AI Transactions: Why Traditional Approaches Fall Short And How To Adapt

Key takeaways

• Transaction structures and terms are evolving, focusing on AI-specific diligence, longer warranty periods and adaptable structures to manage AI risks effectively.
• Post-closing risks can arise from deploying AI in new contexts, leading to potential legal and regulatory issues not identified during due diligence.
• Buyers should prioritize securing data rights and control over AI assets, as ownership alone doesn't fully ensure the ability to adapt AI systems post-acquisition.

Over the past year, artificial intelligence has moved from a diligence consideration to a central driver of deal thesis and valuation in technology transactions. This shift is not limited to acquisitions of AI-native companies. Increasingly, AI is embedded across products, services and internal workflows, even where the target is not being marketed as an AI business. Market data reflects this trend, with a growing proportion of technology deals now involving an AI