Key facts
- Companies seeking to deploy AI at scale must first modernize their legacy technology systems.
- This modernization effort is expected to create a multi-year investment cycle in data, software, and infrastructure.
- Capgemini raised its 2026 revenue growth target following stronger bookings.
- Legacy systems, fragmented data, and complex technology estates are identified as major obstacles to AI adoption.
- Businesses are increasingly prioritizing large-scale transformation programs over standalone AI experiments.
Capgemini Chief Executive Aiman Ezzat stated that companies aiming to deploy artificial intelligence at scale will first need to modernize their decades-old technology systems. This necessity, he explained, is creating what he described as a multi-year investment cycle in data, software, and infrastructure.
Ezzat's comments followed Capgemini's announcement of a raised 2026 revenue growth target, attributed to stronger bookings. He elaborated that the primary barrier to widespread AI adoption is not the availability of AI models, but rather the prevalence of legacy systems, fragmented data, and complex technology estates accumulated over many years.
