Don't just decide faster. Make decisions stick.

AI makes people faster. It researches, analyses, writes, codes and tests. So the question for every leadership team is no longer whether you use AI, but: who makes the company faster?

The AI Monitor 2026 gives an empirical answer. It measures six preconditions for using AI: leadership, people and capabilities, technology foundations, data, external conditions and adaptability. The pattern is clear. Openness to change is the highest score in the study at 3.94 of 5, adapting structures and workflows the lowest at 2.47. People are ready. Their workflows aren't. Many organisations bolt AI onto existing workflows instead of changing the foundation.

The DACH analysis of 64 organisations also shows where the advanced profile pulls ahead. Three differences are especially telling for daily work: data (4.11 versus 2.31), people and collaboration (4.53 versus 2.73) and adaptability (4.13 versus 1.84), the largest gap of all six dimensions. The advanced organisations change their workflows. The others bolt AI on top.

Along the way we noticed something: AI agents need the same things as people. Access to current, reliable information. Orientation on what matters right now. And the ability to turn what was learnt into new work. If one of them is missing, every day starts from zero, everyone pulls in a different direction, and what was learnt yesterday does not change today's work.

From this we derive three practices. Shared Context: connect trusted sources so that people and agents start from the same current picture. Company Brain: connect daily work to shared goals and decisions so that priorities are clear. Playbook: approve changes, write them back to the source and review what works. Only this last step turns learning into adaptability. Learning only counts once it changes how people and agents work.

Why this is a competitive advantage: any company can buy models and tools, and they get better every year. What cannot be bought is your own current context, your shared direction and the pace at which learning flows back into the sources. Every approved change improves the next decision and every agent that works from that source. This lead grows with every cycle and is hard to copy. That is our interpretation as publisher; the study measures readiness, not business success.

This edition makes the results accessible. You can explore the six dimensions, compare readiness profiles and trace what individual statements rest on. The data offers orientation. The self-assessments do not replace an examination of your own workflows.

Our invitation: think of one important decision from the last three months. Do you know whether everyone works by it today, your AI agents too? Don't just decide faster. Make decisions stick.