AI training for Australian teams
Most AI training is a demo, and demos change nothing
Someone shows the room an impressive thing on a screen. Everyone nods. Two people try it that afternoon, both hit something that does not work, and by Friday the organisation is exactly where it was.
Our sessions are built the other way round: we start from the tasks your people already do, and we spend most of the day with them doing those tasks differently, on their own work, with us in the room when it breaks.
What is different afterwards
We write outcomes as things a person can be observed doing, not topics that were covered. If we cannot phrase it that way, it does not go in the day.
Someone in your finance team turns a spreadsheet export into a written variance summary in ten minutes instead of an hour, and knows which numbers to check before sending it.
A client-facing staff member drafts a difficult email, then edits it, rather than sending the first output or writing from scratch at 6pm.
Your operations lead can say which of five proposed use cases is worth piloting and which is a bad fit, with reasons.
Everyone in the room knows what must never be pasted into a consumer AI account, and why, without having to look up the policy.
How a day is spent
Framing
What these tools are, where they fail, and the specific ways they fail that matter for your work.
Hands on their own work
Not exercises we invented. Real documents, real emails, real spreadsheets they brought.
Governance in practice
What goes in, what never does, what has to be checked before it leaves the building.
What happens Monday
Each person leaves with two specific things to try and a way to tell whether it helped.
The 55% is the whole point. It is also the part that makes group size matter, because it needs someone circulating.
Questions
Usually the opposite. Unmanaged adoption is where the risk sits — client data pasted into consumer accounts, output used without checking, and a couple of people quietly doing everything while the rest are afraid to start. A session that surfaces what is already happening is often the most valuable one we run.
Not at all. Nobody writes code, there is no maths, and we do not explain how transformers work. It is about the tasks your people are already responsible for and where a model does or does not help with them.
Best between eight and sixteen. Under eight and the exercises lose their spark; over twenty and it becomes a lecture, which is the format least likely to change what anyone does on Monday.
Some will, some will not, and the difference is mostly whether their manager expects it. Training changes capability, not priority. We are blunt about this in the scoping conversation because a workshop cannot fix a team that has no permission to change how it works.
Yes, and we would rather. If you have Copilot licences across the business, a session on Copilot in the apps people already have beats a generic AI overview by a distance. Tell us what you own.
That is a separate piece of work, but the workshop surfaces most of what a policy needs to cover, so doing them in that order tends to produce a better policy and a cheaper one.
Before you book anything
Tell us who is in the room and what they do all day. If the answer suggests a workshop is not the right intervention — and sometimes it is a tooling problem or a permission problem, not a skills one — we will say so.
Talk about your team