ServiceNow: only 21% see AI returns in Ireland, EMEA

ServiceNow has released research showing a sharp rise in AI investment across Ireland and the wider EMEA region, but only 21% of organisations are generating meaningful returns from that spending.

The findings highlight a gap between strategic ambition and operational delivery. Across EMEA, organisations scored 51 out of 100 for overall AI maturity, up from 34 a year earlier. Leadership, vision and strategy scored 58, while AI-enabled workflows scored 40.

That leaves what ServiceNow describes as an 18-point execution gap, with many businesses setting AI goals but failing to embed the technology in day-to-day work. For Irish companies facing higher costs and tighter margins, the lack of clear returns adds pressure to budgets.

AI spending across EMEA rose 113% year on year, and IT leaders expect to allocate 20% of their budgets to AI by 2027. Yet the research suggests that higher spending alone does not improve outcomes.

Governance gap

Organisations seeing returns tend to have stronger governance rather than bigger budgets. They combine data management, testing and risk controls with more integrated workflows, allowing them to scale AI more consistently.

Among that group, the study reported a 164% return on investment today and an expected 199% return within two years. It also found they were five times more productive, 2.6 times better at scaling AI and 2.5 times stronger at managing risk than their peers.

The results come as companies in Ireland prepare for the impact of the EU AI Act, which is expected to increase scrutiny of testing, oversight and risk management. The findings suggest many organisations still have work to do before they can demonstrate both commercial returns and regulatory readiness.

The research identified several operational weaknesses. Some 73% of EMEA executives cited poor data accuracy, access and management as a major barrier, making data quality the most common obstacle in the survey.

Testing and oversight also remain limited. Only 19% of organisations said they had implemented AI testing, auditing and risk processes, while just 15% had replaced legacy systems with integrated platforms.

Fragmented technology environments are also limiting broader use of AI. Although 57% of organisations use agentic AI, only 9% use it to create autonomous workflows. This suggests many businesses are using AI as a support tool rather than redesigning how work moves across the organisation.

Ireland has a large base of multinational technology and pharmaceutical companies, many of which run their European operations from the country. That concentration increases pressure on local leadership teams to turn AI spending into measurable productivity gains.

Paul Turley highlighted the divide between ambition and execution in the market.

"Organisations in Ireland are among the most ambitious on AI in Europe. The challenge isn't commitment. It's connecting that commitment to the operational infrastructure that makes AI work across the enterprise and, more importantly, getting it live with the right guardrails and governance. The organisations that have closed that gap are already seeing returns the rest have yet to match. The contrast is stark: those bridging the gap aren't just using AI more, they're using it differently, running autonomous, multi-step workflows at roughly eighteen times the rate of the rest of the market," said Paul Turley, Senior Director, ServiceNow Ireland.

The study was conducted by ThoughtLab on behalf of ServiceNow and surveyed more than 4,700 Senior Executives across 16 countries. Of those, 1,700 were in EMEA, and respondents were assessed across seven measures, including leadership, culture, data modernisation, governance, skills and AI-enabled workflows.

The numbers indicate that many companies have advanced quickly in planning and investment, but less so in implementation. Those making progress appear to have done so by tightening governance and improving the underlying systems through which AI is deployed.

For companies still struggling to convert spending into returns, the survey points to practical rather than financial constraints. Weak data foundations, limited testing, ageing systems and low adoption of autonomous workflows continue to hold back wider use.