Artificial intelligence is now part of almost every conversation in private equity, from deal sourcing to infrastructure to portfolio operations. There’s a lot of activity, but across many portfolios, the actual impact is still limited. After years of working with operating businesses, that’s not surprising. The issue isn’t access to AI, it’s how it’s being used. In most cases, it’s helping with reporting, automating workflows, and trimming smaller costs, but it’s not really changing how decisions are made, how companies operate, or how they grow revenue. Yet. So the results tend to be incremental.
The real constraint is execution. Many companies don’t have operators who know how to implement AI in a practical way, there’s no clear connection to value creation, leadership teams aren’t always aligned, and the right talent is hard to find. What’s starting to emerge is a gap between firms that are building AI into how they operate and those that are still experimenting around the edges. More and more, AI is becoming a signal of how well a business is actually run, whether it can scale, operate without heavy reliance on key individuals, and execute consistently. In that sense, AI doesn’t change the fundamentals. It just amplifies them.