Friends at IBM published a compelling overview of major areas of focus in the IT landscape for 2026. I found it fascinating and a strong indicator of where the industry is heading. Listed here are the main predictions with short overview.
Multi-Agent Orchestration
No single model will check all the boxes for every need. Work will be split across multiple agents, each specializing in a specific set of tasks. This setup will include a planner agent that distributes the work. It may also include a critique agent to provide constructive feedback.
Digital Labor Workforce
These are digital workers—autonomous agents. They will be integrated into a system capable of parsing a task and then executing a workflow where the result is an action. These systems will also include a human in the loop for:
- oversight
- correction
- strategic guidance
Physical IA
These are models that understand and interact with the world we live in. They perceive the environment, reason about it, and can take physical actions, such as controlling robots. Training is done in simulation, so no manual programming is required. These models learn the physical rules of our world and are called world foundation models. They can also predict what will happen in the environment.
Social Computing
Many agents operate within a social fabric. They understand one another, form intent, and then decide what actions to take based on the environment, context, and other events. A key element is a shared space where they can collaborate and exchange information. This is also referred to as real-world swarm computing.
Verifiable AI
EU IA Act is coming in mid 2026. High risk AI systems must be auditable and traceable. It means few things:
- Tech documentation which demonstrate compliance how models are tested and indetified risks.
- Transparency – users need to know when they interacting with a machine.
- Data Lineage – summarize training data sources and respect copyrights.
Quantum Utility Everywhere
In 2026, quantum computing began solving real-world problems reliably—faster or more efficiently than classical approaches in certain cases. We reached quantum utility scale: systems that work alongside classical infrastructure to deliver value for practical workloads. This hybrid model will increasingly emerge in real-world business operations.
Reasoning at the Edge
These are very small models that can reason. Most frontier models use inference-time compute—reasoning and step-by-step thinking—to work through a problem. Recent developments have shown how to distill that reasoning process into smaller models. As a result, these smaller models can perform well while requiring significantly less compute.
Amorphous Hybrid Cloud
Early models used transformer-only architectures. Later, alternatives emerged, such as state-space models. In 2026, more sophisticated approaches are expected to combine transformers and state-space models. A similar trend will affect cloud hardware: CPUs, GPUs, TPUs (tensor processors), and QPUs (quantum processors). Cloud services will offer ways to mix these compute types to optimize for efficiency and performance.