""What we had noticed was there was an underlying problem with our data," Ahuja said. When her team investigated what had happened, they found that Salesforce had published contradictory "knowledge articles" on its website."It wasn't actually the agent. It was the agent that helped us identify a problem that always existed," Ahuja said. "We turned it into an auditor agent that actually checked our content across our public site for anomalies. Once we'd cleaned up our underlying data, we pointed it back out, and it's been functional.""
"Ashok Srivastava, senior vice president and Chief AI Officer at Intuit, said he wasn't surprised about the results of a recent MIT study that found that 95% of AI pilots at large corporations had failed, because of the archaic systems at large companies. "The fact is that the foundation of AI-which is data-people don't invest in it," Srivastava said. "So you've got 1990s data sitting in a super-expensive, unnamed database over here, you've got AI here, you've got the CEO telling you to do something, and it's just not going to work.""
Salesforce deployed an AI agent that began hallucinating and delivering inconsistent results, which led to a temporary shutdown. Investigation revealed contradictory knowledge articles and broader underlying data quality problems rather than a flaw in the agent itself. The agent was repurposed as an auditor to detect anomalies across public content, the data was cleaned, and the agent was redeployed successfully. Industry leaders noted that AI performance depends on data quality, that archaic systems and underinvestment in data infrastructure drive high pilot failure rates, and that pilots often deliver learnings but rarely scale to enterprise ROI without data modernization.
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