AI deployment assumptions in M&A due diligence
Abstract
AI-driven revenue projections are increasingly treated as diligence items rather than narrative colour. This paper examines how acquirers and their advisors are beginning to evaluate the decision quality underlying AI-dependent valuation assumptions, and why the evidentiary standard has shifted from technical plausibility to institutional defensibility.
AI is rarely presented in transactions as a discrete asset with clearly bounded risk. Instead, it is embedded within growth narratives that assume successful deployment, adoption, and regulatory durability. Margin expansion, underwriting precision, operational leverage, and new product lines are frequently justified on the basis of AI capability without explicit examination of the decisions that underpin those assumptions.
As AI becomes material to valuation, this implicit trust is eroding. Acquirers are increasingly interrogating whether AI-dependent projections are supported by defensible decision processes rather than aspirational execution plans. The question is no longer whether a model can technically perform, but whether the organisation exercised proportionate judgment before capitalising AI into its valuation narrative.
Decision quality has therefore emerged as a diligence object in its own right. Sophisticated buyers assess whether AI initiatives were subjected to structured pre-commitment review, whether downside and irreversibility were considered alongside upside, whether accountability existed to halt or materially modify the initiative, and whether assumptions were explicitly documented prior to commitment. Where this evidentiary record exists, AI-driven value is treated as conditionally credible. Where it does not, that value is discounted or restructured.
Transaction consequences follow predictably. AI-related upside is shifted into earn-outs, valuation is adjusted to reflect contingent rather than underwritten value, and post-close governance rights are expanded to manage inherited uncertainty. These outcomes are not driven by technical skepticism; they are driven by the absence of defensible decision records.
As AI becomes a valuation substrate rather than an optional enhancement, M&A diligence increasingly rewards organisations that can evidence disciplined decision governance. Where such evidence is absent, AI-driven value is treated as speculative and priced accordingly.