Evaluating Different AI Strategies for Post-Investment Oversight Post-investment monitoring has become increasingly complex as portfolio companies scale and LPs demand more frequent, granular reporting. The traditional quarterly board meeting model leaves funds reacting to problems rather than preventing them. AI offers multiple approaches to this challenge, but choosing the right strategy depends on your fund size, portfolio composition, and existing data infrastructure. This comparison examines three distinct approaches firms are deploying today. The application of AI in Private Equity portfolio management isn't one-size-fits-all. A $500M growth equity fund with fifteen active positions faces different challenges than a $5B buyout fund with five platform companies and forty add-ons. Understanding the tradeoffs between centralized AI platforms, point solution tools, and custom-built systems helps you select an approach that matches your operational reality rather than aspirational architecture diagrams.…