AI's primary value in pre-buy research isn't just accelerating diligence on promising ideas. It's about rapidly surfacing deal-breakers—like misaligned management incentives or existential risks—allowing analysts to discard flawed theses much earlier in the process and focus their deep research time more effectively.

AI diligence has replaced cybersecurity as the modern, high-stakes technical hurdle in M&A. Buyers now focus on a company's AI defensibility and roadmap. A lack of a clear AI strategy or a perceived vulnerability to AI disruption can be an existential risk that either kills the deal or severely impacts the valuation.

Due to the nascent and highly specialized nature of AI, VCs find that traditional expert networks are no longer effective for diligence. Instead, they must rely on curated personal networks of deep specialists who can genuinely assess new technologies and teams.

The success of an AI roll-up hinges on effective technology implementation. Therefore, the primary filter for acquiring a company is not just its financials but whether its leadership and culture are genuinely eager to adopt AI and transform their operations. This cultural fit is non-negotiable.

Before GenAI, the key question for seed investors was whether a product created real value. Now, with AI enabling obvious value creation, the primary concern has become defensibility. Investors are now focused on a startup's ability to compete with big tech, incumbents, and foundation models.

When evaluating software loans, Blackstone moves beyond financials to product underwriting. Its investment committee uses a specific scorecard to assess a company's risk of AI disruption, how embedded its product is in workflows, and how its technology stacks up, demonstrating a structured approach to modern threats.

While many firms are just now reacting to AI's impact, major credit investors like KKR have been actively underwriting AI-driven business model risk for nearly six years. This proactive, long-term approach to assessing technological disruption is a core part of their due diligence process, not a recent development.

To avoid post-close surprises and knowledge loss, marry diligence and integration leads before an LOI is even signed. This ensures real-world operational experience informs diligence from the start. The goal is to have a drafted integration thesis by LOI and a near-complete plan by signing, not after closing.

Despite rapid growth, AI-native SaaS companies are seen as more vulnerable to disruption by acquirers. Buyers are wary of the business's long-term defensibility, leading to harder questions and higher hurdles during the M&A process compared to traditional SaaS.