Exits aren’t random. They’re the result of foresight, strategic positioning, and timing, especially when the fundamentals of value creation are changing in real time.
That’s what’s happening now. The rise of generative AI is transforming what acquirers care about, what makes a company defensible, and how M&A deals get done.
In a standout session at TechExit.io RBCx’s General Manager, Emerging Ventures, Anush Sachdeva broke down what this transformation means for both founders and strategic buyers, and most importantly: how to adapt.
Whether you’re building to scale or acquiring to grow, these shifts will shape your next move.
Key takeaways:
- Moats are shifting: AI is commoditizing code, data, integrations, and go-to-market now define defensibility
- Deal structures are evolving: Earnouts, usage-based metrics, and regulatory contingencies are becoming standard
- Human trust still drives deals: Despite automation, emotional intelligence remains essential in closing
The path to a successful exit looks different in 2025.
In the age of AI, building a strong engineering team or a slick feature set isn’t always enough. Valuations are shaped by what surrounds your product, distribution, data, trust, and deals are structured with new metrics and risks in mind.
These five shifts offer a real-time snapshot of how tech M&A is evolving and what builders and buyers alike will need to know to stay ahead.
1. The Moat Is Moving: Code Alone Won’t Defend You
“AI is dramatically lowering the costs to build code. Gen tools are sort of eradicating the competitive advantage of having really well-resourced engineering teams.”
In 2025, technical horsepower is no longer rare, and that’s eroding what used to be a major differentiator. Startups can now replicate complex features faster, cheaper, and with smaller teams and internal enterprise teams can do the same.
Now, what becomes valuable isn’t just about what you build, but how embedded you are. Strong go-to-market strategies, critical integrations, and customer relationships that can’t be copied are fast becoming the new moat.
2. Proprietary Data Is the New Gold Standard
As AI tools become widespread, what fuels them becomes the real source of advantage.
“The value of complementary assets will skyrocket… whether it’s NVIDIA or proprietary data assets, the value and the premium you’ll be willing to pay for that is obviously going up.”
While the algorithm matters, the dataset behind it has become far more important. The Microsoft–Nuance deal proves this point. Microsoft wasn’t buying a speech-to-text engine. They were buying access:
“What Microsoft is paying for is proprietary data and deep integrations with EHRs that Nuance had.”
Anush reiterates how Founders should be thinking about data defensibility from day one because Acquirers already are.
3. Workflow Ownership Outperforms Feature Building
Generative AI is pushing software beyond point solutions, and the next generation of tools doesn’t just help you do the work; it does the work for you.
That’s creating a new category of competitive advantage: owning the full workflow.
“If I was building a product today, I would not focus on features… I would ask myself; how do I own the entire workflow?”
Think beyond productivity tools. Think automation, orchestration, and agentic systems that deliver business outcomes, not just functionality.
This also shifts the underlying business model. Anush suggests we may be heading toward usage- or outcome-based pricing as standard in enterprise AI.
4. Deal Structures & Metrics Are Being Rewritten
Valuing companies in this new landscape requires different tools and thinking. Expect fewer large, upfront cash deals.
“What I expect to see a lot more of is milestone-based payouts, revenue sharing, and contingencies.”
Founders need to be ready for performance-linked compensation structures, especially in sectors with regulatory friction or longer-term product validation cycles.
Classic health metrics are also shifting. Take revenue per employee, a beloved SaaS efficiency benchmark:
“AI-native applications… that number is likely going to be high by default.”
With lean AI companies generating millions in ARR with tiny teams, acquirers are recalibrating what scale and efficiency mean. Stickiness, integration, and user outcomes matter more than headcount.
5. The Human Element Still Closes The Deal
Even in a world of AI-accelerated diligence and automated modeling, trust wins deals.
“What makes for a successful deal or helps push it over the line is an exercise rooted in trust… It’s the trust between two organizations facilitated by real people.”
Why? Because no matter how well AI simulates logic, it can’t resolve tension, navigate ambiguity, or align values.
“While AI might be able to mimic reasoning, it will not be able to work through nuanced issues of governance and ethics that we need to consider.”
Buyers still bet on people. Founders still win deals by building credibility, clarity, and alignment. That won’t change, AI or not.
Where This Leaves You
The M&A landscape is being redrawn, and the pace of change is only accelerating.
Founders: Build companies that go beyond features and focus on full-stack value, from data to distribution.
Buyers: Rethink what value looks like and how to structure for uncertainty.
And for both sides of the table: don’t underestimate the power of trust. Because at the end of the day, it’s people (not platforms) who close the deal.
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