By Pascal Brier, Chief Innovation Officer at Capgemini and Member of the Group Executive Committee.
As we look ahead to 2026, AI moves beyond experimentation and enters a phase of maturity. The upcoming year will see AI become the backbone of enterprise architecture, reshape software lifecycle development, and redefine cloud consumption. At the same time, enterprise systems are undergoing a fundamental shift toward intelligent operations, while tech sovereignty emerges as a strategic priority, driving organizations to build resilient interdependence.
The year of truth for AI
AI is without doubt the defining technology of the decade, but the pace of investment has outstripped the speed at which organizations have deployed and extracted value from it. Taking stock of where some of their AI experimentations failed to deliver the expected outcomes, business leaders now understand that the issue didn’t come from the technology itself but from the business approach and methodology.
Full-scale deployments will take time, and long-term value will not lie in isolated AI use cases but in enterprise-wide implementations. While the true growth phase begins, an AI ecosystem more rooted in operational value and enterprise architecture is emerging, starting with data foundations and infrastructure, and focusing on “Human-AI chemistry”. 2026 will be the moment to move from proof-of-concept to proof-of-impact, ensuring AI drives measurable outcomes, trust, and collaboration at scale, whilst laying the foundations for larger-scale transformation to follow.
AI is eating software
Software has eaten the world, and now AI is eating software. AI is reshaping the software development lifecycle across industries, shifting from writing code to expressing intent. After years of automation and DevOps-driven acceleration, AI is increasingly generating and maintaining software parts. From now on, developers will specify outcomes while AI generates and maintains components, shortening delivery cycles, and improving quality. But governance and oversight remain critical to prevent hallucinations, security gaps, and silent errors.
This new era of “Rebuilding software” across the full value chain aligns with becoming an AI-Native Business, operating on adaptive platforms rather than static ones. This approach opens opportunities to build more adaptive, sovereign systems, reduce reliance on Software as a Service provider, and enable differentiation through tailored products at competitive price points.
Cloud 3.0: all flavors of cloud
Cloud is entering its next evolution, a phase where hybrid, private, multi-cloud and sovereign architectures are no longer niche, but fundamental to how AI runs at scale, to the point it is becoming the operational backbone for AI and agentic workloads. AI cannot scale and get the right performance on classical public cloud alone, pushing adoption of all other models of cloud. Indeed, agentic systems rely on scalable and low-latency infrastructures, with edge and cloud working as a single intelligent fabric.
On top of that, large-scale outages and geopolitical pressures accelerate diversification and resilience strategies. While hybrid platforms will become mainstream, organizations will redesign architectures for performance, portability, sovereignty, and strategic autonomy to secure business continuity.
The rise of Intelligent Ops
Enterprise systems are evolving from static systems of record into living engines of intelligent operations – it’s a ‘Copernican Revolution[1]’ where processes become the focus, instead of being bolted-on applications. With the promises of agentic systems, businesses have the opportunity to rethink and redesign their business processes to make them self-improving, adaptable, and agile. Companies are now looking to orchestrate entire processes, not isolated steps, to run connected operations that break silos to create integrated value chains and enable organization-wide optimization.
AI agents embedded in core processes are starting to monitor activity, optimize execution, resolve exceptions, and orchestrate workflows across finance, supply chain, HR, and customer service. Automation will shift to Human-AI co-steering, where AI proposes and executes while humans supervise and govern. Oversight will become a design principle to ensure trust and resilience. Intelligent operations will enable businesses to move from reactive to proactive, reducing inefficiencies and improving agility. Apps and operations will continuously evolve instead of remaining static, predefined, or manually maintained.
The borderless paradox of tech sovereignty
Amid geopolitical uncertainty, tech sovereignty has moved from a policy concept to a strategic priority. Nations and enterprises now seek control over critical technologies in a world that remains deeply interconnected. The result is a new paradox: sovereignty is no longer defined by isolation, but by resilient interdependence. Since full tech autonomy does not exist, organizations will focus on risk mitigation and selective control over key layers.
Securing business continuity will become the primary imperative through diversified suppliers and sovereign alternatives. Sovereign and multi-clouds, regional AI models, open platforms and new chip ecosystems are also emerging to offer choice and strategic flexibility.
