Microsoft has made a forecast for the development of AI technologies for 2026. Researchers believe that the role of artificial intelligence may change from a tool to a «colleague».
Microsoft has made a forecast for the development of AI technologies for 2026. Researchers believe that the role of artificial intelligence may change from a tool to a «colleague».
«In various industries, AI is moving from simple answers to interacting with people, amplifying their expertise. In medicine, it is helping to close the gap in access to services. In software development, it understands not only code, but also context. In scientific research, AI is becoming a true assistant in the laboratory. In quantum computing, new hybrid models are opening the way to breakthroughs that until recently seemed unattainable,» the Microsoft report says.
Researchers have identified seven key AI development trends for the coming year.
Microsoft sees 2026 as the beginning of a new era of collaboration between people and technology. AI agents will become digital colleagues who will help individual specialists and small teams. Microsoft experts predict that a team of three people will be able to launch a global campaign in a few days: AI will process data, generate content and personalize communications, while humans will form the strategy and creative idea.
Organizations that create processes so that people can learn and work alongside AI will see the best results—their teams will solve more complex problems faster.
By 2026, the number of AI agents in the workplace will increase significantly. They will perform more tasks and act more like team members than tools. As their role increases, so will the need for trust in them, primarily for security reasons.
Microsoft believes that every AI agent should receive protection similar to that provided to humans: clear identity, access control to information and systems, data rules, and resistance to attacks.
Security will become built-in and autonomous, not an optional extra. And just as attackers use AI to launch new types of attacks, defenders will use «security agents» that can respond much faster.
AI in medicine is entering a pivotal phase. Its capabilities extend far beyond diagnostics to areas such as initial symptom triage and treatment planning. Progress is moving beyond the labs, with generative AI solutions becoming available to millions of patients.
This is especially important against the backdrop of a global health care access crisis. According to WHO forecasts, the world will face a shortage of 11 million health workers by 2030 — that’s 4.5 billion people without basic health care.
AI could be the key to wider access to quality medicine and help people take better control of their own health.
AI is already accelerating progress in climate modeling, molecular dynamics, and the design of new materials. By 2026, AI will not just generalize knowledge, but will become a full participant in scientific research in physics, chemistry, and biology.
AI will generate hypotheses, manage some of the scientific experiments, and interact with scientists and other AI agents. Each researcher will be able to have a digital «laboratory assistant» who suggests new experiments and even conducts certain stages of the research.
The most advanced AI infrastructures will operate in tightly connected distributed networks. 2026 will mark the emergence of agile global systems—a new generation of interconnected, powerful AI computing clusters (AI superfactories) that will reduce costs and increase efficiency.
AI will be judged not by scale, but by the quality of results. In a central AI load management center, where power is dynamically distributed, no resource is idle, and each cycle works for the result.
Software development is experiencing an unprecedented boom. In 2025, activity on GitHub reached record levels:
According to Microsoft researchers, this pace signals profound changes in the industry: AI is becoming a key tool for creating and optimizing software solutions.
The volume of data opens up a new opportunity: AI begins to understand not only lines of code, but also the connections, history and logic of systems. By analyzing repositories — central hubs where all developments are stored. AI will be able to determine what has changed, why it happened and how the elements of the system interact.
Quantum computing has long been a fantasy. But researchers are entering a phase of «years, not decades,» when quantum systems will be able to solve problems that classical computers cannot. This moment is called quantum supremacy.
The breakthrough was made possible by the development of hybrid computing, in which quantum systems work together with AI and supercomputers. AI finds patterns, supercomputers run large-scale simulations, and quantum technologies enable unprecedented precision in modeling molecules and materials.
