Where Can My Team Get Practical AI Training for Work?

If your team has AI tools but isn't really using them to change how the work gets done, the answer isn't another tool, it's practical training. You can get it from a few places: a self-serve course, a live workshop, an internal champion, or a managed training partner that runs a programme around your team's actual tools and workflows. The right choice depends on your team's size, urgency, and how hands-on you need it to be. This guide walks through the options and how to tell practical AI training from the generic kind.

The hard part isn't access to AI. It's turning access into people who confidently use it every day, which is exactly where most training falls short.

Watch: for why this gap matters now, see How to Get Ahead of 99% of Businesses With AI.

What "practical" AI training actually means

Most AI training isn't practical. It's a lecture on what large language models are, a tour of prompts, and a certificate at the end, after which everyone goes back to working exactly as before. Knowing about AI and using it in your job are different things, and only one of them changes results.

Practical AI training has a few non-negotiable traits. It's hands-on, people do real work in the session, not watch slides. It's built around your team's actual tools and workflows, not generic examples. It's function-specific, because what a marketer needs from AI is not what a finance lead needs. And it's measured by work changed, not courses completed. McKinsey's State of AI research found that most organisations now use AI somewhere, yet the large majority still see no real bottom-line impact, and the thing that most separates the two is redesigning how the work is actually done. Training that doesn't touch real workflows doesn't move that needle.

If a programme can't tell you what your team will be able to do differently on Monday, it isn't practical.

Your options for getting AI training

There are four realistic ways to get AI training into a team, each with trade-offs.

Build it in-house. If you have an AI-savvy person willing to teach, this is cheap and tailored. The catch is that they have a day job, the material goes stale fast as tools change, and one person rarely covers every function well.

Generic online courses. Plentiful and inexpensive, good for foundational awareness. The downside is they're self-serve and generic, so completion rates are low and almost nothing transfers to your specific tools and tasks.

One-off live workshops. A live, hands-on session creates momentum and gets people building something real on the day. On its own, a single workshop rarely embeds a lasting habit, so it works best as a start rather than the whole answer.

A managed training partner. A provider that runs an ongoing programme around your team's tools, functions, and real use cases. It's the most involved option, but it's the one most likely to actually change how the team works, because it combines live delivery, your real workflows, and follow-through.

For a deeper look at what separates a programme that sticks from one that doesn't, our guide to AI training for employees breaks it down.

How to choose: a quick checklist

Whichever route you lean toward, judge any option against the same questions. Good practical AI training is:

• Practitioner-led, taught by people who automate their own work, not career trainers reading a deck.

• Built around your tools, your actual stack and workflows, not a generic curriculum.

• Function-specific, with separate, relevant tracks for marketing, sales, operations, and finance.

• Hands-on and live, where people do real work and leave with something built.

• Outcome-focused, measured by what the team can now do, not by attendance or completion.

• Kept current, because the tools change monthly and last year's material is already dated.

If an option ticks most of these, it'll likely change how your team works. If it ticks few, you'll get a certificate and little else.

What practical AI training looks like at 9x

This is the gap we built 9x to close. We're operators who automated our own workflows and ran an automation agency before we taught anyone else, and we've now trained over 20,000 professionals, most of them complete beginners, at companies like Make, Perk, and Project A. As our co-founder Jan puts it, "AI skills are the most important skills a business professional can learn right now, and it shouldn't be left only to engineers."

The programmes are built to be practical by design. Teams learn on their own tools and real use cases, by function, in live sessions, and the measure is work changed rather than courses finished. Depending on what you need, that can look like the free AI Starter course to get people off the ground, public cohorts for individuals, hands-on workshops, or a managed track that takes a whole team from AI literacy through to building their own automations. You can see what teams say about it on our wall of love, and how we think about rolling AI out across an organisation in companies don't adopt AI, people do.

The throughline is simple: we don't teach people about AI, we change how they work with it.

What a practical programme actually involves

It helps to know what "practical" looks like in delivery, not just in principle. A programme that sticks tends to follow a shape: it starts people on the fundamentals, gets them confident with the AI tools in their actual stack, then moves into building, automating real workflows and saving them as reusable skills the team keeps. The sessions are live and hands-on, people bring a real task and leave having done it, and the tracks differ by function, because a marketer and a finance lead need different things from the same tools.

Two details separate a programme that changes behaviour from one that doesn't. The first is follow-through: a single workshop creates a spark, but it's the ongoing cadence, office hours, a community, a place to ask when you're stuck, that turns a spark into a habit. The second is currency. These tools change monthly, so any worthwhile programme is being updated constantly; last year's material is already out of date. When you're weighing options, ask how recently the curriculum was revised and what happens in week three, not just on day one.

Questions teams ask about AI training

How much does AI training for a team cost? It varies with format, from free self-serve courses through paid cohorts to a fully managed programme priced on team size and scope. The better question is cost against outcome: training that changes how people work pays for itself quickly, while a cheap course nobody applies costs more than it looks.

Online or in person? Live and hands-on matters more than the room. Remote sessions where people do real work on their own tools beat in-person lectures, and a good programme is mostly live delivery plus follow-up, whichever way it's hosted.

How long does it take? A single workshop creates momentum in 60 to 90 minutes; building a lasting habit across a team is a programme over weeks, not a one-off.

How do we measure it? By work changed, not courses completed. Look for tasks people now do differently and time given back, not attendance or certificates.

Get practical AI training for your team

If your team has the tools but not the habit, practical training is the missing piece, and the right format depends on your size, urgency, and how much hands-on support you need. Use the checklist above to judge any option, and don't settle for anything that can't tell you what your team will do differently afterwards.

If you'd like to see what a practical, hands-on programme would look like for your team, book a quick call and we'll scope it with you in 30 minutes.