Glossary
What is AI adoption?
AI adoption is the point where people use AI as a normal part of their everyday work, and the business result changes because of it. It is more than access to tools or completed training. Real adoption shows up in how work flows, how decisions are made, and in the numbers the business tracks.
Why AI adoption stalls
Many programs measure adoption by licenses issued or training completed. Usage then drops after the first month, because the tool was designed for an old process and introduced to people at the end.
When people hear AI and think job cuts, trust drains away before any value arrives.
What real AI adoption looks like
Pravv looks for four signals that adoption is real.
- Regular use by the intended teams, on real work.
- Work flowing through the new process instead of around it.
- Managers leading with new routines and measures.
- Movement in the business number the solution was built for.
How to drive AI adoption
Involve the people who will use a solution in designing it. Train them on their own work, not generic examples. Be clear about what changes for each role, and measure adoption against the same Value Case as the solution itself.
Questions
Questions about AI adoption
How do you measure AI adoption?
With usage, process and outcome measures together: who uses the solution, how much work flows through the new process, and whether the business number moves.
Is training enough to drive adoption?
No. Training helps, but adoption depends on whether the solution fits the work, whether managers lead the change, and whether people trust what it means for their role.
Who is responsible for AI adoption?
The business leaders whose teams use the solution, supported by HR and technology. Adoption is a leadership task, not an IT task.
Let's find your Value Case
A conversation with a senior partner. We'll bring a view of where AI could move your numbers.