Practical AI training.

The shadow AI problem

In most SMEs, AI adoption has already happened. It happened informally, through individuals pasting work into free tools on personal accounts, without guidance on what is safe to share and no record of what has been shared.

Banning it does not work and would not be desirable if it did. The realistic position is to make the use deliberate: give people the tools officially, show them what these systems are genuinely good and bad at, and be explicit about what must never be pasted into them.

What the training covers

We start with what these tools actually are, because most misuse comes from misunderstanding. A language model is not a search engine and not a calculator, and knowing the difference explains most of the ways people get burned by one.

From there it is applied: writing instructions that produce usable output, tasks worth handing over and tasks worth keeping, how to check what comes back, and how to build small automations that remove recurring admin without needing engineering support. The examples come from your work, not from a generic slide deck.

Safe use with company information

The practical rules are narrower and more learnable than most people expect. What can go into a general-purpose tool, what needs an enterprise agreement, and what should never leave your systems at all. Where you already hold Microsoft 365 licences, there is often a compliant option available that people simply do not know they have.

We cover the traps that matter in practice: client confidentiality, personal data under GDPR, and the difference between a consumer account and one covered by a data processing agreement.

EU AI Act readiness

The EU AI Act phases obligations in through 2026 and 2027, and its reach depends on how you use AI rather than whether you build it. Most Irish SMEs fall into lower-risk categories, but there are still obligations around transparency, record-keeping and staff AI literacy.

We cover what applies to your situation in plain terms, so the compliance question is answered before it becomes urgent, and so you can evidence that your staff have been trained.

How it runs

Sessions are built around your team and your processes. That means a short discovery conversation first, so the examples used are ones your people recognise, and so the time is spent on the tools they will actually reach for.

It works well as a standalone engagement and well alongside process or automation work, where it helps the change stick. Training that follows an automation project tends to land harder, because people have just seen what the technology does.

Who this is for

Finance and operations teams get the most from it, because their work contains the highest density of tasks these tools handle well: drafting, summarising, checking, reformatting and pulling structure out of unstructured documents.

It also suits leadership teams who need to make decisions about AI without a technical background, and who are currently choosing between vendor claims they have no way to evaluate. Knowing what the technology can and cannot do is the prerequisite for every other decision about it.