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AI USE CASE
Personalised L&D recommendations
Recommend the next best learning resource for every employee, every quarter.
What it is
A recommendation system maps each employee's role, goals and skill gaps to your internal and external learning catalogue, generating personalised quarterly learning paths. Improves course completion 2–3x vs catalogue browsing.
Data you need
Skills taxonomy, course catalogue with metadata, HRIS.
Required systems
- data warehouse
Why it works
- Co-build the skill taxonomy with line managers
- Quarterly review with L&D team to refresh catalogue
How this goes wrong
- Catalogue too small — same items recommended to everyone
- Skill taxonomy that doesn't match how managers think
When NOT to do this
Skip if your learning catalogue has fewer than 100 items — too few to recommend from.
Vendors to consider
This use case is part of a larger Data & AI catalog built from 50+ enterprise transformation programs. Take the free diagnostic to see how it ranks against your specific context.