These are seven AI trends to watch in the next year

– This transformation is visible everywhere. In medicine, AI will help close the care gap. In software development, not only code, but also and the context behind it. In scientific research, he becomes a true laboratory assistant. In quantum computing, new hybrid approaches herald advances that were once considered impossible – it is stated.

As AI agents become digital colleagues and take on specific tasks under human guidance, organizations are strengthening security to keep up with new risks. The infrastructure that drives these advances is also maturing, becoming smarter and more efficient.

These seven trends to watch in 2026 show what’s possible when humans join forces with AI:

AI will amplify what people can achieve together

Microsoft sees 2026 as a new era of alliance between technology and people. If the past years were devoted to AI answering questions and solving problems, the next wave will be focused on real collaboration between AI and humans.

AI agents are ready to become digital collaborators that help individuals and small teams. Microsoft experts envision a working environment in which a three-person team can launch a global campaign in a few days, with AI processing data, generating content and personalization, and humans managing strategy and creativity. Organizations that design ways for people to integrate and work with AI will get the best of both worlds, helping teams tackle more creative challenges and deliver results faster.

AI agents will receive new safeguards as they become part of the workforce

In 2026, AI agents will be increasingly used and play a greater role in everyday work, becoming more collaborators than tools. As organizations rely on agents for helpć in tasks and decision-making, building trust in them will be key – starting with safety.

Microsoft suggests that each agent have similar security protections as humans, to ensure that agents do not become “double agents” carrying uncontrolled risk.

This means giving each agent a clear “identity”, limiting the information and systems it can access, managing the data it creates, and protecting against attacks and threats. Security will become autonomous and built-in, not something that is added later. In addition, as attacks use AI in new ways, the other side will simultaneously use security agents to detect these threats and quickly respond to security challenges.

AI is poised to reduce the global health self

AI in healthcare marks a turning point. In the years to come, we will increasingly see evidence that AI goes beyond diagnostics and expands into areas such as symptom detection and treatment planning. It is important to emphasize that further progress is moving from research environments into the real world, with new generative AI products and services available to millions of consumers and patients.

This change is important because inadequate access to health care is a global crisis. The World Health Organization predicts a shortage of 11 million health workers by 2030, which means that 4.5 billion people remain without basic health services.
The achievements are greater. demonstrated in 2025 through Microsoft AI’s Diagnostic Orchestrator (MAI-DxO), which solved complex medical cases with 85.5% accuracy, far above the average of 20% for experienced doctors. AI advances are a way to give people more influence and control over their own health and well-being.

AI will become a central part of the research process

AI moreć accelerates breakthroughs in areas such as climate modeling, molecular dynamics and material design. But the next leap is yet to come. In 2026, AI will not only summarize papers, answer questions and write reports, but They will actively participate in the discovery process in physics, chemistry and biology.

AI will generate hypotheses, use tools and applications that control scientific experiments, and collaborate with human and AI research colleagues.

This change creates a world in which everyone would research could soon have an AI laboratory assistant who can propose new experiments, and even conduct part of the experiment. It is a transformation that promises to accelerate research and change the way scientific discoveries are made.

AI infrastructure will become smarter and more efficient

The growth of AI is no longer only about building ever-larger data centers. The next wave refers to the utilization of each unit of computing power.

The most efficient AI infrastructure will concentrate computing power through distributed networks. Next year will bring the rise of flexible, global AI systems, a new generation of connected AI “superfactories” that will reduce costs and improve efficiency.
AI will be measured by the quality of the intelligence it produces, not just by its size.

Think of it as air traffic control for AI workloads: computing power will be more tightly distributed and dynamically directed so that nothing sits idle. If one job slows down, the other immediately steps up, ensuring that every cycle and watt of energy is optimally used.

AI learns the language of the code and the context behind it

Software development is experiencing great growth, and activity on GitHub will reach new levels in 2025. Every month, developers submitted 43 million pull requests, which is a 23% increase compared to the previous year. The annual number of “commits”, which follow these changes, jumped 25% to 1 billion. This unprecedented pace signals a sea change in the industry as AI becomes increasingly important in the way software is built and improved.
These data confirm that 2026 will bring a new advantage. Simply put, it means AI that understands not only lines of code, but and the relationships and history behind them.
By analyzing patterns in code repositories, the central places where teams store and organize everything they build, AI can figure out what changed, why, and how the pieces fit together.

The next leap in computing is closer than most people think

Quantum computing has long looked like science fiction. But research is entering an era of years, not decades, in which quantum machines will begin to solve problems that classical computers cannot. This breakthrough, called quantum advantage, could help solve the most difficult social challenges.

What is different now is the rise of hybrid computing, where quantum works alongside AI and supercomputers. AI finds patterns in data. Supercomputers run massive simulations. And quantum computing adds a new layer that will enable far greater precision in modeling molecules and materials.

The quantum advantage will drive breakthroughs in the development of new materials, medicine and more. The future of AI and science will not only be faster, but also It will be fundamentally redefined.