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The article argues that data governance, especially role-based access control, will determine whether enterprise AI agents can be trusted, more than the choice of model. It also reports a shift of AI inference workloads back into corporate data centers, driven by cost, privacy, and sovereignty concerns. Readers should treat this as a vendor-led view of Cloudera's hybrid platform and partnerships, not independent evidence of market trends.
The race to deploy AI agents finds a familiar hurdle in data access
Enterprises racing to put AI agents into production are discovering that role-based access control, not model choice, decides whether those agents can be trusted. Rising inference costs, privacy worries and sovereignty demands are also pulling more AI workloads back inside corporate data centers. That shift favors companies that have spent years governing sensitive data at […] The post The race to deploy AI agents finds a familiar hurdle in data access appeared first on SiliconANGLE.
Enterprises racing to put AI agents into production are discovering that role-based access control, not model choice, decides whether those agents can be trusted. Rising inference costs, privacy worries and sovereignty demands are also pulling more AI workloads back inside corporate data centers. That shift favors companies that have spent years governing sensitive data at scale. Cloudera Inc. is betting on…
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