AI governance and data protection
What is AI Readiness? Definition and examples
Also: AI maturity
In short
AI Readiness describes how well a company is prepared to use AI effectively and responsibly. It is not only about technology but about leadership, data and the ability to change how work gets done.
Why it matters: It shows where the next step with AI pays off most, instead of starting everywhere at once.
Openness to AI
3.94 of 5: the will is there
Adapting structures
2.47 of 5: the lowest item
Why does AI Readiness matter for your company?
Many companies buy AI licences and wait for results. Whether AI delivers depends less on the model than on the organisation: clear goals, usable data and workflows that are allowed to change.
The AI Monitor 2026 shows this clearly. In the DACH analysis of 64 organisations, openness to AI reaches 3.94 of 5. Adapting structures and processes is the lowest item at 2.47: the will is there, the way of working lags behind.
Example: Before the AI budget for 2027
Leadership wants to approve an AI budget for Strategy 2027 and its focus on the DACH mid-market. Every department has its own ideas, from support chatbots to coding agents. Nobody knows where the company stands or what should come first.
An AI Readiness assessment shows the profile: willingness in the team is high, but data is scattered and workflows barely change after a pilot. The budget therefore goes first into usable data and a process that adapts after every pilot, and only then into more tools.
3 common mistakes to avoid
Confusing readiness with licences
Licences for everyone are not maturity. What counts is whether work and responsibility actually change with AI.
Measuring once and forgetting
AI Readiness changes with every project. Measure again after major steps and compare.
Asking only IT
IT sees the technology, not leadership, culture and workflows. Include the leadership team and the business units.
Step by step
- 1
Find your position
Assess honestly where you stand on leadership, data and workflows, for example with a structured check.
- 2
Compare with a benchmark
Compare your profile with other companies, for example with the AI Monitor values.
- 3
Pick the biggest bottleneck
Start where a low score blocks the most value.
- 4
Adapt after every pilot
After every pilot, change at least one workflow, role or approval.
Where does your company stand on AI?
The AI Readiness Check shows in a few minutes where you stand across the six dimensions of the AI Monitor.
Start the AI Readiness CheckRead on in the PM Lab
Articles that go deeper.
Related terms
- AI governance →AI governance is the set of rules a company uses to decide who may use AI for what, with which data and under whose responsibility.
- Shadow AI →Shadow AI is the use of AI tools the company has neither approved nor knows about, such as personal chatbot accounts used for work data.
- Strategy execution gap →The strategy execution gap is the distance between what a leadership team decides and what actually happens in day-to-day work.
- Playbook →A playbook describes a recurring task so that people and AI agents run it the same way: with its knowledge, steps and approvals.