Which cloud architecture decision do tech leaders regret most? Treating AI like just another workload

AI systems break core assumptions of traditional cloud workloads: execution paths are conditional rather than deterministic, resource consumption scales with decision complexity rather than just traffic, and governance boundaries between compute, data and policy become unstable. Treating AI as a conventional workload ignores these shifts and creates challenges for provisioning, monitoring, cost management, and governance.