From records to evidence of learning
When considered alongside assessment, program management, and certification, training records provide a more traceable picture of development. Confirm the scope of Qulak’s modules and your organization’s data protection needs during a demo.
As of 2026, the European Union’s approach and international best practices are bringing transparent records of AI-related processes to the forefront. In-house training can also be considered in this context; documentation should specify which content the training covers, who attended, which tools were used, and how learning outcomes were measured.
To link your record structure to assessment and certification, see Qulak’s assessment and certification features and to discuss your compliance workflow, go to the Qulak contact form.
This article explains how to structure in-house training records to prepare for requirements such as those of the AI Act, which metadata should be retained, and how to create audit-ready documentation. It offers practical operational steps rather than legal advice.
Record systems should provide summary reports suitable for review by senior executives as well as sufficient detail to respond to audit requests. Create a retention policy that takes data protection, intellectual property, and employee rights into account.
1. Which Records Should Be Kept?
The core set of records should include:
- Training title, objective, and curriculum summary
- Participant list and roles
- Date, duration, and format (online/asynchronous, in person)
- Brief description of the tools and models used
- Assessment results (performance measurements, certificates)
- Information about those responsible and the training provider
2. Metadata and Traceability
Examples of metadata recommended for inclusion in records:
- The training’s impact on the business unit and target KPI
- Model/tool version and vendor information (if applicable)
- Approval and review dates
- Related risk assessment and mitigation notes
3. Retention Policy and Data Protection
Retention periods should be determined in accordance with local legislation and the company’s internal risk policy. For records containing personal data, comply with KVKK or applicable regulatory requirements. Establish anonymization, access control, and logging policies.
4. Audit Readiness and Reporting
Use search-and-match (tagging) mechanisms to respond quickly to audit requests. Conduct regular internal audits to ensure that records are complete. Also prepare executive-level summary dashboards (showing which training courses contributed to reducing legal risk).
Implementation Checklist
- Is a standard record template ready for all training courses?
- Are metadata and model version information being recorded systematically?
- Have retention and anonymization policies been defined?
- Have access, logging, and reporting processes for audits been established?
- Are in-house responsibilities (HR, Legal, IT) clearly defined?
We can work together to organize your training records in preparation for the AI Act. For information, a demo, or a quote:
Frequently Asked Questions
Q: Which records are always requested during an audit?
A: Generally, the training content, participant list, assessment results, and information about the model/tools used are the items most often requested.
Q: How long should records be retained?
A: The period varies according to local regulations and internal risk policy; retention for business and compliance purposes is generally recommended for at least 3-5 years, but check the requirements of official authorities.
Q: Do training records fall under GDPR/KVKK?
A: If participant data contains personal data, the relevant data protection regulations must be followed; anonymization and access control are recommended.