Enterprise AI Infra Shifts to DevOps, Raising Scaling and Cost Challenges
As AI workloads move from prototypes to production, the responsibility for GPU orchestration, scaling, monitoring, and cost control is moving from data‑science teams to DevOps and platform engineering. This shift forces organizations to treat LLM deployment as a core infrastructure problem rather than a simple feature integration, introducing new operational and financial complexities.