Updates That Matter4 min read

EU AI Literacy Enforcement: Keep a Useful Training Record

AI literacy enforcement is now active in the EU. Use the RECORD template to document role, context, risk, practice and follow-up without inventing a certificate.

Bokili EditorialPublished August 15, 2026· Verified August 15, 2026

Illustrated AI literacy record linking a role, work task, risk control and evidence of completed practice

AI literacy has moved from a planning topic to an operating requirement. The European Commission says the supervision and enforcement provisions for Article 4 of the EU AI Act now apply. The July 2026 amendment kept an obligation for AI providers and deployers to take measures that support staff AI literacy, while removing the idea that every person must reach one fixed “sufficient” level.

That does not create a universal course, exam or certificate. The Commission says organisations can keep an internal record of training and other guidance, and that no particular governance structure is required. The practical question for HR, L&D and AI leaders is therefore simple: can you show what people needed to learn, what you did about it, and how the learning relates to their real AI use?

What changed in August 2026

Enforcement has started, but the obligation remains context-sensitive. A useful record should connect learning to the employee’s role, the AI system, the work context and the relevant risks. This is a practical template, not legal advice or proof of compliance.

An attendance list is not a useful AI literacy record

A spreadsheet that says “AI webinar completed” proves only that someone was present. It does not show whether the session matched the tool they use, the decisions they make or the people affected by those decisions. The Commission’s current guidance asks organisations to consider technical knowledge, experience, education, training, the system’s context and its risks.

The record should stay proportionate. A copywriter using an approved assistant for low-impact drafts does not need the same evidence as a recruiter using an AI-supported screening workflow. Start with the work, not the course catalogue.

Use the RECORD template

RECORD: six fields for one useful line of evidence

R — Role and starting point

Who is learning, what is their role and what relevant experience do they already have?

E — Exact system and task

Name the AI system or feature and the real work task in which it is used.

C — Context and consequence

Record who may be affected and what can go wrong if the input, output or decision is mishandled.

O — Outcome to practise

State one observable behaviour: for example, remove personal data, verify a source or escalate a high-impact decision.

R — Review evidence

Keep a completed scenario, assessed output, supervisor check or other evidence that the behaviour was practised.

D — Date, owner and next step

Record when the action happened, who owns follow-up and when the need will be reviewed.

Worked example: a procurement analyst

Reading is a start. Practice makes it stick.

Start learning

Suppose a procurement analyst uses a generative AI tool to summarise supplier responses. Their record might say: role — procurement analyst with regular spreadsheet experience; system and task — approved AI assistant used to summarise bid text; context — commercial information may be confidential and an incorrect summary could distort the comparison; practice outcome — separate source facts from AI interpretation and flag missing evidence; review evidence — a completed supplier-summary exercise checked against the original bid; next step — manager review after four weeks.

This is more informative than “completed GenAI basics”. It tells a future reviewer what capability was relevant and what evidence existed. It also makes the next learning decision easier: the analyst may need more practice in evidence tracing, not another introduction to prompting.

	Weak record	Useful record
Scope	AI training	Supplier-response summarisation in the approved tool
Risk	Not recorded	Confidential input and unsupported comparison claims
Evidence	Attendance	Checked exercise linked to the source bid
Follow-up	None	Manager review after four weeks

Keep the record small enough to maintain

A good record is not a second learning platform. One line per meaningful learning action can be enough when the fields are specific. Avoid collecting unnecessary personal information. Use role or team reporting where individual detail is not needed, define retention, and give access only to people who have a reason to see it.

One-page AI literacy evidence check

The role, AI system and real task are named.
The learning action matches the person’s starting point and work context.
At least one relevant input, output or decision risk is recorded.
The expected behaviour can be observed in a task or scenario.
Evidence is more meaningful than attendance alone.
An owner and review point are clear.
The record contains no unnecessary personal data.

Connect documentation to practice

The RECORD template works best alongside a risk-based AI literacy plan, a role-based skills matrix and measures that go beyond completion rates. Together, these answer three different questions: what should this person learn, what did they practise, and what evidence shows progress?

Bokili’s short workplace missions can supply the practice layer: employees perform a focused task, receive feedback and build evidence of demonstrated skills. Whatever platform you use, keep the principle: document the capability that work requires, not merely the content that training delivered.