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AI Predicted Who'd Quit — IBM Saved $300 Million
Published 3 weeks, 6 days ago
Description
Employee attrition is one of the most expensive problems in business, but a new wave of AI-powered prediction tools is changing the game — and the savings run into the hundreds of millions.
In this episode, we break down how IBM, ADP, and Credit Suisse have deployed predictive attrition models that identify flight-risk employees before they hand in their notice. IBM's system hit 95% accuracy and saved roughly $300 million. ADP's DataCloud helped one mid-market company cut turnover from 31% to 25% in a single year. And Credit Suisse found that each one-percentage-point drop in attrition was worth $75 to $100 million annually.
We also walk through the ROI calculation HR leaders can use to build the business case — and look at the four enterprise platforms leading this space in 2026: ADP DataCloud, SAP People Intelligence, Workday People Analytics, and Visier.
If you're an HR leader trying to justify the investment in predictive analytics, this episode gives you the numbers, the methodology, and the practical next steps to get started.