Steven H. Nigro: How AI Is Rewriting the Playbook for Modern Investment Banking
Steven Nigro has experienced innovation in his career. Fax machines transmitted hand delivered documents, spreadsheets and mail became electronic, cell phones extended the business day to 24 hours, and the internet created a worldwide web of resources and communication. He graduated from college in 1982, spent four decades in finance and investment banking, and has watched each successive technology wave reshape how deals get done. None of them, in his view, comes close to what is happening now. Nigro, an investment banker and board director with decades of mergers and acquisitions (M&A) and capital raising experience, is not describing artificial intelligence (AI) as a disruption to his profession. He is describing it as something more significant, changing not just the speed of banking but its fundamental approach. “I don’t look at it as a disruption,” Nigro states. “I look at it as a transformation, and nothing will be as transformative as this.”
The Process Has Been Compressed. Every Part of It
The investment banking process, including origination, analysis and documentation, marketing, receiving and evaluating offers, and closing, has always been time-intensive at every stage. Research that required weeks of analyst hours to produce a credible conclusion now takes minutes. Document comparison that once consumed an afternoon is now a 10-minute task.
Nigro describes completing a comparison of a three- to four-page letter of intent against a 200-page purchase agreement on an Amtrak trip to Washington, D.C., identifying the differences. Typically, that time-consuming analysis was followed by communicating the differences to attorneys to incorporate into the applicable definitive documentation. But Nigro went further, asking the AI to draft the missing contractual provisions, and it did so complete with cross-references to other sections and relevant definitions. The competitive advantage was real, but he knew it was temporary. “Once competitors adopt the same tools, falling behind becomes the risk for those who don’t,” he reflects.
The applications extend well beyond document analysis. Nigro recently used AI to generate a management discussion and analysis (MD&A) from a set of financial statements, a task he once had to teach junior analysts to perform manually. Sitting alongside an analyst as they worked through it together, Nigro found himself in an unfamiliar position: the elder banker urging the younger professional to lean into the technology. “Normally it’s the other way around. The junior person is the one pushing the senior person to adopt the new tool,” he observes. This time, the roles were reversed, and the AI produced the narrative faster and more precisely than traditional methods would have allowed.
The Triangle Is Becoming a Diamond
The traditional investment banking hierarchy is shaped like a triangle, with a wide base of analysts performing the production work and a narrow tip of senior bankers owning client relationships. Nigro believes AI will reshape that into something closer to a diamond, elevating analysts and associates into roles requiring greater judgment, issue identification, and decision-making rather than mechanical execution. He draws the parallel to what happened when paper spreadsheets became electronic. The analysts who once spent hours on manual calculations were freed to focus on analytical review. The profession adapted. It will adapt again, and the adaptation will favor people who can work alongside AI rather than those who simply perform the tasks AI now handles faster.
On due diligence, the implication is already concrete. Nigro queried AI directly on how to improve his firm’s practice and received nine specific suggestions. One stood out: uploading a general ledger, potentially thousands of lines of data, and having AI identify unusual journal entries and potential non-recurring items, generate a time-series profit and loss (P&L), and answer questions about the underlying data. “It put us ahead,” he notes. “And we’re going to invest further in that capability.”
AI Does Not Replace the Banker. It Sits Next to One
Nigro is precise about what AI is and is not in the context of investment banking. In his words, AI is like having the smartest and fastest associate sitting next to him: capable, rapid, and useful. It is still an associate and does not possess the judgment, experience, ability to hand-hold a client through a difficult moment, or nimbleness to respond when a deal goes sideways in a way nobody anticipated. Those qualities remain the irreplaceable value of a seasoned banker. AI makes that banker faster, better-prepared, and more analytically capable, but the client still needs the human at the table.
The profession Nigro entered in 1982 has survived every technological shift it has encountered. The ones who thrived were not the ones who waited to see whether the technology was real. They were the ones who picked it up early, learned what it could do, and adapted their practice around it before the competitive window closed. That window is open now. The bankers who treat this moment as a transformation to engage, rather than a threat to manage, are the ones who will still be setting the terms of the deal, not scrambling to catch up to someone who started two years earlier.
Follow Steven H. Nigro on LinkedIn for more insights on investment banking, M&A advisory, and how AI is transforming the deal-making profession.
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This story was distributed as a release by Jon Stojan under HackerNoon’s Business Blogging Program.
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