AI tool predicts employee turnover risk

The continuous need to reduce employee turnover and encourage long-term employee commitment has led organisations to seek innovative solutions. The latest advancements in AI technology developed by Japanese researchers offer a proactive approach to predicting potential employee departments and providing tailored support.

This groundbreaking tool, spearheaded by Tokyo City University Professor Naruhiko Shiratori in collaboration with a start-up in Tokyo, employs advanced algorithms to analyse a myriad of employee data. From attendance records to personal demographics like age and gender, the AI tool synthesises comprehensive insights. Moreover, it integrates information on former employees and those on leave to construct a predictive turnover model for each organisation.

In an interview with AFP, Shiratori elucidated on the tool’s capabilities, stating that it generates risk assessments for new hires in “percentage points”. He emphasised ongoing trials with multiple organisations to refine the tool’s accuracy and tailor it to individual organisational dynamics.

Crucially, the AI tool offers a discreet means for management to identify employees at risk of departure and extend targeted support. Shiratori highlighted the potential for managers to intervene sensitively, leveraging AI-generated insights to offer assistance without divulging raw statistics, which could unsettle employees.

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The genesis of this AI tool traces back to earlier research focusing on forecasting university student attrition. Building upon this foundation, the researchers aim to enhance the tool’s functionality. Future iterations will leverage data from job interviews and personal histories to recommend suitable assignments for new hires.

In Japan, where synchronised annual graduate hiring is customary, addressing turnover is paramount. Government data revealed that approximately one in 10 fresh college graduates exit their jobs within a year, with around 30% department within three years.