Next year 2026 will be crucial for companies in terms of technology, due to numerous factors, especially related to disruption, innovation and risk, according to the consulting firm Gartner. All this is reflected in what will be the top business technology trends for 2026which will be closely related to each other and also reflect the reality of an increasingly connected world, where AI will take on more and more prominence.
It will also be a year in which companies will have to take into account responsibility in the environment and other areas when innovating, as well as what is necessary to maintain operational excellence. These trends will contribute to this, which in addition to entailing changes in many aspects, will also in many cases be vehicles or catalysts for the transformation of companies, which will occur at an even greater rate than in previous years.
Because the consulting firm warns that the next wave of innovation is not as far away as it may seem, and what happens in 2026 will serve companies not only to address the volatility in their sectors, but also as a basis for the evolution of their sectors in the coming decades. These trends are the following:
1 – AI supercomputing platform
AI supercomputing platforms incorporate AI-enabled CPUs, GPUs, and ASICs, enabling businesses to orchestrate complex workloads and achieve improved performance, efficiency, and innovation. They combine powerful processors, massive memory, specialized hardware, and orchestration software, allowing them to address data-intensive workloads in areas such as machine learning, simulation, and analytics.
By 2028, Gartner predicts that more than 40% of world-class enterprises will have adopted hybrid computing paradigm architectures in business-critical workflows. Currently, this percentage is 8%, and will begin to increase significantly as early as 2026.
2 – Multi-agent systems
Multi-agent systems, or MAS, are sets of AI agents that interact to achieve complicated goals, both individual and shared. Agents can be delivered in a single environment, or developed and deployed independently in distributed environments.
3 – Domain Specific Language Models (DSLM)
IT managers and business leaders are demanding more value from AI for their organizations, but large language models often fall short for specialized tasks. Domain Specific Language Models (DSML) provide more precision than LLM, lower costs, and better compliance.
They are language models trained or tuned with specialized data for a specific industry, function or process, so they offer more precision and reliability for specific business needs. According to Gartner, by 2028, more than half of generative AI models used by enterprises will be domain-specific.
4 – AI security platforms
AI security platforms offer a unified way to protect third-party AI applicationsas well as personalized ones. They centralize visibility, enforce usage policies, and protect against specific AI risks.
Among them, prompt injection, data leaks and the actions of malicious agents. These platforms help IT managers enforce usage policies, monitor AI activity, and implement consistent AI protection measures.
5 – Native AI development platforms
Native AI development platforms use generative AI to develop software faster and easier than until now. The company’s software engineers can use these platforms to work with experts in different subjects to generate applications.
Companies can rely on small groups of people who, with the help of AI, will create more applications with the same level of developers they have today. In fact, there are companies that are already forming small platform teams with the aim that experts in different subjects, but without technical knowledge, can develop software on their own, also counting on security and governance measures.
According to Gartner, by 2030, native AI development platforms will move 80% of companies from large software engineering teams to smaller, more agile teams, complemented by AI.
6 – Confidential computing
Confidential computing changes the way companies manage sensitive data. By isolating workloads into trusted, hardware-based execution environments, you can keep your content and workloads private. Even in front of the infrastructure owners, cloud providers or people with physical access to the hardware. This is especially important for companies in regulated sectors and for global operations that face geopolitical and compliance risks.
By 2029, the consulting firm predicts that more than 75% of operations processed in unreliable infrastructure will be protected during their use, thanks to the action of confidential computing.
7 – Physical AI
The Physical AI brings this technology to the real worldby powering machines and devices that are capable of detecting, deciding and acting. Like robots, drones and smart equipment. Physical AI, therefore, provides quantifiable advantages in sectors where automation, adaptability and security are priorities.
As adoption grows, companies need new skills that bridge technology, operations, and engineering. In addition, their arrival opens up opportunities to improve skills and collaboration, although it may raise concerns about the work, and need change management to be carried out carefully.
8 – Preventive cybersecurity
Preventive cybersecurity is a growing trend, as companies have to deal with exponential growth in threats to networks, data and connected systems. By 2030, preventive solutions will represent half of total security spending, due to the shift from reactive to proactive defense that IT decision makers are addressing.
9 – Digital provenance
Companies are increasingly relying on third-party software, as well as open source and AI-generated content. In this framework, the digital provenance verification It is something essential. Digital provenance is 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 they need to validate and track digital assets throughout the supply chain. For Gartner, those who have not adequately invested in digitally proven capabilities will be exposed to sanctions risks.
10 – Geopatriotism
Geopatriotism is the movement of enterprise data and applications from global public clouds to more local ones. Such as sovereign clouds, regional cloud providers or company data centers, due to the geopolitical risk perceived by organizations.
The cloud sovereigntywhich until not long ago was limited to banks and governments, now also affects companies and entities from different sectors, the number of which is growing as global instability increases.
Thus, by 2030, it is expected that more than 75% of companies in Europe and the Middle East will move their virtual workloads to solutions designed to reduce geopolitical risk. It is an exponential increase, if we take into account that in 2025, the percentage of those who have done so in both regions is less than 5%.
