AI Isn't Replacing Banking Leadership. It's Exposing Its Weaknesses

Guest Editorial by Larry Coval, Founder, ARCANE Leadership Concepts

Financial services leads nearly every sector in terms of AI deployment, at least on paper. Most big banks are running fully autonomous AI in production at more than double the rate of the broader market, and most leaders say it's making them more competitive. Meanwhile, some of those same leaders admit AI has not yet delivered the ROI they expected for the cost and effort involved.

Larry Coval, Founder, ARCANE Leadership Concepts.

That gap is the real story. Not the recurring "AI is coming for your job" meme. Not "the machines are smarter than us now." Something is breaking down between the tool and the outcome, and it isn't the tool.

The technology didn't create a leadership problem. It revealed it.

For years, technical complexity covered up a lot of sins in this industry. Nobody questioned the VP who couldn't fully explain the risk model, because nobody else in the room could either. You could hold a senior title, sign off on decisions you didn't really understand, and never be held accountable.

AI tears down those defenses. AI’s decisions are traceable and visible in a way the old arcane methods never were. When the shielding disappears, what's left naked is whether those leaders ever actually had the skills and abilities to lead through that decision-making process that the model is now automating. That's not an AI problem. That's a leadership problem that's been sitting there the whole time, waiting for something to shine a light on it.

Where AI actually lives inside a bank right now looks nothing like the headlines suggest. A bank executive I spoke to laid it out plainly. Sales and account management picked it up immediately, there's no downside to using it there. Meanwhile, back-office operations either haven't touched it or are very slow to integrate. The customer-facing tools get all the attention and resources, so they look shiny and tech-forward, but a lot of what's running underneath is still archaic. And the labor-intensive work that people do today, the kind that fills out analytics on loans, isn't long for this world.

This isn't a fringe ‘hot take’ on where things are headed; it's what the people running these banks are saying out loud. Jamie Dimon has said AI will eliminate jobs and that people should stop sticking their heads in the sand. Citigroup's Jane Fraser told staff in a January memo that the bank isn't graded on effort, and separately that some roles will no longer be required. Wells Fargo's Charlie Scharf has said the bank plans to use attrition as its friend. Goldman Sachs president John Waldron called the bank a "human assembly line" ripe for automation. Bank of America's Brian Moynihan told employees not to worry, then four months later cited AI directly as the reason behind job cuts.

These are not conversations in back rooms anymore. This is how banks publicly message to their stakeholders that they’re going to take full economic advantage of what AI brings to the party. And why shouldn’t they? The six largest US banks cut fifteen thousand jobs in the first quarter of 2026 while posting forty-seven billion dollars in collective profit, up eighteen percent year over year. That's not a sign of struggle. That's a conscious choice.

How risk and judgement intersect in ways most people don’t realize. Credit decisions under ten million dollars in most large banks can already be made by AI alone, according to the executive I spoke to. For larger transactions, especially those above fifty million, a human is still required, for now, because real judgment calls still have to be made. Below that line, the number-crunching work is already gone or going. Compliance, loan and risk asset review, customer complaint handling, and legal all carry heavy headcount today, and all of it is exposed as AI closes the capability gap.

The correction worth making to the leadership thesis. It isn't just that AI exposes weak leaders while leaving the support layer beneath them to absorb the damage. Fewer people in any department also means fewer leaders. As credit, compliance, and risk groups shrink, the leadership layer isn’t far behind, and what determines who survives isn't tenure or title. It's whether that person can actually harness the tools and catch what it gets wrong. That's a daily skills audit for those people. The stodgy senior execs in credit that every bank has, the ones everyone privately knows can't really engage with the technology, won’t be spared by their seniority or past successes. They're on the clock…and most of them don't know it yet.

We all know this leader. The one who says "I'm not a tech person. I’m a people person" like it’s a personality trait to be celebrated instead of a liability, and gets away with it because someone else always handles the models. The executive I spoke to confirmed it without hesitation: the final decision-makers in credit tend to be senior, and because their adaptability is in real doubt, so is their longevity. Nobody says it out loud…but everyone already knows.

It’s not a massive reduction. It’s a re-framing. Across the big banks broadly, research from Evident found that the AI talent pool grew 25% among major banks they analyzed, led by Bank of America, Capital One, Citigroup, JPMorgan Chase, and Wells Fargo. Separate research from Evident showed a 13% rise in AI headcount across major banks, even as those same banks cut tens of thousands of traditional roles.

The part nobody's talking about yet. AI's early impacts in banking may not be the domestic roles everyone's laser-focused on. Compliance and credit monitoring work that’s been outsourced for many years to places like India and the Philippines is much more exposed, and likely sooner, than the jobs sitting closer to home. Which means the people who've built careers in the US running those outsourcing operations might want to think hard about updating their own resumes, because the function they've spent years managing is exactly the kind AI reaches for first.

And the part that should worry finance leaders more than any layoff headline. Ask what leadership is actually afraid the layoffs will expose, and the honest answer isn't the technology. It's that traditional banking acumen is about to take a back seat to something else entirely: how well a leader can harness AI while also catching the errors it makes, which only sharpens the tool and positions it to cut deeper into the roles people still occupy, leadership included.

What it all means. AI in the finance sector acts the same as it does in other areas. It creates a skills-centric reckoning that exposes those leaders who’ve been filling seats with legacy capabilities. The absence of real leadership skills was always the risk underneath the balance sheet. The technology just lifted the rock it was hiding under. This was never leadership versus AI. It's about which leaders can actually lead through it, and the bench is much thinner than the org chart wants to admit.

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About The Author

Lawrence (Larry) Coval didn’t study leadership from the outside. He lived it for nearly four decades. He started at the bottom, worked his way up, and spent years leading large organizations, managing significant revenue, and being accountable for hundreds of people at a time.

At 23, he was handed a leadership role he wasn’t ready for, and he knew it. That experience shaped everything that followed. Instead of relying on theory, Larry learned through real outcomes, real pressure, and real consequences.

Over time, he developed a simple, unforgiving standard. His job was to make his people successful. If they won, he won. Simple, but not easy.

Today, Larry brings that same operator mindset to his work, cutting through conventional

leadership advice and replacing it with what actually works in the real world.