The widespread adoption of AI is forcing organizations to first get their IT foundations in order. According to Capgemini, the biggest challenge is not the availability of AI models, but the outdated technology on which many companies still rely. This will lead to a sustained wave of investment in infrastructure, applications, and data platforms in the coming years.
CEO Aiman Ezzat conveyed this message during the presentation of Capgemini’s quarterly results, as reported by Reuters. The French IT services provider raised its revenue growth forecast for 2026 after order intake exceeded expectations.
According to Ezzat, many organizations underestimate the preparatory work needed before AI can be deployed on a large scale. “Every organization wants to become ‘agent-driven’ these days,” he said, referring to AI systems that can autonomously perform multiple steps. “But before organizations can become agent-driven, they must be AI-ready, and most are not yet.”
According to the CEO, legacy systems, fragmented data sources, and complex IT environments built up over decades are the biggest obstacles to AI adoption. As a result, AI applications often lack access to consistent and reliable data, which is precisely what is needed to automate business processes.
Ezzat, therefore, spoke of a “multi-year modernization supercycle.” According to him, companies will not only invest in new AI functionality but will simultaneously modernize their technological foundation. This includes data platforms, core applications, and the underlying infrastructure.
The accumulated technical debt also plays a significant role in this. In many organizations, data is scattered across poorly integrated systems, making it difficult for AI to operate across departments or execute processes independently.
From experiments to large-scale projects
According to Capgemini, the way organizations invest in AI is now shifting. Whereas in recent years many projects consisted of pilots and experiments, companies are now increasingly opting for large-scale transformation programs that directly link AI to the modernization of their IT landscape.
While generative AI can produce answers quickly, Ezzat notes that it delivers true business value only when the underlying systems and data have also been modernized. “AI not only creates demand for new business opportunities; it also accelerates the modernization of the technological foundation on which those opportunities are built.”