AI isn't just another productivity tool for the banking sector — it may become the dividing line between winners and losers for years to come.
That is the key takeaway from Bank of America's latest banking industry report, published after panel discussions at its annual Financial Services Conference.
The conclusion is direct: Wall Street banks are not at the greatest risk from flashy AI startups. They are at risk from competitors that deploy AI faster and more effectively.
Disruption Will Come From AI-Savvy Peers
The biggest threat to legacy financial institutions may not be AI startups. In other words, AI won't necessarily replace banks.
Instead, panelists and management teams participating at the conference indicated that incumbents face greater danger from peers that integrate AI deeply into operations, underwriting and client workflows.
In other words, this is a race inside the industry.
That debate comes as bank stocks struggle. Year-to-date, the Financials Select Sector SPDR Fund (NYSE:XLF) is down by over 5%, showing the worst sector performance behind tech.
But Banking Is More Than Code
“We believe the stickiness of client relationships human interaction that demands high-touch service across capital markets, commercial banking and wealth combined with regulatory requirements raise the barrier to entry,” said analyst Ebrahim H. Poonawala in the report.
The implication is clear.
Even as AI agents become more capable, trust, compliance and capital strength remain structural advantages for established banks.
Regulation acts as a moat. Licensing requirements, capital rules, data residency laws and supervisory oversight make it difficult for new entrants to scale quickly.
Adapting to technological change is "in the DNA of the banks," Poonawala said, referencing years of competitive pressure from fintech firms in online banking, payments and robo advisory.
Still, AI could narrow the gap between large banks and smaller competitors. As automation simplifies processes, the traditional advantage of operational complexity may shrink.
A New Era Of Efficiency For Banks
The most immediate transformation is expected in back and middle office functions, areas filled with manual and rules based processes.
Panelists highlighted KYC, anti-money laundering checks, fraud detection, accounting reconciliation, and document review as early automation targets.
These workflows are structured and often offshored, making them attractive for AI deployment. Automating even a portion of these tasks could lower run-rate expenses and improve operating leverage.
Banks that move early may cut costs faster and reinvest savings into growth, technology and talent. Banks that delay risk falling behind on efficiency.
Bubble Or Structural Shift?
The panel acknowledged bubble-like behavior in parts of the private AI market, with companies raising hundreds of millions of dollars at early stages.
Yet participants framed the bubble as "a feature, not a bug." Even if valuations reset, the underlying infrastructure such as data centers, computing power and hardened data pipelines is likely to retain long term value.
Bottom line: for Wall Street banks, the real divide won't be between incumbents and startups — it will be between institutions that hardwire AI into their core operations and those that relegate it to pilot projects and press releases.
Photo: Who is Danny/Shutterstock
