Employee Retention Analysis
Use Case Family:
Predictive Analytics & Forecasting
Business Domain:
Human Ressource
Processes:
Retention Management
Challenge:
High employee turnover leads to increased costs and knowledge loss. Often, resignations are only noticed when it’s too late, as early warning signs are not systematically captured. HR teams struggle to proactively address dissatisfaction or career stagnation, making retention a significant challenge.
Solution:
AI analyzes employee engagement, performance trends, and feedback to identify individuals at high risk of leaving. Machine learning models detect patterns in behavior, satisfaction surveys, and career progression. Leadership receives data-driven recommendations for targeted retention strategies.
Benefits:
Companies can take proactive measures to retain top talent, reduce turnover costs, and increase employee satisfaction. This leads to improved productivity, a stronger workplace culture, and long-term competitiveness by preserving valuable expertise.
Target Group:
Potential Industries:
High Risk systems
Article 6 (Annex III (4b))
No transparency obligantions
Disclaimer
The information provided regarding the risk assessment is without guarantee. The complete classification of a use case according to the EU AI Act depends on numerous regulatory and company-specific factors. Therefore, the risk assessment is always case-specific. The risk assessment logic of Casebase is used for this purpose.