Private market firms have grown dramatically in size and complexity, but many continue to operate on data infrastructure and with data practices that were designed a decade ago. The result is an operating leverage problem. Without change, growth translates into additional people, longer timelines, and greater operational friction.

The firms that pull ahead will treat data as a scalable operating capability. They won't launch broad, abstract data transformation initiatives. Instead, they will identify drag, standardize the definitions and ownership models for those data sets and build use-case-based data foundations that reduce manual data wrangling and streamline workflows.

The same foundation will also shape a firms' ability to adopt AI effectively. As interest in AI dominates across private markets, firms with fragmented, poorly governed date will struggle to generate reliable AI outputs, while firms with trusted data foundations will be better positioned to realize value from AI initiatives.