Gartner Reveals 10 Strategic Technology Trends That Will Transform Businesses in 2026

The research and advisory firm Gartner, Inc. has announced ten strategic technology trends for 2026 that business organisations should examine and monitor.

Gene Alvarez, Vice President Analyst at Gartner, commented:

The year 2026 will be a pivotal year for technology leaders who must contend with disruption, innovation and rapidly expanding risk like never before. The strategic technology trends for next year will be closely tied to these factors and reflect a world that is driven by AI and ever-more connected in which business organisations must drive innovation responsibly, operate with excellence, and build digital trust concurrently.

Tori Paulman, another Vice President Analyst at Gartner, added:

These trends show us more than a technology transition they are business-change accelerators. What is different this year is the speed. In a single year we are seeing more innovation emerge than ever before, because the next wave of innovation is no longer years away. Therefore, organisations that act now will not only be able to deal with volatility but will also shape their industrys direction for the next decade.

The key strategic technology trends for 2026 include:

AI Supercomputing Platforms
These platforms integrate CPUs, GPUs, application-specific AI ASICs, neuromorphic computing (which mimics the human brains processing) and other alternative computing paradigms. They enable organisations to handle complex workloads and unlock a new level of performance, efficiency and innovation. These systems combine powerful processors, large memory, specialised hardware, and orchestration software that manages and coordinates applications, services or workflows to run together. They manage data-intensive workloads in areas such as machine learning, simulation and analytics.
Gartner forecasts that by 2028 more than 40 % of leading enterprises will adopt hybrid-computing-paradigm architectures into mission-critical business workflows up from 8 % today.
This capability is already driving innovation across diverse industries. For example: in healthcare and biotech, companies can model 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 the power grid. Paulman said.

Multiagent Systems (MAS)
A multiagent system is a collection of AI agents that interact to achieve individual or shared complex goals. Agents may be delivered in a single environment or developed and deployed separately across distributed environments.
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 collaborate. Modular, specialised agents can boost efficiency, accelerate delivery and reduce risk by re-using proven solutions across workflows. This approach also makes it easier to scale operations and adapt quickly to changing needs. Alvarez said.

Domain-Specific Language Models (DSLMs)
CIOs and CEOs are demanding more business value from AI, but general large language models (LLMs) often fall short for specialist tasks. DSLMs fill this gap by offering higher accuracy, lower cost, and improved compliance. DSLMs are language models that are trained or fine-tuned on specialised data for a particular industry, role or process unlike general-purpose models. They deliver higher accuracy, reliability and compliance for targeted business needs.
Gartner predicts that by 2028 more than half of the generative AI models (GenAI) used by enterprises will be domain-specific.
Context is becoming one of the most critical differentiators for successful agent deployments. AI agents supported by DSLMs can interpret industry-specific context to make correct decisions even in unfamiliar scenarios, excel in accuracy, explainability and sound decision-making. Paulman said.

AI Security Platforms
These are centralised platforms to secure both third-party and custom-built AI applications. They provide consolidated 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 usage policies, monitor AI activities and apply consistent guardrails across AI.
Gartner forecasts that by 2028 more than 50 % of enterprises will be using AI security platforms to protect their AI investments.

AI-Native Development Platforms
AI-native development platforms use generative AI (GenAI) to build software faster and easier than was previously possible. Software engineers embedded in the business (so-called forward-deployed engineers) collaborate with domain experts to configure the platform and develop applications. Organisations can have small teams paired with AI to create more applications with the same number of developers they already have. Leading organisations are building small platform teams to enable non-technical domain experts to produce software themselves with security and governance built in.
Gartner predicts that by 2030 these AI-native development platforms will lead 80 % of organisations to evolve their large software engineering teams into smaller, more agile teams augmented by AI.

Confidential Computing
Confidential computing is a new approach to securing data while it is being processed. It changes how organisations handle sensitive data: workloads are isolated within hardware-based Trusted Execution Environments (TEEs) so that content and workloads remain private even from the infrastructure owner, cloud provider, or anyone with physical access to the hardware. This is especially valuable for regulated industries and global operations facing geopolitical and compliance risks and for collaboration with competitors.
By 2029 Gartner predicts that more than 75 % of workloads processed in untrusted infrastructure will be secured in-use by confidential computing.

Physical AI
Physical AI brings the intelligence of AI into the physical world embedding it into machines and devices that sense, decide and act (e.g., robots, drones, and smart equipment). It enables measurable gains in industries where automation, adaptability and safety are priorities.
As adoption grows, organisations will need new skills bridging IT, operations and engineering. This shift creates opportunities for upskilling and new collaboration but may also raise concerns about jobs and requires careful change-management.

Preemptive Cybersecurity
Preemptive (or proactive) cybersecurity is trending as organisations 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 defence to proactive protection.
Preemptive cybersecurity is about acting before attackers strikeusing AI-powered SecOps (Security Operations), programmatic denial and deception. Paulman said. This is a world where prediction is protection.

Digital Provenance
As organisations increasingly rely on third-party software, open-source code and AI-generated content, verifying digital provenance becomes 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), attestation databases and digital watermarking give organisations methods to validate and track digital assets across the supply chain.
Gartner expects that by 2029 organisations that have not invested sufficiently in digital provenance capabilities will face risks of penalties running into the billions of dollars.

Geopatriation
Geopatriation refers to organisations moving their data and applications away from global public-cloud providers and toward local operations such as sovereign cloud, regional cloud providers or on-premises data centres in response to recognised geopolitical risks. While this once mostly impacted banks and governments, cloud-computing operations that are located and managed in the same country or region as their users (so-called cloud sovereignty) are now having impact across multiple sectors.

Moving workloads to providers with increasing sovereignty posture can help CIOs gain greater control over data-residency, compliance and governance and build trust with customers who worry about data privacy or national interest. Alvarez said.


Gartner / PC & Associates Consulting Co., Ltd. & FAQ Co., Ltd