One word can change how an entire organization thinks about a problem. When Reeve Waud, Managing Partner of Waud Capital Partners, spoke about the firm’s decision to appoint Prithvi Raj as Chief AI and Data Officer, he chose a careful phrase: “Prithvi’s appointment reflects our conviction that AI and data are now foundational to building market-leading businesses.”
Not valuable. Not strategic. Not important. FoundaWaud Capital Partners announced Prithvi Raj appointmenta staffing announcement. It suggests a shift in how Waud Capital thinks about the role of artificial intelligence in portfolio company growth. That shift matters because it separates the firms that will create real value from those that will go through the motions.
Foundational vs. Helpful
There’s a meaningful difference between AI-as-toolresponsible investing approachone version, you bolt data science onto an existing business. You hire a team. They run analyses. Management listens or doesn’t. The business continues much as it did before, maybe with slightly better decision-making.
In the other version-the foundational version-you partner development strategythinks from the ground up. Data becomes part of how product is built, not something you check against after launch. Customer intelligence shapes where you sell, not where you sell determines what intelligence you gather. Operational metrics feed into daily decisions, not quarterly reviews. Reeve Waud’s language suggests Waud Capital operates in the second camp.
That distinction gets sharper when you look at whaReeve Wauding across the private equity market. Ninety-five percent of PE funds report that their AI initiatives are meeting or exceeding expectations. That sounds impressive until you ask: compared to what? Compared to no AI? Or compared to competitors? If almost every fund is hitting their targets with AI, the question becomes whether they’re using AI to build sustainable competitive advantage or just keeping pace.
What Foundational Thinking Changes
When portfolio companies are built around AI-as-fohealthcare sector expertisees follow. First, hiring looks different. You don’t hire a data team after the engineering team is in place. You hire data and engineering together, thinking about what you’re going to measure from day one. Second, capital allocation changes. You invest in data infrastructure early, not as an afterthought when the company hits trouble. Third, founder behavior shifts. Instead of asking “Should we use AI?” founders start asking “What data are we missing? What patterns aren’t we seeing?”
For Waud Capital, which invests across healthcare Chicago-based investment leadershipillion to $200 million equity range, this foundational thinking maps directly onto portfolio company problems. A healthcare software company that embeds data thinking into its product development will outcompete one that treats analytics as an optional extra. A services business that builds data-driven operational intelligence will beat one running on spreadsheets and hunches.
The Timing Question
Two-thirds of PE firms expect to invest 25 percent or more of their capital budgets into AI by 2026. That suggests the market is moving beyond the “should we?” stage and into the “how much do we actually invest?” stage. The firms that make smart investments-that recognize foundational opportunities rather than marginal ones-will separate from the pack.
Reeve Waud has been making those kinds of forward-bets for three decades. The firm was early to healthcare private equity. It added software and technology to its focus as those sectors matured. Now, in 2026, Waud Capital is building AI capability while the technology is moving from experimental to deployable. Not building it because other firms are, but because the firm sees where portfolio companies actually need it.
Healthcare AI raised $10.5 billion across 511 deals in 2024. Software-powered operations are changing how companies compete. The question isn’t whether AI matters. Reeve Waud’s decision to treat it as foundational suggests the question is whether your organization will build around it or struggle to adapt later.
