Artificial Intelligence Tool to Predict Employee Attrition

A Tokyo City University Professor and Startup Collaborate to develop an Artificial Intelligence Tool to Predict the new hire quit.
Artificial Intelligence Tool to Predict Employee Attrition

In a groundbreaking collaboration, Professor Naruhiko Shiratori of Tokyo City University and a Japanese startup are working on developing an artificial intelligence (AI) tool that aims to revolutionize employee management. The focus? Predicting when new employees, especially freshers, are likely to quit their jobs.


Challenges in Employee Retention

Employee retention has become a significant challenge for organizations worldwide. Despite HR personnel’s efforts to recruit and onboard the right talent, the trend of job hopping persists. Many workers leave their jobs within the first two years, causing disruptions and impacting productivity. Recognizing this issue, Professor Shiratori and the startup have set out to create an innovative solution.


Building on Existing AI Tools

The groundwork for this project lies in an existing AI tool that identifies students at risk of dropping out from colleges and universities. Professor Shiratori and the startup plan to enhance this tool, adapting it for the corporate world. Their goal is to provide employers with insights into when fresh graduates—recently hired by their organizations—might decide to leave.


Predictive Factors

The AI tool will consider a range of factors to make accurate predictions. These include:

  1. Performance Metrics: By analyzing performance data, the tool will assess how well new employees are adapting to their roles. High-performing individuals may be less likely to quit, while those struggling might need additional support.

  2. Attendance Patterns: Consistent attendance is crucial for job satisfaction. The tool will track attendance records to identify any irregularities or patterns that could indicate dissatisfaction.

  3. Background and History: The AI will delve into employees’ backgrounds, including their educational qualifications, previous work experiences, and any relevant personal history. These details can offer valuable context.

  4. Behavioral Traits: The tool will analyze behavioral traits exhibited by employees. For instance, signs of stress, disengagement, or burnout may signal potential attrition.

  5. Interview Insights: Extracting insights from job interviews, the AI will consider how well the employee aligns with the organization’s values and culture.


Early Detection and Intervention

During its pilot stage, the AI tool is already proving its worth. Not only does it predict potential quitters, but it also identifies freshmen who face challenges both at work and at home. By detecting struggling employees early, organizations can intervene proactively. Instead of losing valuable talent, employers can offer targeted support to improve performance and productivity.

A Bright Future for Employee Retention

As Professor Shiratori and the startup refine their AI tool, the corporate world eagerly awaits its implementation. If successful, this predictive tool could transform the way organizations manage their workforce, fostering better employee satisfaction, retention, and overall success.

Stay tuned for further updates on for the evolving workplace paradigm. 🌐🏢

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