"Ten years ago, IBM announced with great fanfare that Watson for Oncology was as accurate as human physicians in reading X-rays, CT scans and other reports. In some regions lacking oncologists, IBM even promoted Watson as a potential substitute for doctors. But the reality soon surfaced. According to ASH Clinical News, internal documents revealed that Watson made unorthodox and unsafe recommendations when provided with synthetic (rather than real) patient data."
"Zillow built an AI model to predict home values and aggressively bought homes based on those predictions. The algorithm consistently overpaid, leading to half a billion dollars in losses and mass layoffs. The program collapsed in less than a year when the algorithm failed to adjust to a cooling housing market. Dig deeper: Implementing AI without a problem is a fast road to failure Even recent rollouts still miss the mark"
AI deployments frequently produce new problems and additional human labor rather than delivering promised efficiency and automation gains. High-profile failures include IBM’s Watson for Oncology, which produced unorthodox and unsafe recommendations when tested with synthetic patient data, and whose health data and analytics division sold for $1 billion after over $5 billion invested. Zillow’s home‑pricing algorithm overpaid for properties, generating roughly $500 million in losses and collapsing within a year as the market cooled. Recent rollouts remain imperfect: Intuit’s QuickBooks Online launched an AI‑powered update that created operational issues for small‑business users, illustrating persistent gaps between AI promise and business reality.
Read at MarTech
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