Definition
An AI Exposure Assessment evaluates material revenue streams and workflows for supported benefits and risks: realizable cash savings, incremental revenue contribution, pricing pressure, substitution, vendor and oversight cost, rights, dependencies, and implementation needs. It distinguishes outcomes already in earnings, unproven seller improvements, and buyer-created synergies. An AI label or sector classification does not establish a premium or a displacement forecast.
What it means for you
Show what customers pay for, what the workflow delivers, its full cost and failure rate, who retains the benefit, and whether the buyer can use it after close. Keep unsupported upside outside the base case.
The buyer’s lens
Does the evidence change standalone earnings, the forecast, investment, buyer-created value, or willingness to acquire? Test capability, economic capture, and transferable rights separately.