Capgemini

From the start, materials science has always relied on a simple model: test, fail, iterate. Quantum-informed modeling changes that. Where once we were limited to macro effects, we can now understand what’s happening at the level of the molecule. To see this approach in action, we can look at the case of advanced aerospace coatings, where harsh conditions degrade the surface in ways that are hard to predict.

Dirk Schrödter, Head of the State Chancellery (CdS) and Minister of Digitalization of the state of Schleswig-Holstein Dirk Schrödter is Head of the State Chancellery (CdS) and Minister of Digitalization of the state of Schleswig-Holstein. He has been leading the State Chancellery since 2017, and since 2022, he has also served as Minister for Digitalization and Media Policy. Previously, he was responsible for budget and financial policy in Schleswig-Holstein’s Ministry of Finance.

Nearly 80% of utilities expect more extreme and volatile demand patterns • Around one in five data center power requests may never materialize, distorting forecasts • At the same time, AI is expected by 60% of utilities to play a growing role in improving grid efficiency and unlocking operational gains, but only few have implemented advanced AI-driven approaches Paris, June 25, 2026 – The rapid expansion of AI-driven data centers is not only increasing electricity demand, but making it...

We are living in the Age of Electricity. While electrification across industry, transport, and buildings continues to push demand higher, one of the fastest-growing drivers is digital infrastructure – data centers and AI. In recent years, electricity demand has surged as data-center activity has expanded, and this trend is expected to continue over the next three to five years.

We are proud to announce that Capgemini has been recognized as the Boomi EMEA Growth Partner of the Year for FY26 – an acknowledgment of our continued commitment to helping clients connect, integrate, and unlock the full value of their data to drive intelligent, AI-enabled outcomes.

Early-stage drug discovery and development have famously always been time-consuming, costly, and risky. But not in the age of AI and digitalization. Ask anyone in pharma about the challenges of early-stage drug discovery and development and you’ll get the same answer: it’s notoriously time-consuming, costly, and risky. It’s always been this way.

Nearly 80% of utilities expect more extreme and volatile demand patterns • Around one in five data centre power requests may never materialise, distorting forecasts • At the same time, AI is expected by 60% of utilities to play a growing role in improving grid efficiency and unlocking operational gains, but only few have implemented advanced AI-driven approaches Paris, June 25, 2026 – The rapid expansion of AI-driven data centres is not only increasing electricity demand, but making it...

What should enterprises do about the advances in agentic AI? How can they build the necessary governance, security, identity, and control foundations needed to scale agentic AI responsibly and effectively? The first article in this series argued that agentic AI is an operating-model shift rather than a tooling upgrade. This article sets out the operating model itself.

Airbus and Great Britain’s National Energy System Operator (NESO) are two leaders in applied quantum exploration. Airbus has been among the first to push quantum into real industry use – developing algorithms to model aerodynamics and materials chemistry.

AI doesn’t have to be BIG to be impactful. Start with a smaller quick win. After plenty of discussion, experimentation, and hype cycles, many contact center leaders are arriving at the same realization: AI works best when it’s applied with precision. Not every implementation needs to be a multi year transformation, and not every use case requires a reinvention of the operation.