Custom AI training for teams that need to use AI safely, consistently, and productively across their real workflows.
Tools got bought. Usage didn't follow, and no one can say why.
A few people have figured it out informally. Most haven't, and there's no shared method.
No baseline was set before rollout, so there's nothing to point to when asked if it worked.
No tools, no plan, and AI feels like it's moving too fast to catch up on. That's a starting point too.
Drafting, summarising, and first-pass analysis move off the manual list.
Output quality stops depending on who happened to write it.
Teams know what may be entered into a tool, and what needs review first.
Managers get a record of what's actually being used after the sessions end.
The same record HR and L&D can attach to an internal report or a participant's own development file. Below is a specimen — the real design is finalised during scoping.
Specimen shown for illustration. Recipient name, programme title, and signatory are set per engagement.
Strategic readiness: is the organisation actually prepared to run on AI, paying for it and not using it, or still deciding where to begin.
Capability development with evidence of learning you can report on internally.
Approved tools and data handling rules — whether governing what's already in use, or setting the policy from zero — fit to your review process.
Workflow change within finance, sales, HR, operations, or procurement specifically.
| Format | Best for | Typical structure |
|---|---|---|
| Focused workshop | One team or department | Live, hands-on session |
| Multi-week programme | Distributed or hybrid teams | Sessions plus applied work |
| Organisation-wide rollout | Several departments | Shared foundation plus specialist tracks |
| Reinforcement | Sustaining adoption | Recap lessons, templates, check-in |
Every programme starts from a shared foundation, then branches by function. This is the shape; the real agenda is built during scoping.
We establish the baseline before training and measure the change afterwards. Four steps, in order, every time.
A discovery call maps your teams, current AI usage, and a baseline for the target tasks.
Sessions delivered against your team's real work, not generic examples.
Employees put the training to work on live tasks during and right after delivery.
An adoption check-in compares usage and time saved back to the baseline.
Actual figures are set per engagement during scoping, using your team's real numbers rather than assumed ones.
Baseline: hours per week currently spent on the target tasks, across the team.
Post-training: hours per week on the same tasks after delivery, measured at the adoption check-in.
Result reported: hours returned per week, plus a note on which tasks shifted and which didn't.
This is reported as a short document your team can bring to a budget conversation, not a headline percentage.
Tell us your sector, then answer six questions across the same pillars we use in the Assess step of the Coursus Method: strategy, governance, data, usage, skills, and measurement. Get a readiness score before you book a call.
The tools taught are the tools your organisation has actually cleared.
Sensitive data is never pasted into a tool that isn't fit for it.
Outputs get a sign-off step where the work calls for one.
Training is scoped around your current IT and compliance workflow, not around ours.
A downloadable document covering data handling, tool approval process, and review requirements in full, for your IT and compliance teams. Available on request during scoping — ask on your discovery call.
Pricing depends on team size, functions covered, and delivery format. You get a fixed proposal after the scoping call, not a generic per-seat rate.
Yes. A foundations engagement starts from tool selection itself, before any team-specific workflow work begins. You don't need existing licences or in-house usage to start scoping a programme.
Yes — that's the default. Every programme starts with a shared foundation module, then branches into function-specific tracks.
We've scoped single-department programmes and multi-function rollouts. Tell us your team size on the discovery call and we'll be direct about fit.
From a single-day foundations workshop to a multi-week rollout with follow-up sessions. Timeline is set during scoping around your calendar.
Sessions use your real work as material, so confidentiality is addressed during scoping before any content is shared.
This is the Measure step of the Coursus Method: a baseline is agreed before delivery, then a scheduled adoption check-in afterward compares actual usage and time saved against it.
Standard scoping documentation and, where required, the Responsible AI Training Scope document covering data handling and review requirements.
Tell us about your team, current AI usage, and the workflow you want to improve.
Book a Discovery Call →No commitment from the discovery call. We'll only send a proposal if it's a genuine fit.
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