The AI returns gap: McKinsey data reveals rising spend, flat earnings

Four years into the generative AI boom, the long-awaited return on investment remains largely aspirational. A global survey of business leaders from McKinsey finds that while corporate conviction in AI is stronger than ever, the technology’s contribution to the bottom line is not growing. The consultancy’s ‘State of AI in 2026’ report, which canvassed 1,719 professionals, shows that the proportion of organisations attributing any earnings before interest and taxes (EBIT) impact to AI use has not changed since its 2025 survey. This stagnation comes despite firms planning to increase their AI investments and a growing belief that the technology will fundamentally reshape their industries within three years.

The data paints a frustrating picture for finance leaders. While 80 per cent of employees using AI report that the technology has improved their individual productivity, these gains are not accumulating at the enterprise level. The number of ‘AI high performers’—organisations that attribute at least five per cent of their EBIT to AI and describe its impact as significant—has remained stuck at a meagre six per cent of respondents for the second year running. This disconnect suggests a systemic failure to scale benefits from the user’s desktop to the company’s profit and loss statement, a classic implementation gap that lands squarely in the CFO’s purview.

This returns gap is compounded by escalating costs. One in five respondents admitted that AI-related operating expenses have already constrained their use of the technology. Furthermore, the report highlights a growing expectation of AI-driven job cuts, with 39 per cent of respondents anticipating workforce reductions in the coming year, up from 32 per cent in 2025. Yet, McKinsey’s own data from the previous year showed that actual job cuts fell well short of predictions, suggesting that replacing human labour with AI is proving more complex and less financially certain than many leaders hope. The narrative of AI as a simple cost-saving tool is being challenged by the reality of high operating expenditure and elusive headcount synergies.

For the CFO, the report is a call to action for greater financial discipline. The era of speculative, faith-based AI investment must give way to a rigorous, data-driven focus on value creation. The challenge is no longer about whether to adopt AI, but how to deploy it in a way that generates a measurable financial return. This involves moving beyond anecdotal productivity stories and demanding that every AI initiative is underpinned by a robust business case with clear, trackable financial metrics. The C-suite can no longer afford to treat AI as a magic wand for efficiency; it is an expensive and complex capability that requires the same financial scrutiny as any other major capital investment.