Use AI to challenge and improve decisions, not just to automate processes.
Key takeaways
As AI commoditizes deal analysis, focus critical thinking on strategy and value capture.
Redesign M&A workflows and structure data to compound learning.
After working almost nonstop for the past month evaluating a critical acquisition, the corporate development team was days away from delivering its final board recommendation. Due diligence was thorough, their financial model looked solid, the CEO was enthusiastic and the seller had set an aggressive deadline.
The day before the upcoming board presentation, someone on the team prompted several frontier AI models with a straightforward request: assume this deal fails in two years and tell us the major reasons why. The models’ responses and subsequent dialog reshaped the conversation entirely.
This scenario is not far-fetched. It is increasingly how savvy deal teams use artificial intelligence, not just to accelerate the process, but to pressure-test their underlying investment thesis.
AI is rapidly becoming a standard part of the mergers and acquisitions toolkit. From scanning the market for potential targets to synthesizing hundreds of documents in a data room, AI-enabled tools are increasingly embedded across the entire transaction lifecycle. Financial modeling and valuation, scenario analysis, contract review, risk identification, the list of AI capabilities continues to grow. Most major private equity firms and sophisticated corporate acquirers continue to deploy and refine these tools.
Here is the essential question: if everyone has access to similar AI tools, where does your competitive edge come from?
The answer is not the technology itself. The value is in how your team uses it to make informed decisions. As AI commoditizes analysis, advantage comes from humans focusing on the activities AI can’t automate: creating and approving the deal thesis, building relationships and redesigning workflows to compound learning over time.
The edge comes from challenge, not confirmation
The strongest deal teams don’t use AI to confirm their instincts. They use it to challenge them. That distinction matters more than most leaders realize.
It is easy to default to “cognitive surrender,” delegating analysis to AI, accepting the output at face value and moving on. When teams do this, they are essentially “falling asleep at the wheel,” letting technology make the decision rather than sharpening the decision-making process itself.
If you are using AI effectively, you are not looking for validation. You are looking for the holes in your thinking. Position AI as a devil's advocate that takes the other side of an argument, raises counterpoints and exposes weaknesses in the deal thesis before capital is committed.
The AI pre-mortem: Pressure-testing before you close
One of the most powerful applications of AI in dealmaking is something most teams are not doing yet in any formal way—the pre-mortem.
Unlike a post-mortem, a pre-mortem assumes the deal has already failed and works backward to understand why, like in our short case study above.
This is where AI becomes genuinely valuable. You can create several AI personas that reflect perspectives from external stakeholders (investors, regulators, customers and suppliers) as well as critical internal players (board directors, sales and marketing, manufacturing and research and development). These perspectives can then tell you how and why the transaction could fall apart. Ask it to identify the weakest assumptions, challenge the synergy case and flag risks that your team may have missed in pursuit of getting the deal done. This approach can surface what a room full of people might hesitate to say out loud. Your team can then restructure the deal in response to these insights.
Consider this: deals sometimes move forward because the CEO wants them done. In these situations, confirmation bias creeps in and can influence decision making. Information that conflicts with the thesis gets ignored because challenging it would mean challenging leadership. That kind of hubris has derailed many well-intentioned transactions. AI, used well, combats that dynamic, not by replacing judgment, but by making it harder to avoid inconvenient truths.
AI-powered pre-mortem: Stress-test your deal
Use AI to challenge assumptions from multiple angles:
Define key stakeholder perspectives. Identify the most important personas and have AI critique the deal from each viewpoint.
Provide deal materials. Use AI to assess the board package, including financials, the investment thesis, synergy assumptions, target metrics and investor communications.
Model failure scenarios. Ask each persona to describe five ways the deal could fail to achieve its objectives over the next two years. For each scenario, request specific recommendations to prevent or mitigate the risk.
Refine the deal. Review the findings and adjust the deal structure, assumptions or integration plans as needed.
Repeat the process. Continue testing and refining until the remaining risks are clearly understood and manageable.
Bottom line: A structured AI-enabled pre-mortem can help surface blind spots early, strengthen decision making and improve the odds of a successful outcome.
AI can be the collaborator that sharpens the conversation
None of this means AI replaces the human element. Far from it.
Relationship-building with founders and target companies, negotiating terms, reading cultural dynamics and maintaining the business’s morale through a divestiture are fundamentally human skills. No model can build the trust needed to be a founder's first call when they are ready to sell. No algorithm will preserve and shape a company's culture through a transition.
The point is not AI versus humans. The strongest outcomes come from thoughtful collaboration between the two. Humans and AI together are better than either one alone. The key is knowing when to lean on the technology and when to trust your instincts, as well as having the self-awareness to recognize when your instincts might be leading you astray.
Speed matters, but AI does not create it alone
In today's increasingly uncertain environment, the ability to move quickly on the right deal is a significant advantage. AI can help teams identify opportunities earlier, analyze more signals faster and prepare to act with greater confidence. But speed is an organizational capability, not a technological one.
Companies still need clear decision rights, aligned leadership and disciplined processes. AI accelerates the preparation, but the ability to act decisively and at the right moment still depends on human readiness.
Smarter decisions start with better questions
AI is already helping deal teams scan, analyze and model. But those capabilities are quickly becoming table stakes. The real advantage will belong to the leaders who use AI not just to move faster through the same old process, but to think more clearly, question and challenge assumptions, highlight risks and strengthen judgment before capital is on the line. The best AI tool in the world will not save a bad decision. But paired with the right judgment, it might just prevent one.
RSM contributors
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Jeffrey GreeneManaging Director
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