Capgemini explains five ‘key tech trends’ of 2026

Capgemini unveils five tech trends and shares its view on the technology of 2026.

Capgemini has presented its new TechnoVision Top 5 Tech Trends to Watch in 2026, a look ahead at technologies that will reach a clear tipping point in the coming year. AI and generative AI remain decisive, but their impact now extends far beyond experimental applications. They are becoming a structural part of software development, cloud architecture and business strategy.

According to Pascal Brier, Chief Innovation Officer at Capgemini, AI will reach a stage of maturity in 2026: a period in which the technology is not seen as a gimmick, but forms the foundation of enterprise architectures and operational models.

1. The year of truth for AI

“In recent years, more has been invested in AI than companies could implement the technology,” says Dr. Mark Roberts, head of applied sciences at Capgemini Engineering. Where experiments sometimes yielded insufficient returns, it is becoming increasingly clear that the problem rarely lay with the technology, but with fragmented methods and limited scale.

“2026 will be the moment when companies focus on reliable data foundations, stable infrastructures and a more mature form of collaboration between humans and machines,” he clarifies. AI is shifting from large, separate AI models to a hybrid and integrated approach in which measurable results are central. The year promises a movement from proof-of-concepts to production, in which companies finally get the value of AI on a large scale.

2. Impact of AI on software

Where software once changed the world, it is now AI that is transforming the software world itself. The classic process in which developers write code is increasingly giving way to a method in which they build the software via prompts and let AI make the technical translation.

“The software lifecycle is becoming shorter and smarter, because AI increasingly generates pieces of code, performs maintenance and even rebuilds complete parts of applications,” says Sudhir Pi, CTO at Capgemini. According to him, this evolution requires new forms of governance and supervision, because quality, safety and reliability remain crucial. At the same time, a new development phase is emerging in which companies must learn to use new toolsets to truly become AI-native. This requires different skills, where a mindshift and close monitoring of AI-driven processes become more important than traditional coding.

3. Cloud 3.0: new cloud innovations

“Cloud technology is entering a new phase,” says Georgia Smith, Cloud Transformation Leader at Capgemini UK. Where the public cloud has been the norm for years, a more varied landscape is now emerging in which hybrid, private, multi-cloud and sovereign environments are central. The scalability and low latency that AI and agent-driven systems require make it necessary to distribute data and computing power across multi-cloud systems. Edge computing and cloud are also growing closer and closer together.

The geopolitical tensions and recent major disruptions are causing companies to choose multiple cloud providers more quickly, so that they are no longer dependent on a single supplier or infrastructure. Cloud 3.0 is therefore about flexibility, resilience and strategic autonomy, but also requires new skills and governance.

4. The rise of ‘Intelligent Ops’

How will companies use AI agents to build and streamline their processes? “Thanks to AI agents, they can design processes that improve themselves, recognize exceptions, solve bottlenecks and create value,” says Simone Neser, AI Taskforce Program Manager at Capgemini’s Business Services. This is called Intelligent Ops, automated processes that combine data, AI and digital processes. The traditional silos are giving way to integrated value chains because departments such as marketing, sales, HR and supply chain are becoming more closely connected.

“The interaction between humans and AI is fundamental here,” she predicts. AI executes and anticipates, while people provide direction, supervise and intervene where nuance or context is needed. This creates an operational model that no longer only reacts, but also looks ahead and adapts.

5. The paradox of tech sovereignty

In a world that is becoming both more global and geopolitically unstable, technological sovereignty is becoming an increasingly important theme. “The paradox, however, is that this sovereignty is achieved through independence. Companies and countries are not striving for complete independence, that is not realistic, but for control over different suppliers,” says Nicolas Gaudilliere, CTO Capgemini Invent France. It is about selective control from chips and data platforms to AI models and cloud infrastructures.

“There are more and more local opportunities and alternatives, such as regional AI models and sovereign clouds, which offer companies the opportunity to split their risks and ensure continuity.”