AI Due Diligence: The New Workstream in Every Deal

Artificial intelligence has moved from something a target company mentions in a management presentation to something a buyer actively evaluates as part of due diligence. A few years ago, a reference to AI in a pitch deck was often treated as a forward-looking idea with little impact on how a buyer viewed the business. Today, it can influence valuation in both directions.

If the technology is real and driving measurable results, it can support a premium. If it is more aspirational, or if the company has built its cost structure around tools and technology it does not control, it can introduce risks that a buyer will want to understand before committing to a price. As a result, AI has effectively become a new diligence workstream alongside financial, tax, and legal diligence.

Start With What the Business Actually Owns

The first step is separating what the business actually does with AI from what it says it does. Many companies describe themselves as AI-enabled when, in reality, they license a third-party model and have built their own interface or application around it. That is not necessarily a problem. In the middle market, it is often the most practical approach. But it changes how a buyer should think about what makes the business different from its competitors.

The key question is what the company actually owns. Does it have proprietary data, models, or workflows that would be difficult for a competitor to replicate? Or does its advantage come primarily from being an early adopter of technology that is now widely available?

That distinction matters because it can affect whether revenue growth is sustainable or whether margins could come under pressure as competitors catch up.

Look Beyond the AI Revenue Story

Once a buyer understands what sets the business apart, the next question is whether the revenue associated with AI is as strong and sustainable as it appears. This is where AI diligence begins to overlap with traditional quality of earnings analysis.

When a company has launched an AI product or module, the revenue it generates deserves the same scrutiny a buyer would apply to any other new revenue stream. Is it contracted or based on usage? Are customers renewing after the initial term, or was early adoption driven by curiosity and budgets that may not repeat? Is the pricing sustainable, or was it designed to encourage initial adoption?

In some cases, the revenue is genuinely recurring and may support a higher multiple. In others, it may look recurring but has not yet been tested through a full renewal cycle. A buyer paying a premium for AI-driven growth needs to understand which situation it is buying into.

Understand the True Cost of AI

Revenue is only one side of the equation. The underlying cost structure is often easier to overlook.

The costs of running AI models are real, they increase with usage, and they do not always appear where a buyer would expect to find them. In many businesses, these costs are recorded as operating expenses even though they function more like a direct cost of delivering the product or service. This can distort gross margins and make the business appear more scalable than it is.

That becomes particularly important when a company is growing quickly. Usage-based costs can increase faster than revenue, particularly if pricing was established before the company fully understood the cost of supporting greater usage.

Part of the diligence process is identifying these costs accurately, understanding the contractual terms with technology providers, and determining whether margins are likely to hold as the business scales. Dependence on outside vendors also matters. If a product relies heavily on a single AI provider, a buyer will want to understand the pricing and renewal terms, the risks associated with that relationship, and what it would take to move to another provider if circumstances changed.

Consider the Risks Behind the Technology

Beyond revenue and costs, AI introduces risks that can be harder to quantify but are increasingly important in a transaction.

Buyers want to understand what data was used to train or operate AI models, whether the company has the appropriate rights to use that data, and whether customer information has been handled in accordance with contractual commitments and privacy requirements.

They will also want to know whether AI is being used in areas where an error could create liability and what level of human oversight exists around those processes.

These issues may not stop a deal on their own, but they can affect how a transaction is structured, including the use of indemnities, escrow, or specific representations in the purchase agreement. As a result, buyers are expanding the scope of buy-side due diligence to gain a better understanding of technology-related risks before closing.

AI Is Also Changing the Diligence Process

While buyers are taking a closer look at how companies use AI, the technology is also changing the way diligence itself is performed.

Analysis that once required weeks of manual work can now be completed more quickly, making deeper diligence economically practical for smaller transactions. That is particularly meaningful in the lower middle market, where certain areas of analysis have historically received less attention because the cost could not be justified relative to the size of the deal.

As that changes, buyers have a greater opportunity to examine areas that might previously have received only limited review.

What Buyers and Sellers Should Take Away

For sellers, the message is straightforward. If AI is part of the growth story, be prepared to support that story with data on adoption, customer retention, pricing, and costs.

For buyers, the stakes are just as clear. AI can contribute to growth and support a premium valuation, but only when the underlying economics, technology, and risks support the story. Understanding what is truly differentiated, what it costs to deliver, and whether the opportunity can scale is becoming an increasingly important part of assessing a business and the value behind it.

As AI becomes more prominent in transactions, having the right diligence approach can help buyers separate opportunity from hype and help sellers better support the value they have built. Our Transaction Advisory Services specialists work with buyers and sellers to evaluate the financial and operational factors that can influence deal value, identify potential risks, and provide greater clarity throughout the transaction process. Contact our team to discuss how we can support your next transaction.