AI Doesn't Create Value. Execution Does.

Every technology cycle creates its own version of the same debate.

Today it's AI.

The market is saturated with platforms announcing their latest AI capability. New models, copilots, assistants and predictive tools appear almost daily. As a result, AI functionality is rapidly becoming table stakes rather than a source of sustainable competitive advantage. For business leaders, the more important question is no longer whether a platform has AI. The question is whether the organisation can turn AI into measurable business outcomes.

This is where many AI initiatives begin to struggle. Most enterprises do not lack models, algorithms or access to data. What they often lack is the ability to bridge the gap between insight and execution. Predictions are generated, opportunities are identified and dashboards are built, yet turning those insights into operational action frequently proves far more difficult than expected.

Over the last decade, I've seen the same pattern emerge across identity, data collaboration, customer data platforms and retail media. The organisations that create the greatest value are rarely those with the most sophisticated technology. They are the organisations that can operationalise insight quickly and consistently, embedding it into decisions, workflows and customer experiences.

That's why I increasingly believe the most important KPI for AI programmes is execution velocity. As AI capabilities become increasingly commoditised, competitive advantage will shift away from the technology itself and towards an organisation's ability to act on the intelligence it generates. The businesses that create the most value will not necessarily be those with the most advanced models, but those that build the operational, commercial and technology foundations required to execute faster than their competitors.

Technology creates potential, but execution creates value.