The Future of AI Isn’t Inevitable — It’s Intentional

AI isn’t just the next wave of technology. It is changing the pace at which we work, the quality of decisions we make, and the expectations customers bring to every digital interaction. But, the future of AI is not predetermined. It will be shaped by the choices that businesses make now. 

At this year’s Money Experience Summit, Sol Rashidi, the world’s first Chief AI Officer, challenged us to rethink not only what AI can do, but what we should do with it. Put simply: “AI has happened, it is happening, and our perspective has shifted.” 

Here are a few key takeaways — and what financial institutions and fintechs should think about next.

The Gap Between Using AI and Doing AI Is Wider Than We Think

Many organizations believe they’re “doing AI” when they’re simply using it. Rashidi drew the distinction sharply:

“Using AI is applying ChatGPT, Copilot, or Perplexity to summarize an email. Doing AI means decomposing workflows, figuring out where machines automate and where humans must decide. That’s a completely different level of effort.”

For financial institutions navigating legacy systems, regulatory requirements, and high consumer expectations, this distinction matters. Using AI can improve efficiency, but doing AI can build long-term value, transform experiences, and unlock entirely new capabilities.

Not Every Problem Needs AI, but Every Problem Needs Clarity

In explaining the correct application of AI, Rashini played on the old adage of using the right tool for the right job. She said, “If you’re cutting a piece of paper, scissors work perfectly. Why introduce a chainsaw? That’s the power, and the risk, of AI.”

While some use cases will make sense for AI, there are just as many that will either be a blend of human and AI — or should remain human-only. For instance, our research shows consumers are not ready to trust AI when it comes to more complex financial actions such as financial advice and processing loans. When asked how likely they are to trust AI to help with specific finance-related actions, areas consumers were least likely to trust Ai were: 

• Providing basic financial advice(46%)
• Categorizing transactions to help understand where money is going (42%)
• Processing a loan or credit application based on their financial data (42%)
• Providing investment-related financial advice (39%)

 For financial services, AI needs to be more nuanced than the catch-all buzzword it has become. And, the  future isn’t replacing humans with AI. It’s leveraging AI to support humans where it can streamline efficiency, add data-driven value, and make a meaningful difference.

AI Is Only as Good as the Data 

“AI is simply a data product. It’s only as good as the data feeding it.” — Sol Rashidi

Without disciplined, consistent, well-governed data, even the most advanced AI systems cannot produce meaningful outcomes. AI doesn’t compensate for weak data foundations — it amplifies them.

In the financial industry, bad data could lead to genuinely poor outcomes for consumers; inaccurate credit assessments that misclassify a borrower’s risk, flawed personalization engines that surface irrelevant or misleading insights, and broken fraud-detection models that generate false positives or overlook real threats. 

AI fueled with bad data can also distort budgeting tools, disrupt onboarding flows, and cause conversational AI to give incomplete or incorrect guidance. Any and all of which can erode trust and undermine the value AI is supposed to create.

As she put it, leaders must recognize that data is not a technical afterthought, but the core ingredient that determines whether AI evolves into something genuinely useful or remains an unrealized promise.

The Next Era of AI Will Require Human Judgment More Than Ever

Even the most advanced systems struggle to interpret nuance, context, emotion, and intention.

The devil is in the details as the saying goes. AI, while amazing and efficient at broad strokes, makes mistakes in the details. Rashidi illustrated this with a simple but striking example of an AI vision model misidentifying shadows on a dog as a tiger. 

As AI becomes more universal, these mistakes will continue to pile up and compound the issue. And, the only way to mitigate this issue is by scaling the injection of human judgment into the process along the way. As Rashidi stated “Critical thinking is the human differentiator, and we cannot outsource it.” 

The Future of AI in Financial Services

AI’s momentum is undeniable. However, its value, especially in financial services, comes down to how thoughtfully it’s applied. 

As we look ahead, the real opportunity is not simply to implement AI, but to use it as a catalyst for a more connected, more intuitive, and more human financial experience.