Organizations are often advised to move quickly with AI adoption, but simply shipping pilots without addressing underlying data quality issues can be ineffective. A utilities company deployed AI for call center documentation, yet continued to lose revenue due to an unresolved data problem in property ownership. In contrast, an insurance company that had invested in data foundations for regulatory compliance was able to quickly leverage AI to identify high-risk buildings, demonstrating the importance of having trustworthy data before implementing AI solutions. AI
IMPACT Emphasizes that foundational data quality and governance are critical for effective AI implementation, rather than just rapid deployment.
RANK_REASON Opinion piece discussing strategy for AI adoption.
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