Private equity giant Apollo says the rapid pace of AI disruption is fundamentally complicating how investors value software businesses, even as dealmaking pushes forward through geopolitical uncertainty.
David Sambur, co-head of private equity at Apollo Global Management, sees a growing tension in the markets right now. Software companies were already difficult to price accurately, and the explosion of artificial intelligence capabilities has made that task considerably harder. Speaking with Bloomberg, Sambur laid out the core challenge facing every private equity firm trying to deploy capital into the technology sector: the traditional metrics used to assess software businesses are being disrupted alongside the products themselves.
The private equity approach to software has historically relied on predictable revenue streams, strong retention rates, and defensible market positions. Those fundamentals still matter, but AI introduces a layer of uncertainty that compresses the time horizon for competitive advantage. A SaaS product that looks dominant today could find its core functionality replicated by an AI model in a matter of months, not years. That compression forces firms like Apollo, which manages over $600 billion in assets, to rethink how they underwrite risk in the sector.
Sambur's broader message was that dealmaking does not wait for calm waters. Markets want certainty, and the current environment offers very little of it, from the escalating tensions involving Iran to persistent inflation concerns and shifting monetary policy. Yet private equity firms are not sitting on the sidelines waiting for pristine conditions. As Sambur put it, fortunes are made in volatility, and the firms that can navigate opaque valuations and geopolitical risk are the ones that will generate outsized returns.
This philosophy tracks with Apollo's recent activity. The firm has remained an active acquirer across multiple sectors, pushing into areas where other buyers have pulled back. The strategy depends on having the conviction and the capital to move when others hesitate, and on building valuation models that account for faster product cycle disruption than the industry has historically seen.
The Software Valuation Problem
What makes AI uniquely challenging for software valuations is the speed at which it reshapes competitive dynamics. In previous technology cycles, enterprise software companies could reasonably expect a multiyear runway before facing serious competitive threats. AI collapses that timeline. OpenAI's GPT models, Google's Gemini, and a growing ecosystem of open-source alternatives are enabling startups and incumbents alike to build features that previously required dedicated engineering teams and years of development. The result is that revenue predictability, the cornerstone of software valuations, becomes a far less reliable proxy for long-term value.
For private equity buyers, this means the due diligence process has to evolve. Traditional analysis of customer concentration, annual contract value growth, and gross margins remains necessary but no longer sufficient. Firms now need to assess how exposed a target's product roadmap is to AI-driven disruption, whether its customer base will remain sticky as alternatives emerge, and how quickly the company itself can integrate AI into its offerings to defend its position. That is a fundamentally different analytical framework, and one that most financial models are still catching up to.
What This Means for Startups and Founders
For early-stage and growth-stage software companies, the message is sobering but actionable. The premium that buyers once placed on steady subscription revenue will likely become more contested as AI tools make it easier to replicate functionality. Startups that can demonstrate deep integration into customer workflows, proprietary data advantages, or network effects that AI cannot easily dislodge will command stronger valuations. Those relying primarily on feature convenience or first-mover timing in a specific niche may find the market less forgiving than it was even two years ago.
The broader private equity landscape is also shifting. After a prolonged period of elevated interest rates that depressed leveraged buyout activity throughout 2023 and into early 2024, firms are sitting on record levels of uncalled capital, often referred to as dry powder. Apollo alone had over $50 billion in unspent private equity commitments as of its most recent earnings report. That capital needs to be deployed, and software remains one of the most attractive sectors for long-term value creation, but the entry points and risk assessments are being recalibrated in real time.
Watch for private equity deal flow in enterprise software to accelerate through the second half of 2025, but expect the terms to reflect heightened caution around AI-driven obsolescence risk. The firms that figure out how to model that risk accurately will have a significant edge over those still applying yesterday's valuation playbook to today's market.
