The Agentic Reckoning: Enterprise AI organizations have a runtime problem, not a model problem — and most are building the wrong solution

VentureBeat’s May 2026 Pulse Research survey of 132 enterprise technology leaders finds that AI agent deployments are breaking down at the runtime layer. Respondents cite issues like lost context, rising token costs, hallucination cascades, and excessive engineering time spent on plumbing rather than business logic.

The findings suggest enterprise AI maturity is shifting from model selection to runtime durability as agents move into production workflows. Vendors and internal teams that can provide persistent state, observability, cost controls, and failure recovery may become critical infrastructure for the next phase of agentic AI adoption.