AI ambition and reality in Private Equity

What investors need to know in 2026 about AI risk, scale, and defensible value across the PE lifecycle.

AI ambition is reshaping private equity, but operational reality tells a more complex story. This report helps investors assess where AI creates durable value and where it introduces hidden risk.

How to separate AI narrative from operational reality in 2026.

What's inside

Get an evidence-based view of how AI risk, governance, and software quality shape value creation across the PE lifecycle.

  • Why AI ambition is outpacing operational maturity in portfolio companies
  • How to distinguish defensible AI capabilities from commoditized functionality
  • What fragmented global AI regulation means for underwriting and exit readiness
  • The real state of AI-assisted software development and its impact on quality and cost
  • Where AI introduces new security exposures — and how they affect risk pricing
  • Why many AI initiatives stall between pilot and scale

These insights help investors assess AI maturity with greater clarity at entry, steer execution during the hold period, and reduce friction at exit.

Packed with executive perspectives

"AI is now changing the way we do business fundamentally, and reliance on technology increases to previously unseen levels. Yet, no clear oversight exists. So, it’s not a new problem, but AI is increasing it tenfold. Can we trust what is being build, do we invest in the right places, how ready are we for AI? Questions any investor has, and that need a clear answer..."

“AI does not change the fundamentals of value creation, but it does accelerate the exposure of weak product strategy. At Main, we study software companies across markets and increasingly observe a widening gap between ambitious AI narratives and the measurable customer and economic impact they deliver."

“The rules will keep looking different, but our responsibility shouldn’t. I don’t think of regulation as a brake—I think of it as guardrails. If organizations build on a few non-negotiables—ethics, safety, security—and we can show our work with clear data lineage, honest disclosures, and real accountability, they can move quickly in the US, the EU, the UK—wherever—without tripping over themselves..."

AI ambition is accelerating. Operational maturity is not.

What the data shows about AI adoption, quality, and risk in PE in 2026.

of GPs report more than a quarter of portfolio companies are testing or piloting AI.

(Pictet)
0 %
of AI systems score below our recommended build-quality threshold.

(Software Improvement Group)
0 %
more security vulnerabilities found in AI-generated code compared to human-written code.


(Software Improvement Group)
0 X
securities class actions tied to misleading AI-related claims ("AI-washing") in recent years.

(DLA Piper)
0 +

We are Software Improvement Group

Software Improvement Group (SIG) empowers organizations to govern the software their business runs on. Through complete portfolio analysis and tailored strategic advice, SIG helps companies embrace AI with control, improve software quality and security by focusing strategic efforts across people, process, and technology.

Sigrid®—SIG’s software governance platform—analyzes over 400 billion lines of code across more than 30,000 systems and 300+ technologies, offering evidence-based insights to help organizations prioritize and manage their most critical IT initiatives.

Founded in 2000 and headquartered in Amsterdam, SIG has offices in New York, Copenhagen, Brussels, and Frankfurt. The company complies with leading ISO/IEC standards, including 27001 and 17025, and co-developed ISO/IEC 5338—the new global standard for AI lifecycle management.

Combining expert consulting with over 25 years of industry-leading research, SIG is the global authority on software portfolio governance. 

Yellow dots representing SIG branding

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