In software M&A, we’ve seen a new question arise as a critical part of buyer decision making:

Does this business become more important in an AI-driven market or less?

While AI has been increasingly important for a couple of years now, this question has become more urgent since the new LLM models landed late last year. It is now a fundamental part of how buyers assess risk, strategic fit and valuation.

The net result of this for M&A is that software assets are no longer being assessed only on traditional standalone metrics. Growth, margins, retention and market position still matter, but on top of this buyers are digging into whether AI is a tailwind strengthening the company’s future or there is a credible risk that the company’s role will be weakened, bypassed or commoditised. We are seeing that AI is not just part of the product roadmap discussion, it is part of the core investment case itself.

This is no longer a simple “AI-enabled” story

A year ago, many software companies could credibly position themselves as “AI-enabled” by adding copilots, workflow automation or productivity features. That is no longer enough. In the current market, buyers are segmenting software businesses into broadly three groups:

• AI-native businesses, where AI is central to the product, user experience and economics. These businesses are attracting the highest valuations on the basis of expectations of stronger growth potential and strategic scarcity.
• AI-enabled software, where AI materially improves product strength, customer outcomes or economics. This can also be attractive, if AI reinforces the moat.
• Legacy businesses, where AI is weakening differentiation. Core functionality is becoming easier to replicate, competitors could close gaps more quickly, and pricing power is vulnerable and may come under pressure.

The valuation gap between these groups is widening, as discussed in more detail in this report [saasrise.com]. There is a meaningful variation in multiples between AI-native assets, AI-enabled software and more traditional SaaS models, with the latter becoming more exposed over time rather than less.

Valuation is becoming more strategic, not less disciplined

None of this means that fundamentals have ceased to matter. Buyers continue to prioritise predictable revenue, strong retention, profitable and scalable economics and credible market positioning. What has changed is that AI is increasing scrutiny on the quality and durability of those fundamentals.

For example, if growth depends on a seat-based pricing model that may come under pressure as customers automate workflows or reduce human inputs, that business model risk will be examined explicitly.

Simply being “AI-enabled” is not enough to support a premium. If a software company owns proprietary context, trusted workflow, regulated or hard-to-recreate data, or a mission-critical system of record, AI can deepen its relevance. Where that is true, AI can accelerate growth and reinforce strategic value. Where it is not, even if you are using AI internally to drive efficiency and productivity, that is now just treated as table stakes.

What is the impact for the buyer?

Another important change is that software acquisitions are being evaluated more explicitly in the context of the buyer’s wider portfolio, not just whether a target is attractive on its own. There is strong demand for AI-related M&A being driven by the urgency to acquire capability, data, talent or defensible positions faster than they can be built internally.

A software company may be strategically more important than its standalone metrics suggest if it solves a real portfolio problem for the buyer by upgrading product capability, defending customer relationships, accelerating AI readiness or future-proofing parts of their portfolio that may otherwise be exposed.

On the other hand, even a software business with respectable current performance may struggle with M&A unless there is a convincing story that its position will not be eroded in an AI-driven market.

Founders need a compelling AI equity story

For founders and their investors preparing for a company sale, the AI narrative needs to be convincing and compelling in order to get a premium outcome.

It is no longer enough to say that the product incorporates AI or that the team has an AI roadmap. Buyers increasingly want clear answers to questions such as:

• How does AI improve customer outcomes in a measurable way?
• How does it strengthen retention, expansion or pricing power?
• How does it improve margins or alter or accelerate the revenue model positively?
• Does the business control proprietary context, workflow or data that becomes more valuable in an AI world?
• How defensible is this as AI models continue to advance rapidly

Bottom line

AI is not an innovation overlay in software M&A. It is increasingly a lens through which buyers assess strategic fit and value.

The companies most likely to get a strategic premium in an exit process will be the ones that can show that AI makes them more embedded, more defensible, more important in the customer workflow and harder to displace, not the ones that have simply added AI features or have plans to do so.

At FirstCapital we advised on one of the early AI deals in Europe, the sale of Bloomsbury.ai to Meta. One of the co-founders of that business, Tim Rocktäschel has recently co-founded Recursive and raised $650mn from GV, Greycroft, Nvidia, AMD and others. There are some incredible AI businesses being founded in Europe, and there’s great demand from buyers and investors for the right opportunity. Anthropic, SpaceX and OpenAI are all likely to list in the coming months at eye-watering valuations, highlighting investor demand. Come and talk to us if you’d like to take advantage of these market conditions.