Data and AI Literacy

What it is

It is role-based. An analyst, a manager who acts on a dashboard and a member of staff who uses an AI assistant need different things. A programme sets out who needs what, how it is provided and how it is recorded.

For AI it is also a legal subject in the EU. The AI Act places an AI literacy duty on providers and deployers of AI systems.

Why it matters

The EU AI Act places an AI literacy duty on providers and deployers. Article 4, as replaced by Regulation (EU) 2026/1744, requires measures to support its development among staff and others using AI systems for them.

The replaced text also states that the obligation does not require providers or deployers to guarantee any specific level of AI literacy of any individual. The duty continues: Article 4 was replaced, not repealed. This is a description of the text and is not legal advice.

The problem it addresses

DII editorial view

Tools reach staff faster than understanding does. People act on a dashboard or an AI answer without knowing what it can and cannot tell them, and a single generic course does little to change that. Literacy work matches what each group needs to know to the systems it actually uses.

Business and organisational relevance

DII editorial view

Literacy is what lets other investments pay back. Self-service analysis, governed metrics and AI assistants all assume people who can question what they are shown. Responsibility usually sits between a data office and learning and development, and needs an owner.

Practical use cases

• Role-based AI literacy measures for staff who operate or use AI systems
• Onboarding for people who are given self-service analysis tools
• A record of the measures taken, kept for accountability

Benefits and opportunities

• Staff who can question an output before acting on it
• A documented response to the AI literacy duty

Risks, limitations and dependencies

• One generic course for every role
• Measures taken once and not maintained
• The evidence DII has read concerns AI literacy under EU law only; it has read nothing that measures the effect of literacy programmes

Prerequisites for adoption

DII editorial view

• A clear owner; the work usually falls between a data office and learning and development
• A view of which roles use which data and AI systems
• A way to record the measures taken

Implementation considerations

• Base it on roles. Decide what each group of staff needs to know for the systems they use.
• Keep a record. Record the measures taken; the Article 4 duty continues.
• Take advice on what compliance requires. The text sets a duty to take measures; what is sufficient for your organisation is a legal question.

The DII Radar assessment

Approved DII Radar assessment

DII assesses Data and AI Literacy as Moderate relevance, with direction Stable. Its strategic impact is assessed as Moderate and its enterprise adoption as Emerging. It is in the catalogue and is not one of the ten entries on the current Radar.

DII relevance is our assessment of current significance and momentum, based on evidence, market development and adoption. Direction is the observed trajectory of relevance and adoption. Strategic impact is the potential or current significance to enterprise data capability, and enterprise adoption is the extent of current real-world enterprise adoption; together they set the position on the Radar. The Radar is not a prediction, vendor comparison or performance ranking.

Evidence basis: EU AI Act (Regulation (EU) 2024/1689) Article 4, as replaced by Regulation (EU) 2026/1744, point (5); consolidated text of 27 July 2026.

What to consider next

DII editorial view

• Keep role-based AI literacy measures for staff who operate or use AI systems
• Keep a record of those measures; the duty continues
• Take legal advice on what is sufficient for your organisation