Due diligence assesses what is visible before closing. The most costly AI dependencies emerge after. When it is too late not to inherit them.
Post-acquisition AI risk refers to all dependencies, obligations and exposures linked to a target's AI systems that are not visible in due diligence and emerge during operational integration: non-reversible vendor dependencies, inherited regulatory obligations, architecture conflicts, exposed data.
Many post-acquisition AI risks are not surprises. They are elements that classic due diligence does not look for, because it is designed to assess value, not to map future dependencies.
An acquisition does not give you control. It exposes you to dependencies you do not yet master. The real risk of an acquisition is not what you see. It is what you inherit without understanding. You are not only buying a company. You are inheriting its dependency architecture.
Beyond traditional assets, a 2025-2026 acquisition exposes you to: the AI architecture deployed in operational processes, unanalysed AI vendor contracts with change-of-control conditions, proprietary data exposed to third-party models, inherited EU AI Act obligations if high-risk systems are deployed, and operational shadow AI that the target may not itself know about.
Unanalysed AI contracts, change-of-control conditions, dependency on specific APIs or platforms.
Target's proprietary data circulating in third-party models, creating irreversible asymmetry.
High-risk EU AI Act systems deployed without compliance, with obligations transferred to the acquirer.
Undocumented AI usages in teams, exposing proprietary data without control.
Incompatible or redundant AI systems making integration more costly and slower than planned.
The first 90 days post-closing are the critical window to map inherited AI dependencies, assess regulatory obligations, and decide which systems to integrate, replace or exit before irreversibilities form.
We map inherited AI dependencies in the first 90 days. Exclusively general management.
let's talk