More Than Half of PE Firms Are Hiring AI and Data Talent, EY Finds
EY's Private Equity Pulse survey finds 53% of firms hiring more digital transformation specialists and 51% adding data scientists, as technology moves from a diligence checkbox to a lever across the entire deal lifecycle.
NEW YORK, August 17, 2026. Technology has become a core differentiator in private equity rather than a back-office concern, and the hiring data backs it up. According to EY's latest Private Equity Pulse survey, 53% of firms are hiring more digital transformation specialists than in prior years, and 51% are seeking more data scientists and AI experts. Both figures point in the same direction: firms that once treated data science as a portfolio-company problem are now building that capability in house.
Technology Is Touching Every Stage of the Deal
The shift shows up across the full deal lifecycle, not just in a single function. In sourcing, firms are using automated screening and unstructured data analysis to spot mispriced assets before they surface through traditional deal channels. In diligence, the same tools are compressing timelines: risk identification, market mapping, and financial validation that used to take analyst teams weeks can now run in the background as an early filter. Inside portfolio companies, the emphasis has moved from advisory recommendations to direct value creation work: pricing analytics, working capital optimization, and process automation are now standard parts of the operating playbook rather than options on a slide. And on the way out, sponsors are leaning on predictive modeling to forecast performance and identify windows for an earlier, cleaner exit.
The War for a Rare Kind of Talent
Building that capability has run straight into a hiring problem. Firms are chasing what recruiters have started calling the unicorn candidate: someone with genuine financial fluency who can also ship AI tools hands-on, a combination that is far rarer than either skill on its own. Even where firms land that hire, the technology often runs ahead of the data it needs. Poor data quality and fragmented infrastructure across portfolio companies remain the practical ceiling on how far advanced AI agents can actually be deployed, regardless of how sophisticated the model behind them is.
What is notably absent from the EY findings is any sign that firms are hiring technologists to replace investment judgment. The stated goal across the survey is augmentation: faster feedback loops and sharper inputs for the people making the call, not a substitute for them. For an industry that has spent the past two years debating how much of its work AI will eventually take over, that is a more measured answer than the hype cycle usually allows.