Platform engineers and SREs share practical perspectives on AI adoption challenges and opportunities in 2026

Infrastructure engineers are focused on the operational costs and resource management challenges of deploying AI systems at scale

Real-world AI implementation requires significant investment in monitoring, debugging, and reliability infrastructure beyond just model training

Platform teams are prioritizing pragmatic AI solutions over cutting-edge models, favoring stability and maintainability

The gap between AI research capabilities and production-ready deployment remains a critical bottleneck for engineering teams