Lee McCabe Critiques Corporate AI Adoption: ‘Buying AI’ vs. ‘Doing AI’

In a recent LinkedIn post, Lee McCabe critically examines the current state of Artificial Intelligence adoption within corporations, arguing that many businesses are merely purchasing AI solutions rather than genuinely integrating and utilizing them. McCabe contends that this approach has led to significant wasted investment and a failure to realize AI’s transformative potential.

The ‘Corporate Theatre’ of AI Adoption

McCabe opens by drawing a sharp distinction between ‘buying AI’ and ‘doing AI,’ framing the former as a common but ultimately ineffective strategy. He cites findings from Deloitte’s latest State of AI report, which indicates a substantial increase in AI access among workers, yet a surprisingly low rate of actual daily workflow integration. This gap, McCabe suggests, highlights a widespread issue of unused enterprise licenses, turning a potentially revolutionary technology into another underutilized corporate asset.

“So we have managed to turn the biggest technology shift in years into another unused enterprise licence.”

Further elaborating on this theme, McCabe points to the discrepancy between AI experimentations and production deployments. While a significant portion of companies have AI experiments, fewer than 60% have moved a substantial amount of these experiments into production. He notes the common corporate tendency to forecast future success, stating,

“Only 25% of companies have moved 40% or more of their AI experiments into production, but 54% expect to get there in the next three to six months. Of course they do. Every bad strategy meeting ends with “next quarter will be transformational.””

AI’s Limited Impact on Revenue and Job Redesign

A key point raised by McCabe is the disconnect between the perceived benefits of AI and its current impact on company revenue. According to the Deloitte report, a vast majority of companies (74%) hope AI will increase revenue, yet only 20% report that it is currently doing so. McCabe argues that this suggests many firms are using AI to marginally improve existing processes rather than fundamentally changing their business models.

This lack of fundamental change extends to job roles and workflows. McCabe highlights that 84% of companies have not redesigned jobs around AI. He uses a striking analogy to illustrate his point:

“Just added a tool and called themselves innovative, which is a bit like buying a Peloton and announcing you’re an athlete.”

As McCabe sees it, true innovation requires more than just acquiring new technology; it demands a strategic rethinking of how work is done and how roles are structured.

Governance, Agentic AI, and Sovereign Concerns

The article also touches upon the emerging risks associated with agentic AI. McCabe expresses concern that a significant majority of companies plan to deploy autonomous AI agents within two years, despite a low percentage having mature governance structures in place. This, he warns, could lead to accountability issues when autonomous systems make errors.

Additionally, McCabe points out a growing trend relevant to private equity firms: the increasing importance of the country of origin in AI vendor selection. He notes that 77% of companies now factor this into their decisions, indicating that the concept of ‘Sovereign AI’ is becoming a commercial imperative, challenging the assumption that software is borderless.

The Path to True AI Value Creation

In conclusion, Lee McCabe asserts that the true winners in the AI race will not be those with the most pilot projects or the most public pronouncements about AI adoption. Instead, he argues, success will come to companies that focus on redesigning work, establishing robust governance frameworks before scaling, and genuinely leveraging AI to alter their business economics.

McCabe’s analysis suggests that many companies are currently mistaking participation in the AI discourse for tangible value creation, akin to merely attending a conference rather than implementing its outcomes.