and start focusing on what it enables.

Financial technology must still be about solving real problems. 

In the current AI “arms race,” it’s easy to lose sight of the consumer. People are not asking for more AI in their banking applications. They want help managing their money, preventing fraud, and growing their businesses. Yet many organizations talk about AI as if it were the solution rather than the technology supporting it. 

Too often, AI is layered onto existing products without enough thought about intrusiveness, usefulness, or relevance. But consumers are beginning to push back.

According to the BAI 2026 Banking Outlook, the number one request for enhancement in banking software is to provide more human support. Over half of respondents rated their digital banking experience as average or worse, citing frequent technology changes as their main frustration. 30% ranked 24/7 customer service as their top desired improvement, and 24% wanted the ability to text a live person.

The study then concluded that AI could help extend customer service hours, but real human interaction remained essential. This raises an important question: what if AI-driven support is failing not because it uses too much AI, but because it uses too little of its true capability?

In highly regulated industries like financial services, digital assistants are often deployed with narrow, risk-averse guardrails. This is understandable. What if AI gives incorrect financial advice? What if it reassures a customer when it shouldn’t? In an environment shaped by fraud risk and regulatory scrutiny, every new interface represents potential liability.

And sometimes AI is wrong. 

We see disclaimers everywhere. 

As a result, many fintech implementations reduce AI to little more than a scripted question-and-answer tool. Meanwhile, general-purpose tools like ChatGPT are demonstrating how much more is possible: nuanced dialogue, context awareness, and emotional intelligence.

This is the paradox of AI. It carries real risk and cannot replace human judgment. Yet it is increasingly capable of filling both logical and subjective roles that were once exclusively human. Navigating this tension is one of the central challenges of our time.

I don’t have all the answers. But I know we will not make meaningful progress if we continue to hide or suppress the emotional and relational capabilities of these systems. 

The opportunity is not just greater efficiency. It is the chance to create more thoughtful, supportive, and responsive digital interactions.

In fintech, leaders cannot afford half-measures.

Some use cases must remain rigid. Transactions require precision. Transfers leave no room for ambiguity. Strong controls, disclosures, and accountability frameworks are essential.

But other moments — financial insights, guidance, education, and support — require something different. Here, excessive risk aversion limits value. In these contexts, AI should be allowed to engage more fully, using its capacity to contextualize, explain, and empathize.

Product leaders should not fear AI. They should design for it responsibly.

When done well, AI can help users feel informed, supported, and confident — not replaced. The future of financial services will not be defined by how much AI we deploy, but by how intentionally we integrate it into human-centered experiences.