In 2026, artificial intelligence (AI) will evolve from a tool into a partner in the workplace and in personal life. We are already seeing how useful it is in a variety of fields - from medicine to software development. For the coming year, technology giant Microsoft outlines 7 factors that will improve the work of AI.
1. People will achieve better results using AI.
If the past years were dedicated to AI answering questions, the next stage will be about true collaboration.
Experts predict that a team of three people could launch a global campaign in days. In it, AI processes data, generates content and personalization, and humans drive strategy and creativity.
Pro tip: Don’t compete with AI, focus on how to work alongside it. Next year belongs to those who elevate the role of humans, not eliminate them.
2. AI agents will receive new safeguards as they join the workforce.
By 2026, AI agents will become widespread and play a greater role in everyday work, acting more as teammates than as tools. Building trust in them will be essential – starting with security.
3. AI is poised to close the gap in global healthcare.
AI in healthcare is reaching a tipping point. We will see evidence of AI going beyond diagnostic expertise and expanding into areas such as symptom assessment and treatment planning. Importantly, advances will begin to move from the research community into the real world, with new generative AI products and services available to millions of users and patients. This shift is important because access to healthcare is a global issue. The World Health Organization predicts a shortage of 11 million health workers by 2030 – a deficit that will leave 4.5 billion people without essential health services.
4. AI will take center stage in research.
AI is already accelerating breakthroughs in areas such as climate modeling, molecular dynamics, and materials design. But the next leap is yet to come. In 2026, AI will not just abstract scientific papers, answer questions, and write reports; it will actively engage in the discovery process in physics, chemistry, and biology.
AI will generate hypotheses, use tools and applications to manage scientific experiments, and collaborate with both humans and other AI colleagues. This shift is creating a world in which every research scientist could soon have an AI lab assistant to suggest new experiments and even perform parts of them. It’s a transformation that promises to accelerate research and change the way scientific discoveries are made.
5. A smarter, more efficient AI infrastructure.
AI development is no longer just about building more and bigger data centers. The next wave is about making the most of every unit of computing power.
The most efficient infrastructure for AI will pack computing power more tightly into distributed networks. Next year will see the rise of agile 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 its scale. Think of it like air traffic control for AI workloads: computing power will be packed more tightly and dynamically routed so that nothing sits idle. If one task slows down, another one will be instantly switched on, ensuring that every cycle and every watt is put to work.
6. AI learns the language of code and the context behind it.
Software development is booming, with activity on GitHub reaching new heights in 2025. Every month, developers merged 43 million pull requests, a 23% increase from the previous year. The annual number of commits that track those changes jumped 25% year-over-year to 1 billion. The unprecedented pace signals a major shift in the industry as artificial intelligence becomes increasingly central to how software is created and improved.
The sheer volume is why 2026 will bring a new advantage. In simple terms, that means AI that understands not just lines of code, but the relationships and history behind them.
7. The next leap in computing is closer than most people think.
Quantum computing has long felt like science fiction. But researchers are entering an era measured in years, not decades, in which quantum machines will begin to tackle problems that classical computers cannot. This breakthrough, called “quantum advantage,” could help solve society’s toughest challenges.
What’s different now is the rise of hybrid computing, where quantum systems work together with AI and supercomputers. AI finds patterns in data. Supercomputers run large-scale simulations. And quantum computing adds a new layer that will enable much greater precision in modeling molecules and materials.