Capgemini is one of the largest technology and consulting firms on earth, and its AI practice is a serious, well-resourced way to get an ambitious AI program delivered by people who have done it at scale before. If you're a mid-to-large enterprise that needs a whole capability stood up — strategy, platforms, and a managed delivery team — Capgemini is a credible choice, and considering it is a sign you're thinking about AI as a real operating change, not a science project.

Capgemini was founded in 1967 by Serge Kampf in Grenoble, France, originally as Sogeti, and grew into a global leader in technology and business services. It's headquartered in Paris, led by CEO Aiman Ezzat, and listed on Euronext Paris under the ticker CAP as a member of the CAC 40. This is not a startup or a marketplace — it's a public company with more than 420,000 team members across roughly 50 countries. (Capgemini, Wikipedia) For 2025 the company reported revenues of €22,465 million and a total headcount of 423,400 at year-end, the higher number driven in part by its acquisition of WNS. (Full-year 2025 results, Capgemini) That scale is the whole point: when Capgemini shows up, it can put a large, cross-disciplinary team on the problem.

AI is now central to how Capgemini sells. Generative AI bookings represented more than 10% of group bookings in Q4 2025 and roughly 8% for the full year — meaningful for a company this size. (Full-year 2025 results, Capgemini) The firm has been reshaping itself around the shift, announcing restructuring costs of approximately €700 million over two years to adapt its workforce and skills, with the majority landing in 2026. That's a real bet, funded on the balance sheet. On the delivery side, Capgemini built RAISE (Reliable AI Solution Engineering) to industrialize its custom generative-AI projects, runs a Generative AI Lab, and partners with Google Cloud, Microsoft, Salesforce, AWS, Mistral AI, and Liquid AI. Its "augmented engineering" offering pairs generative AI with traditional engineering and scientific models, and includes Augmented Software Product Engineering — an agent-based framework plus consulting and engineering services covering requirements, code creation, product generation, and code migration. (Augmented engineering offerings, Capgemini)

End-to-end delivery. Capgemini can take a program from strategy through platform build and into a running, managed team. If you need the whole thing — not just people, but the operating model around them — few firms match that reach. (Data and AI services, Capgemini) Enterprise-grade rigor. Its augmented engineering pitch is explicitly built for contexts that demand precision, regulatory compliance, and low risk tolerance. For regulated industries — banking, healthcare, energy — that discipline is genuinely valuable. Real platform investment. RAISE, the Generative AI Lab, and hyperscaler partnerships mean you're not funding someone's first attempt at industrializing AI. There's an actual method and toolchain behind the work. Scale and continuity. With hundreds of thousands of people and a public balance sheet, Capgemini isn't going anywhere, and it can flex team size as your program grows — real stability for a multi-year transformation.

You're buying a team and an outcome, not a specific engineer. The Capgemini model is a managed engagement — you contract for delivery, and the firm staffs it. That's the right shape when you need a capability stood up broadly. It's a different shape than picking one named person and knowing exactly who is writing your code. It's built for scale, which fits scaled needs. A large services engagement is priced and structured for enterprise programs. If your need is one or two exceptional engineers embedded in your own team, a full managed engagement is more machine than the job requires. AI-native depth varies across a very large bench. Capgemini is investing heavily in upskilling its workforce for the AI shift, which is exactly the right move at its size. For your specific project, it's worth confirming that the individuals assigned have the hands-on, AI-native experience you're counting on — as you would with any large team.

The best AI engineers usually aren't on a services bench waiting for the next project. The ones you actually want are already working — booked on a contract somewhere else, heads-down on hard problems, not sitting in a pool to be staffed onto your account. And with a managed engagement, you don't pick or direct the individuals; you get the team the firm assigns. Nextdev reaches the top 1% of AI engineers — the ones who aren't looking. We give each a real problem to build and watch how they actually work, so you know they're AI-native because you've seen it, not because a slide deck said the practice is. When you want one, we employ them for you: one named engineer, working under your direction. The contract, payroll, and compliance never touch your desk. Capgemini hands you a delivery team and leaves you to trust the bench. We hand you a specific person you chose, already proven on real work. You're not staffed with whoever was between projects. You're getting the engineer who never would have been on the bench.

Capgemini is a strong, credible choice for enterprises that need a whole AI capability delivered — strategy, platforms, and a managed team, from a stable global firm with real investment behind it. If that's the scale of your problem, it's a smart shortlist. If instead you need one exceptional, proven AI-native engineer working directly inside your team, that's a different job — and it's the one Nextdev is built for.