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Commercialising AI: Rethinking Value Creation in Private Equity
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AI is reshaping how private equity firms assess investment opportunities, accelerate portfolio performance and build long-term enterprise value. As the technology becomes more accessible, the challenge is increasingly about understanding where AI can deliver genuine commercial advantage rather than simply identifying what it can do.
That greater selectivity is already visible in the market with EY reporting that the value of tech-focused PE transactions fell 50% in the first half of 2026 compared with the same period last year (1), suggesting investors are applying a higher bar to technology businesses as questions around AI disruption, growth and long-term defensibility become more prominent.
Understanding where AI delivers genuine commercial advantage was a central theme of Codurance's recent London panel discussion, ‘Accelerating Value Creation with AI in Private Equity’, which brought together leaders from across the investment and technology community to explore how AI is influencing portfolio strategy, business performance and long-term value creation.
While the conversation covered a range of opportunities and challenges, three key themes stood out as particularly relevant for investors and portfolio leadership teams.
What this article explores
- Why customer understanding and strong data foundations are essential for lasting value creation
- Why AI must be embedded within the wider value creation strategy
- How AI is reshaping competitive advantage and business defensibility
How Can Private Equity Use Technology to Drive Customer Value?
Because customers pay for solved problems, not for technology. One of the strongest messages from the panel was that portfolio companies need a clear **business strategy, not simply an AI strategy**, with customer value at its core.
While AI is making it easier and cheaper to develop new products and capabilities, innovation alone does not guarantee value. The real opportunity lies in using these advancements to address genuine customer needs, solve business challenges and deliver meaningful outcomes.
For private equity firms, this means ensuring AI adoption is **embedded within the portfolio company's broader business strategy and value creation plan**, rather than pursued as a standalone initiative. The focus should be on how technology can strengthen competitive positioning, support commercial objectives and drive sustainable growth.
The discussion also highlighted how customer-focused pilots can help businesses test ideas, validate assumptions and identify where genuine value exists before committing to wider implementation. Ultimately, the opportunity isn't simply to build more with AI, but to use it to enhance product development, strengthen customer relationships and accelerate value creation.
How is AI changing what makes a software business defensible?
As AI lowers the cost of building software, product features alone are a weaker moat. Sustainable defensibility is more likely to come from proprietary data, customer relationships, integration into critical workflows and domain expertise.
The panel discussed how AI is challenging traditional assumptions about competitive advantage, particularly when assessing the value of software businesses.
As the cost of software development falls, capabilities that once required significant investment may become easier for competitors to replicate. The discussion highlighted how some private equity investors are even using AI-assisted development, often referred to as vibe coding, to rapidly prototype the software capabilities of potential acquisitions and challenge assumptions about their defensibility before investing.
Another approach discussed was “red teaming” both your own business and the competition, deliberately challenging how AI could disrupt existing products and business models while identifying opportunities for new revenue streams.
For private equity investors, this shift makes understanding and articulating a company's true competitive advantage increasingly important, both when evaluating acquisitions and when positioning portfolio businesses for exit.
Why are strong data foundations essential for AI value in portfolio companies?
Because AI initiatives only deliver consistent, measurable outcomes when the underlying data is reliable, accessible and well-governed. While AI is creating opportunities to develop products faster, improve efficiency and modernise existing technology, the panel also highlighted that successful adoption depends on the foundations already in place.
At the centre of those foundations is data. Without reliable, accessible and well-governed data, even the most promising AI initiatives can struggle to deliver consistent and meaningful business outcomes.
For portfolio companies, this means understanding the quality of their existing data, how it flows across systems and whether the right infrastructure is in place to support AI at scale. Investing in strong data engineering foundations can help address these challenges, ensuring data is reliable, accessible and ready to support meaningful AI adoption.
Data foundations were also a key theme at our recent Manchester Digital event, where technology leaders discussed how organisations can scale AI adoption and deliver measurable business value, highlighting why strong data foundations and clear product thinking are essential to achieving sustainable returns.
For private-equity backed businesses, one key trend we’re seeing is that data maturity does not always keep pace with growth. Acquisitions, legacy systems and disconnected platforms can leave information fragmented, which limits the effectiveness of AI adoption. Addressing these challenges early can improve operational efficiency, accelerate initiatives and build stronger foundations for long-term growth and exit readiness.
AI-first software modernisation can also unlock new capabilities and improve existing platforms, but delivering lasting commercial value requires strong engineering practices, data readiness and a clear understanding of the underlying technology.
At Codurance, we see these foundations as essential to helping businesses innovate while maintaining reliability, security and scalability. For investors, this also strengthens exit readiness by ensuring AI investments deliver measurable outcomes without introducing unnecessary complexity or technical risk.
How can AI drive value creation in Private Equity?
The fundamentals have not changed. Understanding customers, building strong technology foundations and identifying sustainable competitive advantages still drive long-term performance. AI changes how quickly and cost-effectively businesses can act on them.
A consistent message from the evening was that while AI is changing how businesses operate and compete, the fundamentals of successful value creation remain largely unchanged.
Understanding customers, building strong technology foundations and identifying sustainable competitive advantages are still central to long-term performance, although AI is changing how quickly and cost-effectively businesses can act on those priorities.
For investors and portfolio leadership teams, the challenge is to look beyond AI adoption itself and consider how the technology can strengthen the underlying business.
Ultimately, the greatest opportunities will come from businesses that put customers first, build on reliable data and connect AI innovation with clear commercial priorities to deliver measurable, lasting enterprise value.
Why choose a software consultancy for AI-driven value creation in private equity?
For private equity investors, understanding where a portfolio company's competitive advantage lies is only part of the challenge. The real opportunity comes from translating those strengths into sustainable growth, stronger operational performance and long-term enterprise value. That means having the right technology foundations, a clear product strategy and the confidence that today's investments will deliver tomorrow's returns.
Codurance works with private equity firms and their portfolio companies to turn technology potential into measurable business outcomes. From assessing technical risk and modernising legacy systems to accelerating product development and strengthening engineering capabilities, we help businesses build the foundations needed to scale, innovate and create lasting competitive advantage.
Whether you're evaluating a new investment, developing a value creation plan or preparing a business for exit, our software craftspeople work alongside your teams to ensure technology supports your commercial ambitions.
Looking to unlock greater value across your portfolio? Get in touch with Codurance to explore how we can help.
Frequently asked questions
How can private equity firms use AI to drive value creation?
By embedding AI into wider value creation plans rather than treating it as a standalone initiative. Opportunities include improving operational efficiency, enhancing customer experiences and identifying new revenue streams that support sustainable growth.
How is AI changing competitive advantage for software businesses?
As AI makes software development faster and more accessible, individual product features are becoming easier to replicate. This places greater importance on proprietary data, customer relationships, domain expertise and integration into critical business workflows.
Why are strong data foundations essential for AI adoption?
Reliable, accessible and well-governed data provides the foundation for AI solutions that deliver consistent, measurable outcomes. Without it, organisations risk investing in capabilities that struggle to scale or integrate with existing systems.
How can AI help private equity firms assess potential acquisitions?
AI-assisted prototyping can help investors test how easily certain software capabilities could be replicated, challenging assumptions about a target company's competitive moat. Combined with technical due diligence, this can highlight potential risks, opportunities and areas for future value creation.
What should private equity firms prioritise when preparing portfolio companies for exit?
Investors should focus on demonstrating how technology investments contribute to commercial performance, competitive differentiation and scalability. Strong engineering foundations, measurable AI outcomes and a clear understanding of potential disruption can help strengthen a company's exit proposition. Codurance’s exit readiness service supports this preparation.
About the Author
As Commercial Director at Codurance, Rob Gray is a strategic commercial leader specialising in partnering with technology-enabled businesses and their investors to unlock enterprise value through AI-driven software transformation and craftsmanship. His expertise spans the entire investment lifecycle, from technical diligence to post-acquisition value creation, helping leadership teams reduce risk and modernise platforms to accelerate commercial performance and secure stronger exit outcomes.