Why AI Makes Talent the Only Durable PE Moat

Key Takeaways

• Michael Bruun oversees private equity at Goldman Sachs Asset Management, where a bench of over 110 operating partners drives operational talent arbitrage across portfolio companies.
• David Weisburd identifies a technological paradox: because specific artificial intelligence tools become obsolete within six months, picking software matters far less than hiring leaders who continuously test and adopt new systems.
• Bruun highlights that autonomous software agents act as extreme force multipliers, enabling a single top operator managing nine agents to match the output of entire traditional departments.
• The private equity moat in a normalized interest rate environment is moving away from software selection toward recruiting executives who operate comfortably amid continuous volatility.

The Software Obsolescence Trap

When every enterprise software product adds natural language interfaces and automated workflows, access to technology ceases to provide an edge. Software becomes a fast-depreciating commodity rather than a durable barrier to entry.

Weisburd frames this dynamic as an organizational paradox: “There's also another paradox which is the faster the technological change, the less the technology matters and the more it's the culture.”▶ 32:35 Committing millions of dollars to custom enterprise tooling often backfires when cheaper, faster models release two quarters later.

“So the question becomes not which AI tool do I implement but which leadership do I implement that will find the AI tool because the AI tools are changing every single day,”▶ 33:10 Weisburd explains. Sponsors who treat artificial intelligence as a static capital expenditure miss the real requirement: recruiting executives who treat tooling as disposable and workflow experimentation as continuous.

The Nine-Agent Force Multiplier

For Goldman Sachs Asset Management, value creation in the middle market requires operational compounding rather than multiple expansion. Bruun points out that technology changes the arithmetic of headcount inside portfolio assets. The gap between an average employee and a top performer expands exponentially once autonomous workflows enter the equation.

“In a weird way, it used to be that a great employee operating a great culture could achieve a lot, but just think about what a great employee with nine agents can achieve,”▶ 33:30 Bruun says. “The war for talent is bigger than it's ever been. Right now, if you can get the right people in with the right change mindset, they can move so much faster because they are AI enabled.”▶ 33:48

This dynamic changes executive evaluation. Sponsors can no longer evaluate CEOs on their static industry experience alone. The deciding metric is cognitive flexibility: “People who understand that the only constant right now is really change and are very comfortable operating in that environment, they are probably the future leaders of these businesses,”▶ 34:48 Bruun observes. In practice, talent arbitrage means finding executives capable of reorganizing operating margins around agent-driven workflows before competitors figure out the staffing ratios.

Why It Matters

In an era of normalized interest rates where multiple expansion can no longer rescue weak underwriting, EBITDA compounding depends entirely on operational speed. As machine intelligence commoditizes technical execution, underwriting risk shifts from technology risk to executive adaptability. Sponsors that build executive networks capable of rapidly absorbing new tools will compound earnings faster, while sponsors betting on fixed software stacks face rapid technological write-downs.