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AI USE CASE

Employee sentiment & attrition prediction

Spot disengagement and flight risk early enough to act.

Typical budget
€15K–€60K
Time to value
10 weeks
Effort
6–14 weeks
Monthly ongoing
€400–€2K
Minimum data maturity
intermediate
Technical prerequisite
data engineer
Industries
SaaS, Professional Services, Retail & E-commerce, Healthcare, Education
AI type
ml classification

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

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.