AI Fluency
Two halves of the same job:
govern it, then land it.
AI Fluency is a governance framework and an adoption programme, run together. The objective is an environment that is efficient and secure — not one traded for the other.
What we observe
10–20%
of licensed users actively use Copilot, Claude or similar tools in their daily work.
Typical root cause: one generic training, then silence.
Two components
Governance makes it safe. Adoption makes it stick.
Run on their own, each one fails in a predictable way. A governance framework nobody adopts is a document. Adoption without guardrails is an incident waiting to be written up.
AI Governance Framework
Safe to scale, from the first use case
Before people are told to use AI on real work, it has to be clear what they may use, on which data, and who signs off on anything new. We put that framework in place first — not as a policy document, but as controls inside the tools themselves.
- Data-access controls by role, so AI only ever sees what that person could already open
- Acceptable-use standards written to be followed, not filed
- Security review of connectors, agents and the data they reach
- An approval path for new use cases, so the pipeline never stalls waiting for a decision
- Monitoring of what is used, by whom, and against which data
- Responsible AI principles built into the framework: safe, fair and transparent use, with a human in the loop on decisions that need one
AI Adoption
Fluency that outlasts the training
With the guardrails in place, adoption becomes a question of habit rather than permission. We teach by role on real work, build one painful workflow per team into something automated, and leave a trained champion behind in each function.
- Baseline AI readiness by role and current tool usage
- Short, role-specific fluency sessions on the work people already have
- Use-case workshops that turn one workflow per team into a working automation
- A trained champion in each function to hold momentum
- Active usage and time saved, reported back to leadership
The objective is a working environment that is both efficient and secure. Most programmes pick one.
The difference that matters
AI training ends. AI fluency compounds.
Same budget line, very different outcome. The column on the right is what we deliver.
AI training
AI fluency
Generic, tool-focused content
Built around each function and its daily work
One session, then nothing
Hands-on sessions plus weeks of handholding
Practice on sample prompts
Practice on their real files, emails and reports
Success = attendance
Success = active usage and time saved
Knowledge fades in two weeks
Habits, champions and use cases that stick
How we drive adoption
We implement Copilot and Claude, then make sure people use them.
Rollout is the easy half. What follows it is what decides whether the licenses earn anything back.
What we implement
- Microsoft 365 Copilot rollout and governance
- Copilot Studio agents for business departments and domains
- Claude for Enterprise setup, Projects and connectors
- Use-case design tied to real workflows
- Usage, security and data-access guardrails
Step 1
Assess
Baseline AI readiness by role: current tools, data access, and the tasks that eat the most time.
Step 2
Teach by role
Short, role-specific sessions. What to know and what to do, on the work people already have.
Step 3
Build with them
Workshops turn one painful workflow per team into a working prompt, agent or automation.
Step 4
Champions
A trained champion in each function keeps momentum after we step back.
Step 5
Measure
Active usage, time saved, and use cases in production — reported back to leadership.
Introductory session · no cost
Start with the free session. Ninety minutes.
A live session for your leadership team covering what AI is, what fluency actually means, what is real in 2026, and what to do on Monday. We include 10 hours of adoption consulting with it.
What you get
90
minutes, live, with your leadership team
10
hours of AI adoption consulting, included
Listed value $1,250. Offered free to introduce how we work.
Start with one team, one workflow.
Pick the function where the tools are least used. We will baseline it, teach to it, and show leadership what changed.