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AI USE CASE
Employee sentiment & attrition prediction
Spot disengagement and flight risk early enough to act.
What it is
An ML model combines anonymised pulse-survey results, calendar patterns and tenure to predict attrition risk by team. HRBPs get a heatmap of where to invest manager time. Properly designed, it surfaces risk 3–6 months earlier than exit interviews.
Data you need
Anonymised survey results, HRIS data, 24+ months of attrition history.
Required systems
- data warehouse
Why it works
- Aggregate at team level, not individual
- Co-design with works council / employee reps
How this goes wrong
- Surveillance perception kills trust
- Predictions used to label rather than help
When NOT to do this
Don't predict at the individual level, legal risk and trust collapse.
Vendors to consider
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