In a recent LinkedIn post, Lee McCabe critiques the prevailing approach to Artificial Intelligence (AI) strategy within private equity (PE) portfolio companies, arguing that many organizations mistake purchasing tools for developing genuine strategies.
McCabe highlights a common scenario where portfolio companies are pressured by boards to present an AI strategy, often leading to superficial solutions. He states:
“Most PE portfolio companies do not have an AI strategy. They have an answer for the board. That is not the same thing.”
According to McCabe, the pressure to demonstrate AI adoption results in companies acquiring chatbots, copilot tools, or basic workflow automation. He characterizes these acquisitions as mere shopping rather than strategic planning.
The Real Foundation: Data, People, and Processes
McCabe contends that the fundamental question for any PE-backed company considering AI should not be about the tools, but about its foundational readiness. He elaborates on the critical underlying elements:
“Does the business have clean enough data to do anything useful with AI. Does it have the people who understand where AI can actually improve execution. Does it have processes that are stable enough to automate without industrialising the chaos. Does it have systems that talk to each other. Does it even trust its own reporting.”
He points out that many businesses struggle with basic data hygiene, such as maintaining clean CRM data or accurate sales forecasts. Attempting to implement AI on top of such shaky foundations, McCabe argues, is unlikely to yield transformative results.
The Pitfalls of ‘AI as a Feature’
The core of McCabe’s argument is that the conversation around AI in private equity is often framed incorrectly. He observes that AI is frequently treated as a purchasable feature that can be added to a suboptimal operating model to create an illusion of modernity.
“AI gets discussed like a feature you can buy. Something you can bolt onto a mediocre operating model and somehow emerge looking modern. You cannot,” McCabe asserts.
He warns that without robust data, sound processes, and adequate talent, AI implementation can lead to amplified confusion rather than value. The true beneficiaries of AI, in McCabe’s view, are not those who make the loudest pronouncements but those who invest in the essential groundwork.
The ‘Boring Work’ for Real AI Value
McCabe emphasizes that achieving genuine value from AI requires diligent, often unglamorous, preparatory work. This includes:
- Cleaning and organizing data.
- Rectifying broken workflows.
- Properly instrumenting business systems.
- Hiring individuals capable of linking technical AI capabilities with commercial objectives.
- Developing an operating model that can genuinely support intelligence.
He clarifies that this approach is not anti-AI but rather the only serious and sustainable way to leverage its potential. Until these foundational issues are addressed, McCabe concludes, most so-called AI strategies are merely performative.
“Until that is fixed, most AI strategy is just theatre with better branding.”
By focusing on these fundamental operational improvements, companies can build a solid base upon which AI can deliver tangible business outcomes, rather than simply adding a veneer of technological advancement.
📝 About This Content
This article is based on insights shared by Lee McCabe on LinkedIn.
📅 Originally posted on April 21, 2026 | View original post on LinkedIn →