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Follow ZDNET: Add us as a preferred source on Google. ZDNET's key takeaways AI innovation dominates 2026's strategic technology trends.Gartner's report shows trends that will impact the next five years.Physical AI powers robots, drones, and smart equipment. In 2026, according to the latest research from Gartner, disruption is accelerating, and AI is no longer optional. The technology is sprinkled throughout the list in various forms, from multi-agent systems to physical AI, driving Gartner's list of the most strategic technology trends for 2026. These are the 10 trends that reflect how leading organizations are responding to complexity and opportunity in an AI-powered, hyperconnected world, according to Gartner: 1. AI-native development platforms AI-native development platforms use gen AI to create software faster and easier than was previously possible. Software engineers embedded in the business, acting as "forward-deployed engineers," can utilize these platforms to collaborate with domain experts in developing applications. Organizations can have tiny teams of people paired with AI to create more applications with the same level of developers they have today. Also: This is why your company is transforming into an autonomous machine Gartner predicts that by 2030, AI-native development platforms will enable 80% of organizations to evolve their large software engineering teams into smaller, more nimble teams augmented by AI. 2. AI supercomputing platforms AI supercomputing platforms integrate CPUs, GPUs, AI ASICs, neuromorphic, and alternative computing paradigms, enabling organizations to orchestrate complex workloads while unlocking new levels of performance, efficiency, and innovation. These systems combine powerful processors, massive memory, specialized hardware, and orchestration software to tackle data-intensive workloads in areas like machine learning, simulation, and analytics. By 2028, Gartner predicts that over 40% of leading enterprises will have adopted hybrid computing paradigm architectures into critical business workflows, up from the current 8%. 3. Confidential computing Confidential computing changes how organizations handle sensitive data. By isolating workloads inside hardware-based trusted execution environments (TEEs), it keeps content and workloads private even from infrastructure owners, cloud providers, or anyone with physical access to the hardware. By 2029, Gartner predicts more than 75% of operations processed in untrusted infrastructure will be secured in-use by confidential computing. 4. Multi-agent systems Multi-agent systems (MAS) are collections of AI agents that interact to achieve individual or shared complex goals. Agents may be delivered in a single environment or developed and deployed independently across distributed environments. 5. Domain-specific language models (DSLMs) CIOs and CEOs are demanding more business value from AI, but generic large language models (LLMs) often fall short for specialized tasks. Domain-specific language models (DSLMs) fill this gap with higher accuracy, lower costs, and better compliance. DSLMs are language models trained or fine-tuned on specialized data for a particular industry, function, or process. Unlike general-purpose models, DSLMs deliver higher accuracy, reliability, and compliance tailored to specific business needs. By 2028, Gartner predicts that over half of the generative AI models used by enterprises will be domain-specific. 6. Physical AI Physical AI brings intelligence into the real world by powering machines and devices that sense, decide, and act, such as robots, drones, and smart equipment. It brings measurable gains in industries where automation, adaptability, and safety are priorities. 7. Preemptive cybersecurity Preemptive cybersecurity is trending as organizations face an exponential rise in threats targeting networks, data, and connected systems. Gartner forecasts that by 2030, preemptive solutions will account for half of all security spending, as CIOs shift from reactive defense to proactive protection. Also: Enterprises are not prepared for a world of malicious AI agents 8. Digital provenance As organizations rely more on third-party software, open-source code, and AI-generated content, verifying digital provenance has become essential. Digital provenance refers to the ability to verify the origin, ownership, and integrity of software, data, media, and processes. Gartner predicts that by 2029, those who fail to adequately invest in digital provenance capabilities will be exposed to sanction risks, potentially running into the billions of dollars. 9. AI security platforms AI security platforms provide a unified way to secure third-party and custom-built AI applications. They centralize visibility, enforce usage policies, and protect against AI-specific risks such as prompt injection, data leakage, and rogue agent actions. These platforms help CIOs enforce use policies, monitor AI activity, and apply consistent guardrails across AI. By 2028, Gartner predicts that over 50% of enterprises will use AI security platforms to protect their AI investments. 10. Geopatriation Geopatriation means moving company data and applications out of global public clouds and into local options such as sovereign clouds, regional cloud providers, or an organization's own data centers due to perceived geopolitical risk. Cloud sovereignty, once limited to banks and governments, now affects a wide range of organizations as global instability increases. Gartner predicts that by 2030, more than 75% of European and Middle Eastern enterprises will geo-patriate their virtual workloads into solutions designed to reduce geopolitical risk, up from less than 5% in 2025. Also: Even the best AI agents are thwarted by this protocol - what can be done In addition to the top 10 strategic technology trends for 2026, Gartner also revealed its top IT strategic predictions for 2026 and beyond. Here are the IT predictions: Through 2027, gen AI and AI agent use will create the first true challenge to mainstream productivity tools in 30 years, prompting a $58 billion market shakeup.By 2027, 75% of hiring processes will include certifications and testing for workplace AI proficiency during recruitingThrough 2026, atrophy of critical-thinking skills, due to gen AI use, will push 50% of the global organizations to require "AI-free" skills assessments.By 2027, 35% of countries will be locked into region-specific AI platforms using proprietary contextual data.By 2028, organizations that leverage multi-agent AI for 80% of customer-facing business processes will dominate.By 2028, 90% of B2B buying will be AI agent intermediated, pushing over $15 trillion of B2B spend through AI agent exchanges.By the end of 2026, "death by AI" legal claims will exceed 2,000 due to the insufficient implementation of AI risk guardrails.By 2030, 20% of monetary transactions will be programmable to include terms and conditions of use, to give AI agents economic agency.By 2027, the cost-to-value gap for process-centric service contracts will be reduced by at least 50% due to agentic AI reinvention.By 2027, fragmented AI regulation will grow to cover 50% of the world's economies, driving $5 billion in compliance investment. Regarding talent management and recruiting, Gartner noted, "Within the next two years, expect to see many organizations implementing practical AI proficiency assessments in their hiring processes." Also: 5 must-have cloud tools for small businesses (and my top 10 money-saving secrets) Regarding multi-agentic orchestration and management, Gartner highlighted the importance of customer relationship management (CRM) systems, noting that organizations that fail to adopt multi-agent AI for their CRM organizational processes risk losing competitive advantage as customer expectations for low effort, rapid service become the norm. To learn more about the Gartner top strategic technologies and IT predictions for 2026 and beyond, you can visit here. Get the morning's top stories in your inbox each day with our Tech Update newsletter.
