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Definition
What is AI Adoption?
AI Adoption is the degree to which AI capabilities are actually used by intended users within an organization. It's the ultimate measure of AI implementation success—deployment without adoption is failure.
Deployment vs. Adoption
Many organizations confuse deployment with success. They roll out AI capabilities, declare victory, and move on. Months later, they discover no one is actually using the system.
Deployment means the system is available. Adoption means people are using it. The gap between these is where most AI initiatives fail.
Measuring AI Adoption
Key metrics to track:
- Active users: How many people use the system regularly?
- Usage frequency: How often do they use it?
- Usage depth: Are they using basic or advanced features?
- Retention: Do people keep using it over time?
- Net promoter: Would users recommend it to colleagues?
Why Adoption Fails
- Users weren't involved in implementation decisions
- Training was insufficient or poorly timed
- The AI doesn't fit existing workflows
- No champions to drive peer adoption
- Feedback mechanisms are missing or slow
Related Concepts
- Change Management — The discipline that drives adoption
- AI Change Management Guide — Practical strategies
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