The easiest mistake is to train employees and forget everyone else who touches AI in the same operating context.
1. Short answer
If a contractor uses AI as part of work they do for your organisation, you should usually consider whether they need role-appropriate AI literacy measures too.
The practical test is not whether they are on payroll. The practical test is whether they are using AI on your behalf in a way that affects your operations, outputs, decisions, or risk profile.
2. Who counts
- freelancers writing content with AI support
- agencies producing campaigns with AI tools
- contract developers using AI code assistants
- analysts or consultants using AI with client data or internal material
The right training depth depends on role and context. Not everyone needs the same module.
3. When they are in scope
| Situation | Practical implication |
|---|---|
| The contractor uses AI in work done for you | Usually include them in your literacy measures. |
| The contractor never uses AI in that work context | The case for training is weaker, but document the reasoning. |
| The contractor handles sensitive data, code, or regulated workflows | Training scope usually needs to be more specific and more careful. |
4. A simple rollout model
- List the external roles that use AI on your behalf.
- Group them by real use context, not by contract type.
- Give them the matching literacy track.
- Keep the completion record in the same place as employee records.
This is one reason the Aivoin access model uses a company magic link instead of heavy user provisioning.
5. What proof to keep
Keep the same kind of evidence you would keep for employees:
- name or identifier
- role context
- completion date
- training scope
- attestation or assessment outcome if used
A single training record that includes employees and contractors is often easier to review later than two separate systems.