AI’s rapid advancement has ignited enthusiasm about its potential to revolutionize corporate decision-making by substituting for expensive, fallible humans. But it’s naïve to believe that by gathering ever more data and feeding it to ever more powerful algorithms alone, businesses can uncover the truth, make the right decisions, and create value. We call this false belief “dataism.”

Decisions are not merely exercises in data aggregation and algorithmic analysis. They necessarily involve many additional nuanced elements, such as selecting trustworthy data sources, employing imagination to envision possibilities beyond available facts, and judging the feasibility of solutions. These are areas where humans have innate advantages over machines. Crucially, these involve implicit and often untrained human capabilities.

Consider the case of Kodak and Fuji. Both companies had access to the same data indicating the rise of digital photography, and they evaluated it subject to the same objectives of maximizing growth and profitability. Still, they came to different decisions: Kodak doubled down on its analog products, while Fuji diversified, investing in digital technologies and pursuing other options like cosmetics, which collectively were sufficient to ensure its survival. The same data inspired yet another decision for Sony, which, as a challenger in the market, saw the rise digital photography as an opportunity worth embracing.

This divergence underscores that decisions depend on interpretation, context, and strategic framing — areas where human judgment will remain crucial.