Enterprise data platforms face pressure to deliver AI business results
SiliconANGLE: AI’s production push puts data platforms on the hook for results
Enterprise data platforms must turn AI pilots into measurable business returns while overcoming the data access, sovereignty and cost barriers that stand between experimentation and production. The conversation is shifting from what AI can do to how companies make it pay off. One data platform provider has responded by folding its post-sales teams under a […] The post AI’s production push puts data platforms on the hook for results appeared first on SiliconANGLE.
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The conversation around enterprise AI is shifting from theoretical capabilities to actual business results. Enterprise data platforms now face pressure to help customers move AI projects from experimental pilots into production while delivering measurable returns on investment. Three major obstacles stand in the way: data access challenges, data governance and sovereignty issues across distributed systems, and uncertainty about true costs and returns when scaling pilots to full deployment.
Explainer: Why AI Replacements Are Failing: The 95% Pilot Problem
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