When AI Attacks Earnings

Unity Software recently revealed that it missed top line expectations due to issues related to machine learning models, causing an estimated impact of approximately $110 million in 2022. This highlights the growing need for companies to better manage AI risk from both organizational and technical perspectives. There are four steps enterprises can take to prevent common issues with ML before they materially impact revenue: (1) know what can go wrong, (2) implement ML observability, (3) invest in the right people, and (4) ensure ML teams are close to the businesses they serve. By adopting these best practices, companies can better manage AI risk and avoid potential pitfalls.

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