Commercial Banking’s AI Breakthrough

Commercial banking has long prided itself on relationship-driven service, with bankers cultivating trust and tailoring solutions to each client. But as Blake Balsamo — Executive Director, i2i Logic, Americas — explains, that very strength has also become a weakness. “The human-centered model has been effective, but it’s expensive and slow to scale. Banks end up devoting disproportionate resources to top-tier clients, while the long tail of small and mid-sized businesses remains underserved,” Balsamo says. 

Despite years of investment in CRM systems, loan origination platforms, and compliance tools, front-line sales and client engagement have been left largely untouched, he finds. The banker’s role as the main channel for business development, therefore, has proven resistant to change. 

Balsamo points out a fundamental distinction between investment banking and commercial banking: “In investment banking, you’ve got oceans of public data to mine. In commercial banking, most clients are private, and their data isn’t easily accessible. That makes traditional analytics platforms less effective.” 

This opacity, coupled with the personal nature of banker-client relationships, has limited technology’s impact. Instead, software providers have focused on back-office efficiencies rather than front-line growth. “What’s been missing,” Balsamo points out, “is innovation that helps bankers generate business — not just process it.” 

That landscape, however, is starting to shift. Banks are realizing they already hold a goldmine of client data — if only they can organize and use it effectively. Pair that with advances in artificial intelligence, and the potential becomes clear. 

“AI can help bankers synthesize insights from both internal and external data, so instead of going into a meeting with just a pitch book, they go in with highly specific, personalized solutions,” observes Balsamo. “It’s the difference between a generic conversation and one that feels like it was crafted uniquely for that client.” 

Over time, AI won’t just empower bankers; it will engage clients directly, particularly for smaller businesses that haven’t traditionally had a dedicated financial services professional. “Imagine an AI agent that can guide a company through cash management or capital solutions, all while seamlessly connecting them to the bank’s services,” Balsamo notes. “That’s where scalability happens.” 

For banks, the implications are significant. Those who continue to scale only by hiring more bankers face spiraling costs. But those who harness AI-driven client engagement can reduce their dependency on headcount while expanding reach. 

A model scenario demonstrates the impact: Adding 50 new bankers produces modest growth in operating income. By contrast, layering AI and advanced analytics into the same model yields a 70 percent uplift in just two years. Much of that growth comes from tapping into the long tail of clients who were once overlooked.

“This is a transformation as profound as the shift from branch banking to online banking,” says Balsamo. “At first, customers clung to the old way. Then they embraced digital — and there was no going back. We’re on the cusp of the same kind of evolution in commercial banking.” 

The outward-facing advantages of deeper AI integration also carry inward implications that bankers should recognize. For example, Balsamo points out that technology innovation, particularly AI-driven solutions, will reduce dependency on banker headcount for scaling operations. 

That shift could alter hiring practices, reducing reliance on traditional banker headcount. Future hiring practices in banking, Balsamo suggests, may center less on traditional relationship managers and more on tech-savvy professionals. 

Forward-looking bankers embracing technology will have the opportunity to become even more valuable to their institutions. Inroads to this upside will be bolstered by sharpening their abilities to offer hyper-personalized insights and tailored solutions to customer needs. 

For bankers looking to thrive in this transformed financial services industry, therefore, training will be key, Balsamo suggests. To succeed, tomorrow’s bankers will need to equip themselves with hyper-personalized customer insights and adapt to AI-enhanced workflows. Doing so, Balsamo suggests, will enable them to focus on higher-value tasks such as strategic client engagement, while AI handles routine interaction and data-driven analyses.  

The present challenge is timing. Technology is advancing rapidly, and corporate clients — mirroring their retail counterparts — are increasingly open to digital interaction. 

While Balsamo focuses on the client engagement opportunity, it’s worth noting that C-suite leaders will also need to weigh regulatory considerations. Any AI deployment must align with standards around data privacy, model transparency, and fair lending — areas regulators are paying close attention to. 

Banks that act now could reshape market share dynamics for decades, and those with a sharp vision of the potential of AI have already started adopting and adapting. Balsamo cites that large banks, both domestic and international, are beginning to develop proprietary systems that integrate internal and external data to generate actionable insights. He further notes that interest in AI-driven client engagement has increased in 2025, signaling a potential shift in how banks approach sales and relationship management. 

“The opportunity is vast,” Balsamo concludes. “Banks that move first will set the standard. Those that don’t will be forced to play catch-up in a world where traditional, banker-heavy models just won’t compete.” 

The largest takeaway from Balsamo’s industry observations is this: The future of commercial banking has reached an inflection point. The institutions that pair banker expertise with AI-driven scale won’t just improve efficiency, they’ll rewrite the rules of client engagement for the next generation.