Gartner reveals strategic tech trends set to redefine 2026
Gartner has revealed its list of top strategic technology trends that organisations should plan for in 2026, highlighting advancements in artificial intelligence, cybersecurity, cloud sovereignty, and data verification.
The trends identified for 2026 centre on the growing impact of AI supercomputing platforms, multiagent systems, AI security platforms, digital provenance, geopatriation, and preemptive cybersecurity among others, according to business and technology analysts at Gartner.
Gene Alvarez, Distinguished VP Analyst at Gartner, underscored the pressures facing technology leaders.
"Technology leaders face a pivotal year in 2026, where disruption, innovation and risk are expanding at unprecedented speed," said Alvarez. "The top strategic technology trends identified for 2026 are tightly interwoven and reflect the realities of an AI-powered, hyperconnected world where organisations must drive responsible innovation, operational excellence and digital trust."
Commenting on the pace of developments, Tori Paulman, VP Analyst at Gartner, said,
"These trends represent more than technology shifts; they're catalysts for business transformation. What feels different this year is the pace. We've seen more innovations emerge in a single year than ever before. Because the next wave of innovation isn't years away, organisations that act now will not only weather volatility but shape their industries for decades to come."
AI supercomputing platforms
AI supercomputing platforms bring together CPUs, GPUs, specialised hardware and orchestration software to manage complex, data-intensive workloads for fields such as machine learning, analytics, and simulation. These platforms enable enterprises to reach new performance and efficiency standards.
Gartner predicts that more than 40% of leading enterprises will have adopted hybrid computing architectures for critical workflows by 2028, up from eight percent today. In describing the real-world impact, Paulman said, "This capability is already driving innovation across a diverse range of industries. For example, companies in healthcare and biotech are modelling new drugs in weeks instead of years. In financial services, organisations are simulating global markets to reduce portfolio risk, while utility providers are modelling extreme weather to optimise grid performance."
Multiagent systems
Multiagent systems (MAS) involve distributed AI agents collaborating to achieve complex goals, with applications spanning both centralised and decentralised environments. Alvarez stated, "Adopting multiagent systems gives organisations a practical way to automate complex business processes, upskill teams and create new ways for people and AI agents to work together. Modular, specialised agents can boost efficiency, speed up delivery and reduce risk by reusing proven solutions across workflows. This approach also makes it easier to scale operations and adapt quickly to changing needs."
Domain-specific language models (DSLMs)
With the limitations of general-purpose large language models, domain-specific language models provide greater accuracy and compliance for industries requiring tailored solutions. Gartner expects over half of generative AI models in enterprise use will be domain-specific by 2028. Paulman noted, "Context is emerging as one of the most critical differentiators for successful agent deployments. AI agents unpinned by DSLMs can interpret industry-specific context to make sound decisions even in unfamiliar scenarios, excelling in accuracy, explainability and sound decision-making."
AI security platforms
AI security platforms give businesses a consolidated view of AI applications, enforce usage policies and guard against risks such as prompt injection and unauthorised agent actions. Gartner forecasts more than 50% of enterprises will employ AI security platforms to safeguard their AI systems by 2028.
AI-native development platforms
Harnessing generative AI within development platforms, organisations can enable small multidisciplinary teams to create applications, lowering the barriers for non-technical staff while maintaining oversight through governance frameworks. Gartner projects that, by 2030, 80% of businesses will restructure large engineering departments into agile, AI-augmented units.
Confidential computing
Confidential computing enhances data security by running workloads in hardware-based trusted execution environments, restricting data access even for infrastructure owners and cloud providers. Gartner foresees over 75% of operations processed on untrusted infrastructure will be kept secure by confidential computing by 2029.
Physical AI
This trend reflects AI's expansion into robotics, drones, and smart devices, increasing automation and operational safety in physical settings. It is noted that adoption drives a need for combined IT and engineering skills, encouraging upskilling and cross-functional collaboration, while also presenting workforce management challenges.
Preemptive cybersecurity
In response to escalating cybersecurity threats, preemptive measures utilising AI-driven operations and deception techniques are expected to dominate. Gartner forecasts these solutions will make up half of security spending by 2030. Paulman said, "Preemptive cybersecurity is about acting before attackers strike using AI-powered SecOps, programmatic denial and deception. This is a world where prediction is protection."
Digital provenance
With reliance on third-party code and AI-generated output growing, verifying the origin, ownership, and integrity of digital assets is increasingly important. Tools such as software bills of materials, attestation databases, and digital watermarking are emerging to support this. Gartner estimates companies without robust digital provenance practices could face sanctions worth billions of USD by 2029.
Geopatriation
Shifting data storage and computation from global public clouds to local or sovereign environments is becoming more common beyond regulated sectors, driven by growing geopolitical risk. Alvarez commented, "Shifting workloads to providers with an increased sovereignty posture can help CIOs gain more control over data residency, compliance and governance. This greater control may improve alignment with local regulations and build trust with customers who are concerned about data privacy or national interests."
The identified trends point to significant disruption and new opportunities for CIOs and technology decision-makers in the coming years, as organisations work to address rapid changes in technology, regulation, and security.
