Beyond ROI: Clare Kitching on Reframing AI Investment for Long-Term Advantage

In a recent LinkedIn post, Clare Kitching challenges conventional approaches to funding Artificial Intelligence initiatives, arguing that a narrow focus on Return on Investment (ROI) can obscure the true, long-term value of AI adoption. Kitching highlights a common tension in business investment decisions, contrasting the CFO’s demand for immediate payback with the CEO’s vision for future capabilities.

Kitching points out that traditional AI business cases often begin with the question, “What’s the ROI?” She contends that this question can inadvertently mask the more significant, long-term benefits that AI can deliver.

“For a lot of AI spending, that question hides long term benefits and payoffs.”

Drawing on insights from a Harvard Business Review article by Baba Prasad, Kitching explains that AI investments typically fall into five categories. She emphasizes that only two of these categories should be evaluated using standard ROI metrics. This distinction is crucial for understanding why many organizations are not seeing the expected financial returns from their AI investments.

The ROI Trap in AI Investment

Clare Kitching notes that a significant number of companies are measuring AI initiatives in a way that limits their potential. She cites sobering statistics from McKinsey and BCG, indicating that while AI adoption is widespread, reported impacts on profitability remain low for many organizations.

McKinsey’s 2025 survey, as mentioned by Kitching, found that 88% of organizations utilize AI in at least one function, yet only 39% reported any impact on Earnings Before Interest and Taxes (EBIT). Similarly, a BCG study revealed that 60% of companies investing in AI are not generating material value. Kitching suggests that a key reason for this disconnect is the tendency to measure AI like a standard commodity, rather than recognizing its unique potential.

“Part of those numbers is that we are measuring AI like an even commodity. However, its best value is local, embedded, and specific to your business.”

Kitching argues that the true value of AI is often found in its specific application within a business, its embedded nature, and its ability to adapt locally. This contrasts with a one-size-fits-all commodity approach.

Five Sharper Questions for AI Strategy

To move beyond the limitations of traditional ROI calculations, Kitching proposes that leaders should ask five more strategic questions when considering AI investments. These questions are designed to uncover a broader spectrum of value, including strategic positioning, future options, and capability development.

Strategic Imperatives and Option Value

The first two questions focus on maintaining competitive parity and exploring future possibilities. As Kitching puts it:

“What happens if we don’t? (competitive parity: the cost of falling behind)”

and

“What could this unlock next? (option value: building AI fluency)”

Kitching suggests that these questions help organizations stay in the game by understanding the risks of inaction and the potential for future innovation. This perspective frames AI not just as a cost center, but as a strategic enabler.

Building Durable Advantage

The remaining three questions delve into areas that Kitching believes are critical for building sustainable competitive advantage, yet are often underfunded:

1. Distinctiveness: “Where can this make us distinctive? (embedding AI in what only you do well)” – This focuses on leveraging AI to enhance unique business processes.

2. Data Flywheels: “How does this get better every time we use it? (data flywheels)” – This highlights the importance of AI systems that improve with usage through data accumulation.

3. Capability Building: “What new skills, habits or roles are we building? (capability for long term)” – This emphasizes the development of human capital and organizational readiness for AI integration.

Kitching observes that companies which prioritized these latter three aspects when investing in data over the past decade are now better positioned to accelerate their AI adoption. In her view, these are the areas where true, long-lasting advantage is forged.

Clare Kitching encourages leaders to use these five questions as a filter for evaluating AI business cases and refreshing their AI strategies, moving beyond a simple ROI calculation to a more holistic view of AI’s transformative potential.