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Why most AI projects flop - and how your business can beat the odds
Only 5% of AI business projects succeed. Here's what they get right.
Successful AI efforts "focus on narrow but high-value use cases, integrate deeply into workflows, and scale through continuous learning rather than broad feature sets," according to the study's research team, consisting of Aditya Challapally, Chris Pease, Ramesh Raskar, and Pradyumna Chari. "However, they often fail in mission-critical work due to factors including a lack of memory, which reduces their ability to learn, adapt, and be customizable to the degree required to integrate effectively with our day-to-day workflows." Rather than relying on a centralized AI function to identify use cases, successful organizations allowed budget holders and domain managers to surface problems, vet tools, and lead rollouts."
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