Every company wants to make breakthroughs with AI. But if your data is bad, your AI initiatives are doomed from the start. This is part of the reason why a staggering 95% of generative AI pilots are failing.
I’ve seen firsthand how seemingly well-built AI models that perform reliably during testing can miss crucial details that cause them to malfunction down the line. And in the physical AI world, the implications can be serious. Consider Tesla’s self-driving cars that have difficulty detecting pedestrians in low visibility; or Walmart’s anti-theft prevention systems that flag normal customer behavior as suspicious.
