Training your teams on AI: where do you start?

Start with a simple question: who in your office works with documents today? Those people are probably already using AI, or will be soon. Whether that adoption holds over time depends on what they know how to do with the tool and on which tasks they use it.

Why training needs to continue over time

In the BCG AI at Work 2025 survey, 36% of employees consider their AI training sufficient. Regular AI use is reported by 79% of people who received more than five hours of training, compared with 67% below that threshold. The survey shows an association between training and regular use. It does not establish that training time alone causes that use.

The result does not establish a universal number of training hours. In practice, it supports returning to real tasks after an initial module. A thirty-minute webinar on "how to write a prompt" provides a reference point. Later sessions apply it to the documents the team actually handles.

A McKinsey study published in January 2025 (Superagency in the workplace) asked business leaders to estimate what proportion of their employees used AI for at least 30% of their work. The median answer was 4%. The figure measured directly from employees was 13%. Teams are adopting AI faster than leadership thinks. Structure, support, and training on the tasks that actually matter then determine the quality of that adoption.

The two essential dimensions

Two dimensions come up in every office that takes AI adoption seriously. They can be addressed briefly within a single module.

The first is judgment: knowing which outputs need review and which tasks genuinely lend themselves to AI. This assessment depends first on the structure of each task. Training should at least establish that the assessment exists and belongs to the employee.

The second is the question of data: understanding what type of document can go into what type of tool, and why that distinction has real consequences. What using a consumer-grade tool without a contract covering data processing means for client data or confidential documents is itself a topic that deserves its own attention. What training should produce here is a reflex: before copying a document into a tool, ask what it contains.

These two dimensions form the foundation of what is called AI literacy. Training that covers only part of them leaves blind spots that may appear a few weeks later, when the habits formed meet a situation the training did not anticipate.

3 signs that training holds up in daily work

These three points allow you to assess a training you have received or are considering. The precise content depends on the actual tasks of the office and the tools already in place.

• Staff know how to phrase a request and, on their own office tasks, which outputs need careful review.
• The question of what can or cannot be entered into a public tool was raised explicitly, with examples drawn from the company's usual documents.
• There is a clear answer to this question: what happens when the employee who was most skilled with the AI tool leaves the company?

That last point is often overlooked. In offices where adoption holds over time, the skill is shared widely enough to survive a departure and documented well enough that a new employee can pick up the same practices without starting from scratch.

In practice, the few practices that genuinely changed how people work are written down somewhere, whether that is a shared page, a short memo, or a few lines added to an existing process. A few lines are enough for a colleague or a new arrival to understand which tasks AI is used for, how, and what must always be checked. Without that record, the skill leaves with the person who attended the training.

The construction site question

A doubt comes up regularly in construction companies: do teams need to leave the site to be trained? AI literacy mainly concerns the office staff who work with documents every day.

In a construction company's office, the employees directly affected by AI day to day work with quotes, site meeting reports, technical specifications, supplier correspondence, and subcontractor requests. A handful of people, sometimes two or three in a mid-sized office, handle the bulk of this document work. Training them on their own cases as part of the working day simplifies the organisation and increases the session's immediate usefulness.

What the EU AI Act requires, without interpreting it for your situation

The current wording of Article 4 on EUR-Lex has applied since 2 February 2025. Providers and deployers must, to their best extent, take measures to ensure a sufficient level of AI literacy among people who operate or use AI systems on their behalf. They must take account of factors such as knowledge, experience, and the context of use. The article sets neither a universal number of hours nor a single training format.

The European Parliament approved the Digital Omnibus on 16 June 2026, and the Council gave its final approval on 29 June 2026. On 22 July 2026, publication was still pending according to the OEIL procedure file. The Council states that the amending regulation enters into force on the third day after publication. Until then, the current wording of Article 4 remains applicable.

In practice, keeping a record of training carried out and its content remains useful, whatever form the final text takes. The value of that record lies in documenting the ability to use a tool appropriately, including when and how to check its outputs.

The precise interpretation of Article 4 in your situation belongs in legal advice.

Frequently asked questions

Is a single training session enough?

Rarely. In the BCG AI at Work 2025 survey, 36% of employees consider their AI training sufficient. Regular AI use is reported by 79% of people who received more than five hours of training, compared with 67% below that threshold. This is an observed correlation, not evidence of a causal effect from training time. Practice on real office tasks then helps the skill settle into daily work.

Do teams need to leave the construction site to be trained?

AI literacy in a construction company mainly concerns the few office staff who work daily with documents: quotes, meeting reports, technical specifications, supplier correspondence. Training them on their own tasks as part of their daily work is the most direct way to start.

Who does the AI Act obligation apply to?

Article 4 of the EU AI Act addresses providers and deployers of AI systems. A construction SME that uses such a system in its operations may be a deployer. On 22 July 2026, the amendment adopted by Parliament and Council had not yet been published in the Official Journal, so the current wording still applied. Consult a specialist lawyer about your particular situation.

How long does it take to train a team?

There is no universal answer. Training becomes effective when it covers the office's concrete tasks and is followed by time to let the habits settle. A few hours targeted at the company's real cases can already produce lasting results when they form part of that follow-up.

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Where do you start in practice? With the few people who handle documents daily and with their actual tasks. A first step, before committing to anything: identify the two or three document tasks that come up most often in the office, a type of quote, a standard meeting report, a recurring letter, and note who handles them. That is where training is most likely to stick, because repetition turns a practice into a habit.

The right depth and the right order then depend on what you find in the company: which tools are already in use, who actually uses them, and where the skills gap really is. Training built around those real uses starts from that assessment and remains grounded in daily work.