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Artificial intelligence M&A Startups

The No. 1 Reason M&A Deals Fail Before They Even Start

Illustration of a hand dropping M&A.

I got off a call recently with a very nice and talented founder running a company that had been around for about four years. Solid team, interesting technology, good investors, but still early revenue. Typical of many promising AI companies, two years ago it raised $10 million at a $40 million valuation, even though at the time the company had no revenue. The founder and the company鈥檚 investors are now aiming for an exit that will exceed their previous valuation.

I can definitely understand their logic in wanting a valuation that builds on top of the previous valuation. I also understand that they have strong underlying tech, a good team and the belief that the right buyer would see the potential upside.

And to be fair, there are cases that support this line of thought.

But in the current AI cycle, we鈥檝e seen transactions that look disconnected from fundamentals.

structured a roughly $650 million licensing and talent deal with , effectively bringing in most of the team and its technology. has done similar deals around AI startups, combining technology access with hiring key teams. and others have been active in this space as well.

In rare situations, they can be replicated. When they are, they can lead to exceptional outcomes and everyone involved would welcome that. But they cannot be the working assumption.

The main reason I decide to walk away from a deal is simply because expectations are not aligned with how M&A actually works. If we are not aligned on that from the beginning, I am setting myself up for failure.

Here are the patterns I see most often:

1. Narrative without enough proof

Founders tend to focus on what the company can become. Buyers focus on what has already been demonstrated. Technology and vision matter, but they need to be supported by real signals: Revenue quality, growth, retention and how easily the product fits into a buyer鈥檚 ecosystem all carry weight.

When expectations are built mainly on potential, the gap becomes hard to close.

2. Using exceptional outcomes as reference points

The market always has headline deals that shape perception, especially in AI. While these examples are real, we cannot use them as a baseline.

Most transactions are still priced on traction, growth and strategic fit. When a process is anchored on rare outliers, it is likely doomed to fail.

3. Capital raised vs. commercial reality

When a company raises capital at a certain valuation, it sets a reference point. Founders and investors expect the next outcome to build on that. Buyers look at something else entirely. Current performance and future synergies. If the business has not grown into the expectations created by earlier funding rounds, a gap forms, and it is a gap we need to address.


is a strategic adviser to tech companies and investors, specializing in strategy, growth and M&A, a guest contributor to SA国际传媒 News, and a seasoned lecturer. Learn more about his advisory services, lectures and courses at . for further insights and discussions.

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