AI is changing mergers and acquisitions. Dealmakers feel the energy, but many still worry about risks. The push for faster, smarter deals is strong. Everyone wants to know how to both use AI safely and stay ahead.
Dealmakers handle sensitive data. A single leak can hurt a business. Security and privacy top the list of concerns. Firms share financial plans, strategies, and private ideas. Protecting this data is not optional. It’s essential. In fact, according to a Datasite survey, 36% of global dealmakers said security and privacy concerns are critical AI adoption obstacles.
Most professionals want strong government oversight for AI. Over 70% of dealmakers in the same survey said they want government oversight of generative AI, underscoring widespread uncertainty about accountability frameworks and regulatory structures. Clear rules help everyone understand what is safe and fair. Without guidance, trust falls, and confusion grows. Rules build confidence and protect all sides. The sensitivity of M&A information, from proprietary financials, strategic roadmaps and confidential business intelligence, means any breach can bring catastrophic consequences.
Change in M&A is nothing new. When virtual data rooms (VDRs) appeared, dealmakers hesitated. They initially saw digital document storage as unnecessarily risky, preferring the tangible security of physical data rooms. Today, VDRs provide indispensable infrastructure, and M&A without them is virtually inconceivable. Technologies which fundamentally improve efficiency, while addressing core industry pain points, eventually achieve widespread acceptance, regardless of initial resistance.
As artificial intelligence continues to transform M&A, industry leaders face both new opportunities and growing challenges. To take advantage of AI in M&A, dealmakers should:
While AI has already made its mark by automating repetitive tasks and streamlining deal processes, agentic AI is taking M&A another step forward. It represents something different – systems capable of autonomous decision-making, adapting to different contexts, and independently adjusting strategy throughout the deal lifecycle.
The evolution goes beyond conventional AI tools that operate on a prompt and response basis. Instead, dealmakers can benefit from the technology’s genuine autonomy, operating as a sophisticated digital team member that retains institutional knowledge and contributes meaningfully to dealmaking workflows. These systems can independently monitor acquisition targets over extended periods, understand a firm’s investment thesis, and proactively evaluate market conditions to bring new opportunities to the surface.
The question then isn’t whether agentic AI will transform M&A, it’s how quickly and effectively participants adapt to, manage, and drive the transformation. The fastest movers with strong safeguards will lead the market. Now is the time to act, learn, and build smarter dealmaking for the future.


