In late May, OpenAI quietly announced its $6.5 billion acquisition of Io, a little-known but highly technical company focused on model deployment and orchestration. This deal was interesting not because of the size of the deal. It was what the deal revealed.
The most aggressive buyers in AI are no longer chasing novelty. They are chasing infrastructure. As AI shifts from lab to production, the real battle is not about building models. It is about running them at scale โ reliably and securely.
Volume is up, but value is polarized
Across the three half-year periods from H1 2024 to H1 2025, AI M&A volume climbed steadily, reaching 262 deals in the most recent half, Crunchbase data shows. That marks a 35% increase year over year.
On the surface, it looks like a market firing on all cylinders. But the data tells a more nuanced story. The median deal size stayed flat at $67.5 million, while the average soared past $435 million, per Crunchbase data.
That spread is significant. It reflects a bifurcated market. On one end, a small number of strategic infrastructure plays are driving billion-dollar outcomes. On the other, a long tail of smaller, often modest acquisitions is quietly taking place at a steady pace.
That long tail deserves more attention.
These companies tend to be less heavily funded, more capital efficient and focused on solving very specific business needs. Their exits may not make headlines, but they create tangible value for acquirers who need domain expertise, internal automation or edge-case capabilities.
These are disciplined businesses built for sustainability, not spectacle. In many cases, their modest M&A outcomes are not a reflection of failure but a sign of good market fit.
Beyond Big Tech: Strategic buyers step in
While companies such as Nvidia and OpenAI continue to lead in both frequency and deal value, a different class of acquirer is emerging. Mastercard, ServiceNow, Accenture and a growing roster of vertical SaaS players have stepped into the M&A market with strategic intent.
These buyers are not looking for demos or experiments. They are seeking AI that can be embedded, deployed and commercialized inside industries that demand performance and reliability. In sectors like healthcare, legal, financial services and compliance, the startups getting acquired are not pitching bold visions.
They are delivering operational results, often in regulated or high-stakes environments. That makes them highly valuable, even if they fly under the radar.
From novelty to necessity
What we are seeing now is not a trend. It is a reset. AI has matured from a futuristic edge into a commercial foundation. M&A activity reflects that shift.
The startups commanding the most interest are not those with the most powerful models or the flashiest interfaces. They are the ones solving persistent, expensive problems in a way that integrates cleanly into existing systems.
For founders, the lesson is increasingly clear. The real question is not how impressive the tech is. It is how difficult the company would be to replace. Whether the focus is on infrastructure, domain-specific automation or a narrow but mission-critical workflow, the market is rewarding precision and purpose.
These are the quiet wins that will define the next phase of AI.
Itay Sagie is a strategic adviser to tech companies and investors, specializing in strategy, growth and M&A, a guest contributor to Crunchbase News, and a seasoned lecturer. Learn more about his advisory services, lectures and courses at SagieCapital.com. Connect with him on LinkedIn for further insights and discussions.
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