How to choose an AI training system: the right questions to ask
Choosing an AI training system requires assessing four dimensions: functional (does the system genuinely generate learning paths or merely select from a catalogue?), technical (HRIS (Human Resources Information System) integration, data hosting, language model used), legal (RGPD (GDPR), AI Act, Qualiopi) and organisational (deployment time, maintenance load, vendor support). The most important distinction is between genuine dynamic personalisation and personalisation via predefined conditional paths: both are marketed under the same name but produce very different results.
Why this market is hard to read
The market for AI training systems is growing quickly and is highly unstandardised. The same promise (personalised learning paths, adaptive AI, skills measurement) covers very different technical realities depending on the vendor. Sales demonstrations are built on optimal cases.
A rigorous choice depends on being able to distinguish what is demonstrated from what is merely claimed.
Functional questions
Does the system generate content or merely distribute it?
An AI system that generates content from a skills framework is fundamentally different from an LMS that distributes existing content. Generation is what makes it possible to adapt to specific needs without depending on a pre-existing library.
Is personalisation dynamic or via predefined paths?
Personalisation via conditional paths ("if the learner answers incorrectly, they go to module B") is fixed branching. Dynamic personalisation recalculates the learning path after each assessment based on actual attainment. The demo should show this second mechanism in action on a real case.
Is measurement of acquisition integrated or added at the end?
An end-of-module quiz measures short-term memory. Integrated measurement assesses skill by skill at points spread over time and triggers an adjustment to the path.
Can the system integrate your existing skills frameworks?
Ask how long it takes and who does it.
Technical questions
HRIS and LMS integration: which APIs are available and used in production with existing clients? Data hosting: on which infrastructure, in which country? Language model: which one is used, is it auditable? Availability: what is the SLA contractually committed to?
Legal questions
Is the system compliant with RGPD (GDPR) and where is the data processing record documented? How is AI Act Article 4 (AI literacy) supported? Is the content compatible with Qualiopi criteria for traceability and assessment?
Organisational questions
What is the deployment timeline on a comparable scope? What internal workload is required to maintain the skills frameworks and content? What support does the vendor provide during the first six months?
Red flags
A vendor who cannot show dynamic personalisation on a live example. A vendor who cannot name reference clients where HRIS integration is in production. A price that does not include integration and skills framework configuration.