Artificial Intelligence is Transforming the M&A Transaction Lifecycle

Artificial intelligence (AI) is fundamentally altering how mergers and acquisitions are conceived, valued, and closed, as Katten writes in a recent advisory. In M&A, AI now functions as an acquisition target, a source of due diligence complexity, a valuation challenge, and a deal-execution tool.

Buyers, sellers, and their advisers must develop new frameworks to address AI-specific risks and opportunities across every stage of a transaction.

Buyers are pursuing targets with proprietary AI capabilities or valuable data sets. At the same time, they are growing cautious about legacy businesses that have not adopted AI. Valuing AI assets is inherently difficult. Technology can become outdated quickly, revenues are uncertain, and buyers and sellers frequently disagree on worth.

Deal structuring mechanisms such as earnouts, equity rollovers, and escrow arrangements are increasingly used to bridge valuation gaps. At the same time, AI raises practical concerns at a transaction’s outset: parties exchanging confidential information risk inadvertent disclosure if recipients use AI tools that incorporate uploaded data into their models. That is prompting the emergence of AI-specific clauses in non-disclosure agreements.

Legal due diligence in AI-driven transactions must assess how AI capabilities were developed, how they are integrated into the target’s products, and what intellectual property, data protection, and regulatory compliance obligations attach. Contractual protections should address ownership, training data, performance representations, and interim covenants to prevent AI asset deterioration between signing and closing. Regulatory scrutiny of AI acquisitions is expected to intensify.

Transactional counsel should build AI-specific due diligence protocols covering technical architecture, data provenance, IP ownership, and regulatory compliance. Deal structuring for AI targets requires careful attention to earnout metrics, interim operating covenants, and representations regarding AI performance. Non-disclosure agreement templates should be reviewed and updated to address AI tool usage and confidentiality risks. Regulatory approval timelines may lengthen as scrutiny of AI-related acquisitions increases globally.