In Season 4, Episode 7 of the Force and Friction Investor Series, we sit down with Nav Rajput, Managing Partner at Active Growth Partners, a private equity firm investing in tech-enabled service businesses and industrial technology platforms.
Nav shares how the investor lens on M&A is evolving, from traditional operational efficiencies to a new era of AI-enabled value creation.
He dives deep into how investors are embedding AI at every stage of the deal cycle—from diligence and underwriting to post-close value realization. It’s a conversation that bridges tech investing, operational excellence, and future-ready leadership.
If you’re in M&A, private equity, or thinking about how to scale in a world where AI isn’t just a tool but a growth driver, this episode is for you.
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Here are the core areas we discuss in today's episode:
Nav explains that for modern investors, AI has become embedded in every phase of the deal lifecycle. No longer just an idea or a pilot, AI is now core to how firms like Active Growth Partners source, underwrite, and operate their investments.
“AI isn’t a side project—it’s becoming part of the deal DNA.”
This shift goes beyond efficiency, it’s about using AI to find value in places traditional diligence might overlook. From automating research on customer trends to surfacing hidden patterns in financials, Nav sees AI as table stakes for forward-thinking investment firms.
While many investors talk about AI as a tool to cut costs, Nav believes the bigger opportunity is to drive top-line growth. He shares how Active Growth looks for ways to embed AI directly into the GTM stack of portfolio companies, creating new revenue streams and customer experiences.
“We’re not just looking for AI to cut costs. We’re looking for it to unlock new revenue streams, new business models, and competitive moats.”
Nav sees AI not just as a margin play, but as a lever for creating compounding value post-close, whether through smarter cross-sell or more data-driven pricing.
Tech-Enabled M&A: Predictive Sourcing and Faster DiligenceAI isn’t only about portfolio operations, it’s also transforming the M&A process itself. Nav shares how data-driven sourcing is helping identify companies that align with strategic value, and how AI models can accelerate due diligence while reducing risk.
“Data-driven signals let us move faster and more confidently, even in complex markets.”
This means more precise targeting, faster deal cycles, and ultimately more conviction in the investment thesis, even in high-stakes environments.
Balancing Risk and Innovation in Deal Execution
Nav acknowledges that AI also brings a risk of hype and noise. He talks about how investors must separate real AI opportunities from the buzzwords—ensuring that any AI investment has a clear path to ROI and customer value.
“We’re not here to fund science projects. We’re here to fund real businesses that can use AI as an accelerant.”
For Active Growth, this means rigor around where and how AI gets deployed—focusing on real-world impact and long-term defensibility.
From Efficiency to GTM Acceleration: AI in Portfolio Operations
Post-close, Nav sees AI as a game-changer for revenue growth—not just internal efficiency. He explains how AI can inform customer segmentation, identify the best-fit go-to-market motion, and even forecast churn risk with more precision.
“AI gives you sharper customer insights, not just back-office efficiency. That’s where the compounding growth really starts.”
He frames this as a new era of portfolio management—where the goal isn’t just to maintain margins, but to unlock new pathways to growth and market leadership.
Final Thoughts
Nav Rajput’s perspective is a timely reminder that AI is no longer optional—it’s foundational. For private equity leaders, GTM strategists, and portfolio operators, the takeaway is clear: using AI to automate is only the start.
The real differentiator is using it to create new revenue pathways, smarter customer journeys, and stronger exit stories.
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