Gartner highlights interconnected technology trends that reinforce digital trust and operational resilience.
Gartner has outlined its list of the top strategic technology trends that organisations need to explore in 2026.
“Technology leaders face a pivotal year in 2026 in which disruption, innovation and risk are expanding at an unprecedented rate,” said Gene Alvarez, Vice President Analyst Emeritus, Gartner. “The key strategic technology trends identified for the year are directly interconnected and reflect the realities of a hyper-connected, AI-driven world, where organisations must foster responsible innovation, operational excellence and digital trust.”
“These trends represent more than technological changes; they are catalysts for business transformation,” said Tori Paulman, Vice President Analyst, Gartner. “What looks different this year is the pace. We’ve seen more innovations emerge in a single year than ever before. Because the next wave of advancement is not years away, organisations that act now will not only withstand volatility but shape their industries for decades to come.”
The main strategic technology trends for 2026 are:
AI supercomputing platform
AI-powered supercomputing platforms integrate AI-powered Central Processing Units (CPUs), Graphics Processing Units (GPUs), Application-Specific Integrated Circuits (ASICs), neuromorphic and alternative computing paradigms, enabling organisations to orchestrate complex workloads while achieving new levels of performance, efficiency and innovation.
These systems combine powerful processors, massive memory, specialised hardware and orchestration software to handle data-intensive workloads, especially in areas such as machine learning, simulations and analytics.
By 2028, Gartner predicts that more than 40% of leading enterprises will have adopted hybrid computing paradigm architectures in critical workflows, up from 8% today.
“This capability is already driving innovation across a wide range of industries,” Paulman says. “For example, in healthcare and biotechnology, companies are modeling new drugs in weeks rather than years. In financial services, organisations are simulating global markets to reduce portfolio risk while utilities are modeling extreme weather to optimise grid performance.”
Multi-agent systems
Multi-agent systems (MAS) are sets of AI agents that interact to achieve individual or shared complex goals. Agents can be provisioned in a single environment or independently developed and deployed in distributed environments.
“Adopting multi-agent systems gives organisations a practical way to automate complex business processes, enhance teams’ skills and create new ways for people and AI agents to work together,” Alvarez says. “Modular and specialised agents can increase efficiency, speed delivery and reduce risk by reusing proven solutions across all workflows. This approach also makes it easy to scale operations and adapt quickly to changing needs.”
Domain-specific language models
CIOs and CEOs are demanding more business value from AI but generic large language models (LLMs) often fall short on specialized tasks. Domain-specific language models (DSLMs) bridge this gap with greater accuracy, lower costs and better compliance.
DSLMs are language models that are trained or fine-tuned based on specialised data for a particular industry, function or process. Unlike general-purpose models, DSLMs offer greater accuracy, reliability and compliance for specific business needs.
By 2028, Gartner predicts that more than half of the Generative Artificial Intelligence (GenAI) models used by enterprises will be domain-specific.
“Context is emerging as one of the most critical differentiators for successful agent implementation,” says Paulman. “AI agents not tied to DSLMs can interpret the industry-specific context to make sound decisions, even in unfamiliar scenarios, excelling in accuracy, explainability and sound decision-making.”
Security platforms for AI
AI security platforms offer a unified way to protect AI applications, both internally developed and third-party. They centralise visibility, enforce usage policies and protect against AI-specific risks such as prompt injection, data leakage and actions by malicious actors.
These platforms help CIOs enforce usage policies, monitor AI activity and apply consistent protections across AI.
By 2028, Gartner predicts that more than 50% of companies will use AI security platforms to protect their AI investments.
AI-native development platforms
AI-native development platforms use GenAI to create software faster and easier than was previously possible. Business-integrated software engineers, acting as forward-deployed engineers, can use these platforms to work together with domain experts to develop applications.
Organizations can have small teams of people working together with AI to create more applications with the same level of developers they have today. Leading organisations are creating small platform teams to enable non-technical domain experts to produce software on their own, with security and governance barriers in place.
Gartner predicts that by 2030, AI-native development platforms will cause 80% of organisations to transform large software engineering teams into smaller, more agile teams enhanced by AI.
Confidential computing
Confidential computing changes the way organisations handle sensitive data. By isolating workloads within hardware-based trusted execution environments (TEEs), it keeps content and workloads private, even for infrastructure owners, cloud vendors or anyone with physical access to the hardware.
This is especially valuable for regulated industries and global operations that face geopolitical and compliance risks, as well as collaboration between competitors.
By 2029, Gartner predicts that more than 75% of operations processed on untrusted infrastructure will be protected in use by confidential computing.
Physical AI
Physical AI brings intelligence to the real world, powering machines and devices that detect, decide and act, such as robots, drones and smart equipment. It brings measurable gains in industries where automation, adaptability and security are priorities.
As adoption grows, organisations need new skills that bridge IT, operations and engineering. This change creates opportunities for professional improvement and collaboration, but it can also raise employment-related concerns and require careful change management.
Preventive cybersecurity
Preventive cybersecurity is on the rise as organisations face an exponential increase in threats targeting networks, data and connected systems. Gartner predicts that by 2030, preventative solutions will account for half of all security spending as CIOs move from reactive defense to proactive protection.
“Preemptive cybersecurity is about taking action before attackers attack, using AI-powered SecOps, programmatic denial and deception techniques,” Paulman says. “This is a world where prediction is protection.”
Digital provenance
As organizations increasingly rely on third-party software, open source and AI-generated content, digital provenance verification has become essential. Digital provenance refers to the ability to verify the origin, ownership and integrity of software, data, media and processes.
New tools such as software bills of materials (SBoM), certification databases and digital watermarks give organizations the means to validate and track digital assets throughout the supply chain.
Gartner predicts that by 2029, those who do not invest adequately in digitally sourced resources will be subject to sanctions risks that could run into billions of dollars.
Geopatriation
Geopatriation means moving the company’s data and applications from global Public Clouds to local options, such as sovereign clouds, regional providers or the organisation’s own data centers, due to perceived geopolitical risk.
Cloud sovereignty, once limited to banks and governments, now affects a wide range of organisations as global instability increases.
“Shifting workloads to providers with an increasing sovereignty posture can help CIOs gain more control over data residency, compliance and governance,” Alvarez says. “This increased control can improve alignment with local regulations and build trust with customers who are concerned about data privacy or national interests.”
Gartner predicts that by 2030, more than 75% of European and Middle Eastern enterprises will shift their virtual workloads to solutions designed to reduce geopolitical risk, up from less than 5% in 2025.
