Perspectives

Artificial intelligence has become a stated priority across private equity portfolios. In post-acquisition plans, AI is frequently positioned as a lever for operational efficiency, revenue growth, or differentiation.Despite that intent, most AI initiatives in PE-backed portfolio companies stall after proof of concept.This is not primarily a tooling problem. It is an execution problem rooted in post-M&A operating realities that are often underestimated.‍

Technology due diligence in private equity has improved significantly over the last decade. Most firms now review systems, vendors, security posture, and high-level architecture before closing a deal.

Private equity firms do not evaluate technology partners the way most vendors expect. While diligence conversations focus on tools, platforms, credentials, and prior experience, real evaluation begins after the deal closes, when execution pressure increases and portfolio realities surface.