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New Diligence Challenge: Uncovering AI Risks and Opportunities

🔗https://www.bain.com/insights/new-diligence-challenge-uncovering-ai-risks-and-opportunities/?utm_source=substack&utm_medium=email


1. Introduction


In today’s M&A and private equity world, assessing a target company means more than just looking at revenues and costs. The article argues that evaluating the impact of AI is now a core diligence task.


Buyers and investors are increasingly asking: How will AI reshuffle risk and opportunity in the business we’re about to acquire? This shift means that due diligence isn’t just checking boxes—it’s thinking about how the business model, cost structure and competitive dynamics might change because of AI.


2. What type of AI risk and opportunity do we see in diligence?


According to Bain, a key step is to map where the target sits in relation to AI’s impact. They define three categories:

  • Revolution: refers to companies where AI can totally upend the business model. The target may operate in a domain where AI tools or platforms can render the current model obsolete—think translation services, outsourced customer support, or other roles where generative/automated AI can replace large swathes of the value chain. In those cases survival often means reinventing the product or service from the ground up.

  • Transformation: in this category the business model isn’t dead yet—but it requires significant change. The company needs to invest in new processes, data, technology, training: in short, to adapt the way it operates. For example, in healthcare, AI can increase speed and accuracy of diagnosis—but capturing that value requires investment and re-thinking of services. It’s about both opportunity (new revenue streams, efficiency) and risk (falling behind, market share erosion) if you wait too long.

  • Augmentation: most companies fall into this bucket. Here, AI isn’t about reinventing the business model; rather it's about doing existing things better—unlocking cost savings, efficiency gains, enhanced customer experience. These companies still have value in their current workflows, but need to adopt AI to maintain competitive advantage and resist being commoditized.


3. Five key questions you should use to assess AI’s impact on a target


To make this evaluation actionable, five questions should guide diligence:

  • Will the business model be upended?. The first question asks directly whether AI could fundamentally disrupt the target’s business model. For example, if the business is content creation and AI is already generating compelling text, graphics or video, then the business may fall into the Revolution category. If yes, the investment thesis must account for either radical change or walk-away risk.

  • Will market volumes be affected?. The second question is whether AI will change market demand, pricing, volume. For instance, if a company sells seats of software and AI reduces the need for human seats (e.g., paralegals in law firms), the pricing model could be under threat. Understanding how AI shifts the cost structure and customer willingness to pay is key.

  • Will the basis of competition change?. The third question explores whether AI will shift the competitive moats and what defines winning in the future. If the target’s advantage is in data, workflows, service and AI reduces those barriers, the competition could change dramatically. The acquirer needs to ask: are we competing tomorrow with the same rules as today? If not, who will win under the new rules?

  • What improvements to the product offering are possible?. Question four looks at upside: What new product, service or feature opportunities does AI unlock? Can the target use AI to reach new users, justify higher pricing, or extend its offering? It’s one thing to defend the core, another to use AI to expand it and capture additional value.

  • Will there be meaningful cost savings for the business?. Finally, the fifth question asks whether AI offers meaningful operational or cost advantage. For example, many tasks—knowledge work, repetitive processes—may be augmented or replaced by AI, leading to potential savings. But you must evaluate if the target has many similar tasks, sufficient scale, and a willingness to invest to capture savings.

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