Banks are better positioned to benefit from AI than many realize

• Key insight: Legacy financial institutions with vast troves of customer data are actually very well positioned to reap the benefits of AI — if they understand how.
• What's at stake: There are real questions about where AI could take us as a society without the proper guardrails.
• Forward look: People want to bank with people, buy financial products from people and know the faces behind the transaction. Technology's role is to augment those relationships, not replace them.
  

The conversation around AI and financial services has reached a fever pitch. Every day brings new headlines about machines replacing white-collar jobs and upending entire industries.

In financial services specifically, fears abound that AI agents will disrupt the business models of banks, wealth managers and capital markets firms — along with the technology providers that serve them.

These fears deserve to be taken seriously. There are real questions about where AI could take us as a society without the proper guardrails. But amidst the noise, it's important to step back and consider what actually drives lasting value in financial services.

In the rush to predict which sectors will be disrupted, the market often overlooks a fundamental question: How do AI models actually deliver value, and where does that value come from?

The answer is data. AI technologies are only as valuable as the data that feeds them. Without high-quality, proprietary data, accumulated over years and embedded in regulated workflows, even the most sophisticated models can't deliver meaningful outcomes.

This is where financial institutions hold an extraordinary advantage. Banks and credit unions, capital markets firms, and insurance providers sit on deep reservoirs of insight into the needs, behaviors, and preferences of their customers, relationships that often span decades. No other private-sector industry has data assets of this depth, duration and sensitivity.

Consider the scope: Across the financial services ecosystem, institutions collectively manage billions of accounts and process tens of billions of transactions annually. They can see money at rest in deposits, money in motion across payment rails, and money at work in lending and investing. In a world where AI-enabled insights depend on integrated, authoritative data, that visibility is enormously differentiating.

Here's the critical nuance. Yes, individual banks hold valuable data about their own customers. But a single institution, no matter how large, only sees one slice of the picture. Its fraud patterns, spending behaviors, and risk signals are limited to its own customer base and its own transaction volume.

Take credit risk models trained on anonymized behavioral data from thousands of institutions; they outperform models built on any single lender's portfolio. Customer acquisition insights drawn from cross-industry spending patterns reveal opportunities no bank could identify from its own data alone. Benchmarking tools that show an institution how it performs relative to peers in real time require a vantage point that only a scaled platform can provide.

This is the part of the AI conversation that too often gets lost. AI doesn't just need data, it needs breadth, diversity and density of data.

And unlike a proprietary dataset that could theoretically be replicated, a contributory network is a compounding asset. Every institution that participates makes the intelligence better for every other institution in the network. That network doesn't just resist disruption, it accelerates with scale. This is where the financial services industry excels.

There's a related point the market is missing. A recent Forbes article made the case that AI agents actually make systems of record more valuable, because these core systems provide the accurate, authoritative data AI needs to function effectively.

Financial services runs on mission-critical systems of record defined by deep integration into regulated workflows, decades of accumulated proprietary data, and enterprise-grade governance, security, and auditability. These characteristics cannot be easily replicated by standalone AI tools or horizontal technology platforms. Financial institutions, and the technology partners who operate these systems, have built something over decades that represents a durable structural advantage.

This is why I'm skeptical of the narrative that positions AI as a wholesale replacement for people and institutions. Financial services is, at its core, a relationship business. When it comes to their money, people want to bank with people, buy financial products from people and know the faces behind the transaction. Trust is hard-won and easily destroyed. Technology's role is to augment those relationships, not replace them.

If we want to know which firms will thrive in an AI-enabled world, here's what I'd look for:

Firms investing in technologies that deepen customer relationships and remove friction across the entire customer journey. Firms deploying AI where it matters most: in risk and fraud prevention, client acquisition, customer service, and portfolio optimization. Firms building on proprietary data assets and regulated infrastructure.

Look for firms that are reinventing branches as multimodal hubs combining physical presence with digital convenience. Firms investing in AI agents and chatbots that free up human talent to focus on complex issues and relationship-building. Firms enhancing trust in their networks through real-time fraud detection powered by cross-network intelligence that no single institution can match.

And look for the deep domain expertise in highly regulated financial processes that new entrants simply can't replicate quickly. The firms that understand always-on systems, that have mastered regulatory frameworks and that have the data breadth to train AI models that outperform point solutions.

We are witnessing a generational moment in financial services. Banks enter this new moment in a position of strength, with excess capital, stable credit and strong operating performance. Technology spending across financial services is projected to increase roughly 30% by 2029. AI adoption is accelerating rapidly, and institutions recognize it's not a future opportunity, it's a competitive imperative today.

But the institutions and technology providers best positioned to lead over the long term are not the ones grabbing headlines with the boldest predictions. They're the ones with the strongest data networks, deepest customer relationships, most resilient infrastructure, and the regulatory expertise that took decades to build.

Despite the headlines, I've never been more confident in the future of financial services or more energized by what comes next.