Evaluating A Software Business in the AI Era

AI is changing how software is built, priced, and defended, but the fundamentals of evaluating a strong software business still matter. In this livestream, you will learn how investors assess software companies when AI is reshaping products, customer behavior, margins, and competitive advantage. We will combine traditional software diligence with the new questions investors must ask in an AI-driven market. We will cover: • How to assess ARR quality, retention, churn, and customer concentration • What gross margin, CAC payback, Rule of 40, and unit economics reveal • How AI inference and data-processing costs affect software margins • The difference between an AI feature and an AI-native workflow • How to evaluate data advantages, switching costs, and workflow ownership • When AI improves pricing power and when it commoditizes the product • How to identify services disguised as software or recurring revenue • The most important AI-era red flags, including model-provider dependence and weak data rights • How to reach a buy, pass, or diligence-further recommendation We will also work through an illustrative software company together and evaluate its revenue quality, retention, margins, defensibility, risks, and valuation. You will leave with a practical framework for separating durable software businesses from AI hype and for discussing software investments more confidently in interviews, case studies, and real deal work. This session is best for candidates pursuing private equity, growth equity, venture capital, investment banking, and technology-investing roles, as well as operators and MBA students who want to strengthen their software-investing judgment.