DraftKings Used AI to Target High-Loss Gamblers

DraftKings used machine learning models to identify and target gamblers most likely to lose money with promotional incentives, according to an investigation by The New York Times. Former employees, including data analyst Jayden Butts, claim the company prioritized elastic bettors—those who lose more per promotion—effectively targeting individuals prone to addiction to improve margins and optimize spending.

Former staff allege the company simultaneously sidelined or shut down AI projects intended to predict and prevent gambling addiction. Nestor Hernandez, a former data scientist, developed a model to proactively identify gamblers in trouble before the project was terminated.

DraftKings rejects any implication that its marketing practices are unfair or improperly target customers, stating that promotions are aimed at sustained, engaged users. Chief Responsible Gaming Officer Lori Kalani defended the company's decision to decline predictive risk technology, arguing it was not evidence-based. Kalani stated the company instead uses reactive triggers based on specific betting behaviors to identify customers who are betting for entertainment and fun.