Intellectual Property India Publishes Patent Application for System And Method For Al-Based Employee Attrition Risk Prediction And Automated Retention Intervention.

MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202621091676 A) filed by Gyan Ganga Institute Of Technology & Sciences Bargi Hills, Jabalpur Madhya Pradesh; Dr. Narendra Kumar Shukla; Dr Nikita Shukla; Dr. Meghna Jain; Ms. Shivani Agrawal; Ms. Deepika Rajak; and Ms. Simran Kesharwani on July 28, 2026, for System And Method For Al-Based Employee Attrition Risk Prediction And Automated Retention Intervention..

Inventors include Dr. Narendra Kumar Shukla; Dr Nikita Shukla; Dr. Meghna Jain; Ms. Shivani Agrawal; Ms. Deepika Rajak; and Ms. Simran Kesharwani.

The application for the patent was published on September 18, 2026, under issue no. 38/2026.

Abstract: Abstract The present invention relates to an Artificial Intelligence (AI)-based system and method for predicting employee attrition risk and automatically recommending personalized retention interventions. The invention integrates structured organizational data, behavioral analytics, employee engagement metrics, communication patterns, performance records, attendance history, learning progress, compensation trends, and external labor market indicators into a unified predictive intelligence platform. Advanced machine learning, deep learning, explainable artificial intelligence (XAI), and reinforcement learning algorithms continuously estimate an employee-specific attrition risk score while identifying the key contributing factors. Based on organizational policies and historical intervention effectiveness, the system automatically generates customized retention strategies including compensation recommendations, career development plans, learning opportunities, workload optimization, manager intervention, wellness initiatives, and succession planning. The system continuously learns from organizational outcomes to improve prediction accuracy and intervention effectiveness. The invention significantly reduces employee turnover, improves workforce stability, enhances organizational productivity, and enables proactive human resource management through intelligent automated decision support.

Disclaimer: Curated by HT Syndication.