AI Implementation
You’ve had the AI training. Now for the real-life application.
We train reps, MSLs and brand teams on their own work, on the tools you’ve approved, inside your rules. Then, where it makes sense, we build agents.
- The tools you’ve approved
- Your SOPs and AI policy
- Your review route
- A named person who signs off
We work inside it.
Why AI use can stall after the training.
In our experience, people haven’t seen what good looks like on their own work.
Global chose the tool. IT locked it down. Legal wrote the policy. Head office ran the training, and it covered the basics. Then everyone went back to a full calendar and an inbox, and AI stayed something extra to learn.
Fixing that takes someone who has done the job. We sit with your people, watch how they work, and find the parts of their week that AI can take off their hands today, with the tools they already have.
And we work inside your box. If global says Copilot only, we train on Copilot. If your rules keep something out of AI, it stays out.
Three phases. Stop after any of them.
Discovery Sprint
3 to 4 weeks
6 to 12 one-on-one interviews with reps, MSLs and marketers, on screen where they’re comfortable, so we see how they work. You get a map of where AI helps each team, a findings presentation and a clear go or no-go.
Curriculum Build
3 to 4 weeks
A foundation module, modules for each business unit, and a prompt library indexed to the jobs people do. Everything is built on your tools and reviewed for your therapeutic area before delivery.
Delivery and Support
60 to 90 days
Hands-on sessions where people run prompts on their own work. Then weekly office hours, because the questions in week three differ from the questions in week one. Optional AI Champions keep it going after we leave.
Each phase is scoped and contracted separately, at a fixed price.
Where each team usually starts.
Reps
Call prep, recaps, and practice on the hard objections before the call instead of during it.
MSLs
Congress papers turned into briefing notes, prep before KOL meetings, and post-meeting documentation.
Brand teams
Message variants, competitive monitoring and first-pass checks against your claims list, before anything enters review.
When it makes sense, we build agents.
Once a team is comfortable with the tools, an agent can be the next step. Every agent we scope has a named owner and a person who signs off.
These are examples we can scope with you. Some we have built and others are concepts. Every agent runs inside your approved tools. Adverse events go to your safety process, never to an agent.
“What has stood out most is their practical, business-focused approach to AI adoption, not simply providing theory and guidance but creating real tools and strategies based on our own data and internal systems to improve efficiency, sales visibility, and customer engagement.”
Want a quick read on your team first?
Take the 60-second AI Literacy CheckThe questions pharma teams ask first.
Our company only allows Copilot. Can you still help?
Yes. We’ve worked under that limit before. We train on the tools you’ve approved and build agents inside them. You won’t be asked to buy another tool.
We’ve already run AI training. Why do this?
First-round training often teaches the tool. This starts from the job, with the people doing it, and stays for 60 to 90 days afterwards. If your first round worked, the Discovery Sprint will show that, and you can stop there.
Global runs our AI. What can a Canadian team do on its own?
More than you’d think, inside the tools you already have. Before anyone builds anything, we work out with your team what your policy allows.
Who reviews the training materials?
Your team does. Materials are reviewed for therapeutic area and brand safety before delivery, and they go through whatever internal route your company requires.
Do you need our data or patient data?
We work inside the tools your IT team has approved, and we don’t need patient data. If your rules keep something out of AI, it stays out.
How do you measure whether it worked?
We agree the measures in Phase 1, usually who is using the tools, how often, and for which jobs. Your usage data and interviews at the end show what changed.
Bring one real workflow to the call.
Tell me one job your team does every week. In 30 minutes we’ll work out whether AI can take it on inside your rules, with the tools you already have.