Artificial intelligence is no longer a futuristic add-on for corporate transactions, it’s reshaping how deals are sourced, diligenced, and integrated. For companies engaged in mergers and acquisitions, becoming “AI-ready” isn’t just about chasing efficiency: it’s about safeguarding transaction value, managing regulatory and data risks, and positioning for long-term success.
- Why AI Matters Today in M&A and Commercial Deals
Artificial intelligence is transforming the M&A lifecycle by enabling faster, more informed decision-making. In the early stages, AI can analyze market trends, competitor activity, and financial data to identify attractive targets, while also highlighting potential risks that might be missed by conventional review. Advanced analytics and machine learning models allow deal teams to forecast post-merger performance, simulate integration scenarios, and quantify potential synergies, providing a more precise basis for valuation.
Natural language processing tools reduce the manual burden of reviewing contracts and regulatory documents, helping teams focus on strategic issues rather than repetitive tasks. Beyond the deal itself, AI can monitor performance metrics, operational efficiency, and customer behavior during post-merger integration, supporting quicker realization of value and smoother operational alignment.
2. Legal, Data-Protection and Regulatory Considerations
Deploying AI within corporate transactions demands more than commercial understanding. Legal and compliance teams must review whether data used by AI, particularly personal or sensitive data, has been legitimately gathered, processed, and kept in line with applicable data-protection regulations.
Guidance from data-protection authorities stresses that businesses integrating AI must follow risk-based, transparent and responsible practices, ensuring that models operate fairly, securely and with regard for individuals’ rights.
New regulatory frameworks are emerging in addition to data-related concerns. For instance, under the EU Artificial Intelligence Act (EU AI Act, 19th February 2025), some AI systems would be subject to increased responsibilities, such as human monitoring, transparency, documentation, and accountability requirements, especially if they are deemed to be “high-risk”.
For deal teams, these developments are important even when the parties aren’t based in the EU: where a target’s operations serve or touch EU markets, compliance obligations may follow. That means assessing AI systems, data flows, and regulatory exposure should become a standard part of diligence, not an afterthought.
3. What Being “AI-Ready” Looks Like in Practice
An AI-ready transaction is one where buyers and sellers treat AI as they would any other material asset or liability. Before signing, buyers should seek a clear inventory of all AI models, associated data sets, ownership or licensing rights, historic performance and validation records. Sellers should prepare transparent documentation, including data-provenance logs, training-data inventories and evidence of lawful data collection and processing.
Moreover, governance mechanisms must exist to support ongoing compliance and risk management of AI systems after closing. This includes clarity over who will operate, maintain, and monitor AI tools,especially where those tools affect personal data, drive revenue, or underpin key business operations.
Contracting also needs to reflect AI-specific risks and value drivers. Representations and warranties around data and model provenance, indemnities for data breaches or regulatory non-compliance, and transition or escrow provisions for models and training data become essential when a target’s value is materially linked to its AI capabilities.
4. Conclusion: AI is an opportunity, but only if approached responsibly
AI has the potential to elevate commercial work and M&A activity by improving efficiency, insight and value creation. But unlocking that potential requires more than adopting new tools, it demands clear governance, strong legal foundations and thoughtful integration into existing processes.
Teams that prepare early and approach AI with discipline will gain a strategic advantage. Those that don’t may find that gaps in governance or data practices surface at the worst possible moment. In a rapidly evolving regulatory and dealmaking environment, being AI-ready isn’t optional ,it’s simply good business.
