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This disconnect has deep roots. Enterprise IT advanced rapidly through two decades of cloud software, large-scale compute hardware, and AI innovation. But organizations that operate physical infrastructure — e.g., factories, energy systems, vehicles, medical equipment, telecommunications facilities — depend on edge computing systems engineered for fundamentally different priorities: industrial-grade reliability, deterministic control, extreme longevity in challenging environments, and unattended operation. These constraints shaped robust, specialized platforms that evolved in isolation from mainstream IT. Hence the AI discontinuity.
Previous attempts to bridge this gap misdiagnosed the problem. So-called “end-to-end solutions” have usually proven brittle, costly, and vendor-specific. Integration frameworks that attempted to reshape edge platforms into miniature enterprise systems ignored operational constraints and collapsed under their own weight. Moving AI as close to the data as possible is the smartest thing enterprises can do. But getting it there requires rethinking how enterprise and operational systems connect, not forcing impractical integration.
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TABLE OF CONTENTS
The AI Computing Continuum
The Agentic AI Imperative
Closing the Gap
The Cloud-Native Edge
The Wind River Cloud-Native Edge Platform
Getting Started
The Agents Are Coming — Are Your Edge Systems Ready?
COMPANIES CITED
Wind River
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