A new area is appearing in due diligence: how resilient the business model is to artificial intelligence. Buyers check whether customers could replace part of the company's services with AI tools, whether AI will make it easier for them to bypass intermediaries, and whether the company itself uses AI to cut costs. A risk the owner cannot explain will be priced in, usually against the seller. That is why it is worth assessing before the sale process starts.
Until recently, due diligence focused on finance, legal, tax and people. Today a question beyond historical results comes up more and more often: will this company earn the same in a few years, once customers and competitors use AI as a matter of course?
1. Why do buyers ask about AI?
A company's price largely reflects the value of its future profits. A private equity fund typically plans to sell after a few years and needs the next buyer to pay at least as much. A strategic investor plans even further ahead. If part of the revenue could disappear because customers do something themselves with AI, it affects the valuation today.
It works the other way too. A company that uses AI to cut costs or improve service can show a buyer real potential for higher margins. That supports a higher price, provided it is backed by numbers rather than announcements.
2. Where is the risk highest?
Not every sector is equally exposed. The table below is an indicative assessment based on transaction practice, not the result of a study.
| Area | What may change | Risk to valuation |
|---|---|---|
| Intermediation and distribution | Easier price comparison and direct purchasing from manufacturers, automated buying on the customer's side | Medium to high for pure trading; low where the company provides service, technical advice and product registrations |
| Repetitive office work and knowledge services | Bookkeeping, translation, simple design work, handling enquiries, reporting | High for services billed by the hour |
| Customer service and inside sales | AI assistants take over part of contacts and orders | Medium: mostly affects costs and ways of working, less often revenue itself |
| Manufacturing, service and logistics | AI supports planning and maintenance but does not replace physical work and presence at the customer | Low; more often a chance for higher margins |
In distribution, the key question is whether the company is only an intermediary or adds value that cannot easily be automated: service, technical advice, product registrations, exclusive agreements. See How does a buyer value a distribution company?
3. What do buyers ask in due diligence?
- Share of revenue exposed to AI. What part of revenue comes from work customers could do themselves with AI tools?
- Position towards customers and suppliers. Will AI make it easier for customers to compare offers and buy directly from manufacturers?
- Current use of AI. Where does the company already use AI, and with what effect on costs or sales?
- Plan for the coming years. Is there a realistic implementation plan with costs and expected savings?
- Data. Does the company hold well-organised data of its own on customers, products and processes? This often decides who has the advantage once AI is widespread.
- People. Which skills in the team are hard to replace, and which roles will change most?
- Compliance and security. How does the company protect customer data when using AI tools, and is it prepared for obligations under the EU Artificial Intelligence Act?
“A risk the owner cannot explain will be priced in, usually against the seller.”
4. A self-assessment before the sale
- If my best customer had the best AI tools today, which of our services would they stop buying?
- Do customers pay us for knowledge and relationships, or for working time that AI can shorten?
- Could our manufacturer or supplier use AI to serve our customers directly?
- How much could we cut costs within two years by using AI in administration, order handling and sales?
- Can we show this in numbers, not just in plans?
5. What to do before a sale
- Low risk. Say so clearly in the investor materials. Resilience to AI can support a higher valuation, especially when the company already shows first results.
- Medium risk. Prepare a plan for using AI with measurable results and start delivering it before the process. Buyers pay for results they can see in the numbers.
- High risk. Timing matters here. The company's value may fall before the market notices. Consider starting the process earlier, bringing in a strategic partner to strengthen the business model, or transforming the company before the sale.
In each scenario, it is better to find out now than in the middle of negotiations. Other issues buyers find are covered in Due diligence before a company sale: 10 red flags.
Do you know which part of your revenue customers could replace with AI tools in a few years?
Prepared by Protectimo based on transaction practice. The risk assessment in the table is indicative and does not replace an analysis of a specific company.