AI capability building
Awareness is easy.
Everyday skill is the work.
Most AI training teaches people what AI is. Capability is whether they use it on Monday, in their own work, and use it well. Amit designs programmes for the second one.
Literacy isn't capability.
AI literacy
Knowing what AI is.
- Generic courses for everyone
- Measured by completion
- Little changes on Monday
AI capability
Using it in your own work.
- Built around real tasks in each role
- Measured by daily use and time saved
- Changes how the work gets done
High course completion can sit right next to flat daily usage.
When official training doesn't help with the real job, people find their own tools. That's how unapproved AI spreads.
From awareness to mastery.
- AwarenessShared vocabulary and safe-use rules
- LiteracyHow models work, and where they fail
- CapabilityRole-specific use on real work
- MasteryRedesigning work around AI
How a capability programme gets built.
Start with the work, not the course catalogue.
Assess roles before training anyone.
Find the roles where AI can change the most work, and start there rather than with an enterprise-wide course.
Pick three to five real tasks per role.
Name the actual work, such as a weekly report or a first contract draft, not a generic goal like using the chatbot more.
Train on the team's own deliverables.
Practice happens on real work with approved tools, so what's learned on the day gets used the next morning.
Grow champions inside each team.
Early adopters become peer coaches who keep the practice going after the programme ends.
Measure behaviour, not completion.
Track daily use, time saved and the quality of AI-assisted work instead of hours of training.
Questions people ask.
What is the difference between AI literacy and AI capability?
AI literacy is knowing what AI is and how it works. AI capability is the applied, role-specific skill of using it to do real work better. Literacy is the foundation. Capability is where the value shows up.
Why doesn't generic AI training change how people work?
Because it isn't tied to the person's actual tasks. Without clear use cases in their own role, people default to low-value requests, get unremarkable results and stop.
How do you measure AI capability?
By behaviour: how many people use AI in their daily work, how much time it saves on specific processes, and the quality of the work it helps produce. Course completion measures attendance, not capability.
Where this connects.
Building AI capability across your organisation?
Role-based programmes, workshops and masterclasses built around your teams' real work.