ServiceNow On Why U.K. AI Maturity Lags Soaring Spend

Summary

U.K. organizations have increased AI spending by 102 percent, yet ServiceNow’s Enterprise AI Maturity Index scores the country at only 51 out of 100. The discrepancy points to a common stage in adoption: most investment has gone into exploratory pilots that test use cases and quantify value, leaving many firms now preparing to move those systems into live operations.

Once AI enters daily workflows, leaders require more than budget and enthusiasm. They need mechanisms to observe system behavior, measure return on investment, restrict data access, enforce policies, and shut tools down when necessary. Adam Spearing, EMEA Head of AI Innovation at ServiceNow, frames governance not as a compliance burden but as the practical foundation that lets organizations retain control and realize expected returns.

Without such controls, risks surface quickly. One client discovered 20,000 AI agents already running inside the business, each created with good intent but outside IT oversight. This “shadow AI” raises immediate questions about data exposure, security posture, and operational accountability.

Data quality presents a parallel constraint. AI systems act on whatever information they receive, without the human tendency to flag anomalies. Organizations therefore need explicit strategies for context, accuracy, and lineage before scaling AI across departments.

A further gap exists between reported use of agentic AI and the ability to run complex, end-to-end processes autonomously. Real progress, Spearing argues, will require companies to redesign workflows around AI capabilities rather than simply layering new tools onto existing silos.

Why it matters

Although focused on the UK, the article addresses universal challenges in AI governance, shadow AI, and data security that are highly pertinent to Dutch security and privacy professionals. It provides actionable insights on establishing visibility and control as organizations move AI from pilot to production.