2026年顶级科技趋势

Who should readthis report and why? Table of contents This report is designed for C-suiteexecutives and business and innovationleaders. The report presents ourconvictions regarding what will be themost impactful technological trendsof 2026. It offers valuable insights intothe trends we see dominating the techlandscape, while looking back on theaccuracy of our predictions for 2025.Data from comprehensive surveys of industry Cloud 3.0 –all flavors of cloud 03Introduction06 technological sovereignty22 truth for AI10 by 2030 and beyond29 softwareThe rise of14 executives, the investor community, andin-depth discussions with experts supportour predictions. The insights we derive fromthis analysis will help technology and businessleaders in establishing sound strategies andimpactful investments. intelligent ops Concluding remarks Pascal Brier Group Chief Innovation Officer,Member of the Group ExecutiveCommittee, Capgemini Introduction At the same time, the global environment isforcing companies to rethink resilience andbusiness continuity at a much deeper level.Rising dependencies on critical technologies(from semiconductors and cloud services toAI models and compute infrastructure) havebecome strategic risk factors rather thanpurely technical choices. This is driving a dualmovement: a renewed push for architecturesthat can withstand disruption, and a search forgreater control over the layers of technologythat matter most. Cloud strategies are evolvingaccordingly, with hybrid, multi-cloud, andsovereign options emerging not as exceptionsbut as mechanisms to secure continuity, reduceconcentration risk, and safeguard data andoperations. Sovereignty is part of this shift, butthe underlying theme is broader: organizationsare redesigning their foundations to remain After several years of extraordinaryacceleration across AI, cloud, data, andautomation, 2026 marks a shift towardstrengthening, upgrading or rebuilding thefoundations that will support the next decade.Across industries, leaders recognize that open, scalable, and globally connected,while ensuring that no single dependencycan compromise their ability to operate. toward structural rebuilding, pointing to a singlemessage: technology leadership in 2026 is nolonger about experimentation, but aboutconstructing the durable foundations thatwill enable true value to be extractedfrom innovation.As every major technological shift has shown, progress cannot rest on fragmented pilots orloosely connected digital initiatives. The eraof experimental AI is giving way to the needfor solid AI foundations: reliable data, cleargovernance, scalable architectures, and systemsdesigned for safety, trust, and measurableoutcomes. The organizations able to movefrom isolated models to integrated, enterprise-wide intelligence will be those that generatelasting value. it is the strength of these foundations, not thenovelty of individual tools, that determineswho captures long-term advantage. This reportaims to help business and technology leadersmake the right strategic choices at a momentwhen those foundations are being rebuilt. Looking back to the top tech trends of the last two years 20252024 The top techtrends of 2026 The year oftruth for AI The year oftruth for AI AI. Short-term hype fades, but what remains is anecosystem increasingly grounded in operational value,enterprise architecture, and sustained productivity.As with past technology waves, real growth beginsonce organizations recognize that value does not liein isolated use cases but in enterprise-wide systemsthat evolve and scale over time.Reaching that future requires discipline. Organizations and experimentation, AI has become thedefining technology of the decade. Yet thepace of investment has outstripped the speedat which organizations have been able todeploy it at scale and extract measurablevalue. Many enterprises now find themselveswith sophisticated models, agents, andprototypes that remain unintegrated, under-utilized, or disconnected from real businessoutcomes. This gap has generated someskepticism and a sense of some form of AI hype.Beneath the noise, however, something operations1. Crucially, these gains are not merelyabsorbed as efficiency: half of organizationsreinvest the time saved into developing newfeatures, while nearly as many channel it intoworkforce upskilling. This marks a shift fromexperimentation to value compounding.At the same time, AI itself is evolving in form and function. Large models are becoming moremodular, agents are moving from novelty toolsto workflow orchestrators, and AI is shiftingfrom peripheral experimentation to deeperintegration within enterprise cores. Adoptionreflects this transition. Today, roughly 46% ofthe software workforce uses generative AItools; by 2026, that figure is expected to reach85%2, signaling a move from early adoption todefault capability.must confront their true AI readiness, starting withdata foundations and infrastructure. The agenticwa