The Great AI Divide: Navigating Risk and Disruption in Private Equity

It is clear that Artificial Intelligence (AI) is no longer a future-tense technology; it is a present-day force actively reshaping the entire investment landscape, presenting both profound opportunities and existential threats. 

For private equity firms, AI presents a dual reality: it's a source of profound operational efficiency, but also a primary driver of competitive disruption and margin erosion. To navigate this, we must recognise that the nature of AI risk is not uniform; it varies based on how a business is built and the vertical it occupies.

% of organisations that use AI in at least one business function (Source: McKinsey Global Surveys on the state of AI, 2017-2025)

What This Article Explores:

• The two distinct AI risk profiles affecting private equity portfolios
• The difference between AI-native and AI-adapter companies
• How AI is compressing margins across high-risk verticals
• Why brand and legacy positioning are no longer defensible moats
• The strategic shift from software-first to data-first thinking
• How to embed AI risk assessment into your Value Creation Plan (VCP)

The Two Faces of Risk

We see a widening divide between two types of companies, each facing distinct threats:

• For “AI-native” portfolio companies, businesses founded specifically to solve a problem using AI where the technology is the core product, the main threat is algorithmic competition. This means they risk being out-innovated by a rival that develops a superior model, better data, or a more efficient AI architecture. Because their entire business depends on the performance of their AI, the window of defensibility is constantly under pressure.
  
• Conversely, for “AI-Adapter” portfolio companies, integrating AI into existing products and workflows to gain efficiencies, the risk is margin compression and commoditisation. Their challenge is to use AI to defend market share and drive operational improvements, while also capitalising on competitors that are slow to meet customer demand for AI-powered products.
  

High-Risk Verticals and the Erosion of Brand

AI has fundamentally altered the barriers to entry and the pace of competition. The highest risk of disruption is concentrated where AI can automate routine, data-intensive tasks that historically justified premium pricing. In Professional Services, such as legal, accounting, and consulting, AI automates high-value cognitive tasks like drafting, due diligence, and forecasting. This leads to margin compression and disintermediation with smaller firms offering comparable quality at lower cost.

In Financial Services, AI-powered quantitative tools democratise analytics once reserved for large institutions, allowing mid-market players to match institutional-grade insight. We even see impact in Healthcare, where AI models outperform or augment human experts in image interpretation, and in Education, where adaptive learning platforms challenge traditional tuition-based models and alumni-network moats. Competitive advantage can no longer rely on product features alone.

Identifying these risks early is the first step toward building a resilient Value Creation Plan (VCP). At Codurance, we believe the transition from "software-first" to "data-first" is the only way to ensure long-term resilience in a portfolio.

Closing Thoughts

How Codurance Can Help 

If you are assessing AI adoption, preparing for diligence, or strengthening a Value Creation Plan, technology strategy must be directly aligned to enterprise value outcomes.

Codurance partners with private equity firms and their portfolio companies to unlock and accelerate enterprise value through modern technology, while proactively identifying and mitigating technical risk. 

Across the investment lifecycle, we help businesses modernise legacy platforms, implement scalable and resilient architectures, and build high-performing engineering capabilities through Software Craftsmanship. The outcome is faster delivery, lower technical risk, stronger operational performance, and a more resilient, exit-ready asset.

If you'd like to find out more, get in touch with us today. 

Frequently Asked Questions

1. What is AI risk in private equity?

AI risk refers to the impact AI can have on a portfolio company’s competitiveness, margins, valuation and long-term defensibility. It includes algorithmic disruption, commoditisation, operational dependency risk and technical debt exposure.

2. What is the difference between AI-native and AI-adapter companies?

AI-native companies build AI as their core product. AI-adapter companies integrate AI into existing products to improve efficiency or customer value. Each faces different competitive and margin risks.

3. How does AI affect private equity valuations?

AI can increase valuations where businesses have proprietary data, scalable architecture and strong engineering capability. It can reduce valuations where AI exposure threatens margins or where technical risk is uncovered during due diligence.

About the Author

Lee Sanderson has over 30 years of experience in software development,
spanning roles from Developer to hands-on CTO, and is a polyglot
programmer with deep experience across modern technologies. He enjoys
helping teams move faster by streamlining development through XP, Agile
practices, and continuous delivery, while maintaining clean architecture
and high-quality code. He also enjoys spending time exploring how AI will
shape the future of software engineering.

Citations 

1. McKinsey Global Surveys (2025). The State of AI: Global Survey 2025 | McKinsey