Beyond the AI Gold Rush: a quick guide for business decision makers

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The enterprise AI conversation is shifting from experimentation to execution. Early pilots proved what’s possible, but today’s AI workloads—continuous inference, real-time decisions at the edge, and integration across hybrid estates—stress infrastructure and operations that were never built for always-on AI.

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This Report Covers:

  • Enterprise AI is moving from experimentation to execution, but modern workloads are straining legacy infrastructure and operations.
  • Many organizations still struggle to turn AI pilots into real business value (“pilot everywhere, value nowhere”).
  • Successful AI at scale requires governance, lifecycle visibility, data readiness, cost control, and policy-driven compliance.
  • The recommended approach is to reassess infrastructure readiness, remove bottlenecks, and implement repeatable controls for scalable AI.
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