Predicting Retention: IBM’s Data-First Approach to Smarter HR

IBM began developing and applying its predictive analytics for employee retention around 2015–2016, when its internal HR organization started working with the company’s data science division to clean and unify workforce data. (IBM, 2024)
By 2018, IBM’s HR Chief Human Resources Officer Diane Gherson opening discussed the results, noting that the AI system could predict the risk of an employee quitting with up to 95% accuracy and had already helped increase retention by about 25%. (CNBC, 2019)

The work continued through into the ‘20s up until now, adapting as IBM expanded its use of internal data platforms, and AI tools across HR purposes. The success of this early program became one of the first major examples of how structured, reliable data can directly improve AI-driven HR decision-making. (HR Cloud, 2024)

-Taylor Howard
Chief Marketing Officer, Blue Sky Compute
Taking organizations from AI to ROI.