Summary

• Capgemini has raised its 2026 revenue growth target after stronger first half performance.
• UK and Ireland revenue grew sharply, while AI, legacy modernisation, intelligent operations, and sovereignty themes shaped demand.
• The results reinforce an established trend: AI adoption is increasingly tied to core systems, process redesign, and enterprise operating models.

Capgemini has upgraded its 2026 outlook after stronger first half trading, with demand for AI driven enterprise transformation sitting alongside legacy modernisation, intelligent operations, and public sector work.

The French technology services group now expects faster constant currency revenue growth for the year, while keeping operating margin and organic free cash flow guidance broadly in line. Its UK and Ireland business stood out in the regional figures, helped by public sector traction, consumer goods and retail work, and a dynamic financial services sector.

Capgemini chief executive Aiman Ezzat said: “Our pipeline has expanded substantially.” Speaking to analysts, he added: “Every organisation today wants to become agentic. But before they can become agentic, they must become AI-ready, and most are not.”

The market signal is useful because enterprise AI demand is becoming less detached from the work that has always made technology transformation difficult. Ezzat’s comments put the emphasis on the foundations beneath AI adoption: data platforms, applications, infrastructure, and the decades of technical debt that make autonomous workflows harder to deliver in live organisations than they appear in demonstration environments.

Bookings also point to a more serious spending environment. Capgemini’s operations and engineering work benefited from intelligent business operations, where AI, automation, and managed process capability are being packaged around practical work rather than narrow chatbot deployment. This reinforces a recognised pattern rather than introducing a sudden new market: organisations are moving AI into document heavy processes, contact centres, finance operations, software engineering, compliance tasks, and supply chain analysis.

Those use cases can produce measurable improvements, but they require clean data, workflow integration, controls, and revised operating processes before AI can safely influence live decisions. A generative AI tool may summarise, draft, classify, or retrieve information, yet value depends on whether the surrounding process changes. Otherwise, AI becomes another layer of software on top of old friction.

The results are favourable for systems integrators and consulting groups, but buyers will need to manage dependency carefully. If AI adoption becomes another large transformation programme led mainly by external advisers, companies may struggle to retain ownership of the underlying capability. Stronger deployments will combine external delivery capacity with internal teams that can govern models, challenge outputs, maintain processes, and measure performance.

Capgemini’s comments on defence, security, and technological sovereignty add a European dimension. AI transformation is being connected not only to productivity, but also to resilience, national capability, and independence from fragile or geopolitically exposed supply chains. That framing is increasingly visible in European public sector, defence, financial services, and infrastructure markets.

The pressure now shifts towards evidence. Service providers can point to pipelines, bookings, and client demand, but buyers will ask whether AI transformation produces better margins, faster operations, lower risk, or improved customer and citizen outcomes. Many organisations are past the stage where a generative AI pilot is enough to satisfy boards. The next phase will be measured through adoption rates, process cycle times, assurance controls, cost to serve, and whether modernisation unlocks new ways of working.

Capgemini’s upgraded outlook does not show AI solving enterprise transformation. It shows companies beginning to fund the harder work between ambition and operational change.