D://LEAD45AI/ML Training
Teach the team,
not the tool.
Practical AI training for staff: what these tools do well, where they fail, what may safely be put into them, and how to judge the output. It is for organisations whose staff are already using AI and would benefit from doing it well.
THE PROBLEM
Staff are using AI whether or not they have been trained. Untrained use is where the bad outcomes come from.
The cost of leaving this alone is rarely one visible failure. It is the slow accumulation: the workaround that became the process, the thing only one person knows, the renewal nobody questioned.
Our starting point is always the same: establish what is actually true today, then decide what to change. Work scoped against an assumption tends to solve a problem you do not have.
- 01Nobody owns itIt sits with whoever touched it last, which is not the same as being managed.
- 02No current pictureWhat you have, what it costs, and who has access are all slightly out of date.
- 03Only handled when it breaksAttention arrives after the disruption rather than before it.
WHAT YOU GET
What the engagement covers
Scoped before it starts, so you know what is included and what is not.
- 01
Fundamentals
What the technology actually is, in plain language, including why it produces confident wrong answers and why that is a feature of how it works rather than a bug to be patched.
- 02
Role-based sessions
Worked examples from the actual jobs in the room. A finance team and a sales team need different hours, not the same demonstration twice.
- 03
Data boundaries
What may and may not go into a prompt, made concrete with your own examples rather than described in the abstract.
- 04
Verification
How to check output before acting on it, which is the skill that matters most and the one least often taught.
HOW WE WORK
Discover, design, deliver, embed
Four stages with a written output at each one. You always know which stage you are in and what comes next.
- 01Weeks 1 – 2
Discover
We map how the work happens now, including the workarounds people are slightly embarrassed to mention.
- 02Weeks 3 – 4
Design
Options costed against benefit, so the choice is a decision rather than a preference.
- 03Per stage
Deliver
Built in slices that reach production and get used, each with a success measure agreed before it starts.
- 04Post-delivery
Embed
Training, documentation, and a check-in once the novelty has worn off. Adoption is the only measure that counts.
WHAT CHANGES
What you should expect
- Someone other than you owns it, with that written down.
- The current state is documented and stays documented.
- Cost is planned ahead rather than discovered at renewal.
- Decisions are made against evidence rather than assumption.
FAQ
Questions we get asked
01What is AI/ML training?
Practical AI training for staff: what these tools do well, where they fail, what may safely be put into them, and how to judge the output. It is for organisations whose staff are already using AI and would benefit from doing it well.
02Our staff already use ChatGPT. Why would we pay for training?
Because using it and using it well are different, and because untrained use is where the exposure sits. Most people use these tools at a fraction of their usefulness and simultaneously put things into them that they should not. A couple of hours of specific, role-relevant training generally pays for itself in a week and closes the risk at the same time.
03How long does the training take and how is it delivered?
Typically short sessions by role rather than one long all-staff session, because the useful examples differ by job. On site or remote, both work. Follow-up matters more than length: people try things, hit something, and need somewhere to ask. A session with no follow-up tends not to change behaviour.
04What should staff never put into an AI tool?
As a starting point: client-confidential material, personal information about identifiable people, anything covered by a confidentiality obligation, credentials, and unreleased financial information. The list should be specific to your business rather than generic, because a vague rule gets interpreted generously by someone under deadline pressure.
05Will AI training make our staff worried about their jobs?
Some will arrive with that concern whether or not anyone raises it, and pretending otherwise does not help. We find it lands better when leadership is direct about the organisation’s position before the training rather than leaving people to infer it from the fact that training is happening.
06How much does AI/ML training cost in New Zealand?
We quote after scoping rather than before. Anyone pricing this work without looking at your environment is guessing, and the guess is rarely in your favour. Scoping itself is quick, and we tell you what it costs before we start it.
07How long does it take to get started with AI/ML training?
A first conversation takes about half an hour and costs nothing. Scoping is usually a week or two of our time depending on the size of the environment, and we agree the delivery dates with you before anything is booked in.
08Can you deliver AI/ML training alongside our existing IT team or provider?
Yes, and it is common. We are happy to work as an extra pair of hands under your internal team, or alongside an incumbent provider on a defined piece of work. We will set out in writing where the responsibilities split, so nothing falls between us.
09Do we have to be an existing Atlas client to start a project?
No. This can be delivered as a standalone piece of work for an organisation we have never worked with before, or folded into a managed agreement if you already have one with us. Plenty of clients use us for one thing and keep everything else where it is.
10Do you deliver projects outside Auckland?
Our team is based in Auckland and we attend sites across the wider region. Most of this work is delivered remotely, so we support organisations throughout New Zealand, and we will say up front where being on site genuinely matters.
11Who from Atlas will be on the engagement?
Named people, not a queue. You get a lead who knows your environment and stays with it, which is the difference between explaining your business once and explaining it every time you make contact.
12What happens when the engagement ends?
You keep the documentation regardless, and anything registered in your name stays in your name. Whether we stay involved is your call. Some clients take it in house from there, others move it onto an ongoing agreement with us. We would rather you left cleanly than stayed because leaving was difficult.
Start with a conversation.
Tell us what you are dealing with and we will tell you whether this is the right service for it, and what it would take.
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