AI literacy FAQ

Twelve plain-English answers to common questions about AI literacy, Article 4, evidence, workforce development and AI capability.

What is AI literacy?

AI literacy is the skills, knowledge and understanding people need to make informed use of AI systems and recognise their opportunities, risks and possible harms. The EU AI Act defines the term in Article 3(56), with context and responsibilities built into the definition. Read the AI literacy guide for the fuller explanation.

What does Article 4 of the EU AI Act require?

Article 4 requires providers and deployers of AI systems to take measures to support the development of AI literacy among staff and others using AI systems on their behalf. The current wording has applied since 27 July 2026 and reflects people’s knowledge, experience, education, training and context of use. Read the Article 4 guide.

Does Article 4 apply to UK companies?

UK companies can fall within scope where their activities meet the AI Act’s territorial rules, including certain EU market activity, deployment through an EU establishment or location, or use in the Union of AI-system output produced outside the EU. The position depends on the activity. Read the Article 4 guide and take legal advice on your exposure.

This guide is general information, not legal advice. Take advice on your own exposure.

How do we evidence AI literacy?

Keep an evidence log showing which AI systems are in use, which roles are exposed, what literacy each role needs, who completed which development and when, how learning or capability was assessed, the owner, and the next review date. The AI literacy checklist provides the full eight-step process and evidence-log template.

What is the difference between AI literacy, AI fluency and AI skills?

AI literacy, AI fluency and AI skills describe different things. AI literacy is the understanding needed to use AI systems responsibly and judge their output, as defined in EU AI Act Article 3(56). AI fluency is the practised ability to work with AI effectively, described in the AI Fluency Framework through four competencies: delegation, description, discernment and diligence. AI skills are task-level abilities built on both.

Is the free UK AI training enough?

The UK government’s free AI training is a useful foundation for workers who need basic skills to use simple AI tools confidently and responsibly. Some roles will need deeper, role-specific development, practice and evidence afterwards. See the Skills England mapping and our analysis of where free foundations training stops.

What is an AI capability platform?

An AI capability platform builds, coaches and measures what people can do with AI in their work. It connects structured development with practice, coaching inside real tasks and capability tracking over time, rather than stopping at course completion. Read the AI capability platform guide for the full definition and comparison with LMS and LXP models.

Do we still need an LMS?

Not necessarily. Most organisations can keep their LMS for formal learning, mandatory training, certificates, and learning records while adding a capability platform for development closer to work and capability measurement. The systems can serve different purposes. See the platform page for how Nadifor fits alongside an existing learning stack.

How do you prove AI training worked?

AI training worked when work changed, and you can show it. Prove it with four records: a capability baseline per team, evidence that people used AI inside real tasks during the programme, a reassessment on the same scale afterwards, and examples of changed work products or decisions. Completion rates and satisfaction scores on their own prove attendance, not capability.

Who should be trained first?

Start with people who already operate or use AI systems in their work, especially where outputs influence decisions, customers, colleagues or important processes. Prioritisation should reflect exposure, responsibility and context rather than job title alone.