O Gartner, Inc.., company of insights Business and technology announces its list of main strategic technological trends that organizations need to explore in 2026.
“"Technology leaders face a crucial year in 2026, in which disruption, innovation, and risk are expanding at an unprecedented speed," he states. Gene Alvarez, Emeritus Vice President Analyst at Gartner. “The key strategic technology trends identified for the year are directly interconnected and reflect the realities of a hyper-connected world driven by Artificial Intelligence (AI), in which organizations must foster responsible innovation, operational excellence, and digital trust.”
“"These trends represent more than just technological changes; they are catalysts for business transformation," he says. Tori Paulman, “What seems different this year is the pace. We’ve seen more innovation emerge in a single year than ever before. As the next wave of advancement is not years away, organizations that act now will not only weather the volatility but will shape their industries for decades to come,” said Gartner Vice President Analyst.”
The main strategic technological trends for 2026 are:
Supercomputing platform with AI
Supercomputing platforms with Artificial Intelligence integrate Central Processing Units (CPUs), Graphics Processing Units (GPUs), Application-Specific Integrated Circuits (ASICs) with AI, neuromorphic and alternative computing paradigms, allowing organizations to orchestrate complex workloads while achieving new levels of performance, efficiency, and innovation. These systems combine powerful processors, massive memory, specialized hardware, and orchestration software to handle data-intensive workloads, especially in areas such as... Machine Learning, simulations and analyses.
By 2028, Gartner predicts that more than 401,300 of leading companies will have adopted hybrid computing paradigm architectures in mission-critical workflows, compared to the current 81,300.
“This capability is already driving innovation across a wide range of sectors,” says Paulman. “For example, in healthcare and biotechnology, companies are modeling new drugs in weeks instead of years. In financial services, organizations are simulating global markets to reduce portfolio risk, while utility companies are modeling extreme weather conditions to optimize grid performance.”
Multi-agent systems
Multi-agent systems (MAS) are sets of AI agents that interact to achieve complex individual or shared goals. The agents can be provided in a single environment or developed and deployed independently in distributed environments.
“Adopting multi-agent systems offers organizations a practical way to automate complex business processes, enhance team skills, and create new ways for people and AI agents to work together,” says Alvarez. “Modular and specialized agents can increase efficiency, accelerate delivery, and reduce risk by reusing proven solutions across workflows. This approach also facilitates scaling operations and rapidly adapting to ever-changing needs.”
Domain-specific language models
CIOs (Chief Information Officers) and CEOs (Chief Executive Officers) are demanding more value from AI for business, but generic large language models (LLMs) often fall short in specialized tasks. domain-specific language models (DSLMs) fill this gap with greater accuracy, lower costs, and better compliance. DSLMs are language models trained or tuned based on specialized 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 models of Generative Artificial Intelligence (GenAI) used by companies will be domain-specific.
“"Context is emerging as one of the most critical differentiators for successful implementation of..." agents”AI agents not tied to DSLMs can interpret industry-specific context to make sound decisions, even in unfamiliar scenarios, excelling in accuracy, explainability, and sound decision-making,“ says Paulman.”
Security platforms for AI
AI security platforms offer a unified way to protect Artificial Intelligence applications, both those developed internally and those from third parties. They centralize visibility, enforce usage policies, and protect against AI-specific risks such as prompt injection, data leaks, and malicious actor actions. These platforms help CIOs enforce usage policies, monitor AI activity, and apply consistent protections across all AI applications.
By 2028, Gartner predicts that more than 501% of companies will be using TP3T platforms. security for AI to protect your investments in Artificial Intelligence.
AI-native development platforms
Native AI development platforms utilize GenAI To create software faster and easier than previously possible. Software engineers integrated into the business, 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 organizations 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 enable organizations to transform large software engineering teams into smaller, more agile teams enhanced by Artificial Intelligence.
Confidential computing
Confidential computing changes how organizations handle sensitive data. By isolating workloads within 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. This is especially valuable for regulated industries and global operations facing geopolitical and compliance risks, as well as for collaboration between competitors.
By 2029, Gartner predicts that more than 75% of operations processed on untrusted infrastructure will be protected through 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 delivers measurable gains in sectors where automation, adaptability, and safety are priorities.
As adoption grows, organizations need new skills that bridge IT, operations, and engineering. This shift creates opportunities for professional development and collaboration, but it can also raise employment concerns and require careful change management.
Preventive cybersecurity
THE preventive cybersecurity This is on the rise, as organizations 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 shift from reactive defense to proactive protection.
“"Preventive cybersecurity involves acting before attackers strike, using SecOps with AI, programmatic denial, and deception techniques (deception)”This is a world where foresight is protection,“ says Paulman.”
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, offer organizations the means to validate and track digital assets throughout the supply chain.
Gartner predicts that by 2029, those who fail to invest adequately in digitally sourced resources will be subject to penalties that could reach billions of dollars.
Geopatriation
Geopatriation means transferring a company's data and applications from one place to another. Clouds Global public offerings are shifting towards local options, such as sovereign clouds, regional providers, or the 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.
“Transferring workloads to providers with an increasingly sovereign posture can help CIOs gain more control over data residency, compliance, and governance,” says Alvarez. “This greater control can improve alignment with local regulations and build trust with clients who are concerned about data privacy or national interests.”
Gartner predicts that by 2030, more than 751% of European and Middle Eastern companies will migrate their virtual workloads to solutions designed to reduce geopolitical risk, compared to less than 51% in 2025.
This year’s key strategic technology trends highlight those that will generate significant disruption and opportunities for CIOs, IT leaders, and high-tech professionals over the next five years. Gartner clients can read more in the Special Report “Top Strategic Technology Trends for 2026”.
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