Enterprises have deployed AI agents faster than they have established controls to manage them, doing so knowingly. This finding comes from five surveys conducted by VentureBeat Research in June, covering identity, evaluation, cost telemetry, context, and orchestration layers essential for trusting AI agents. Most deployed AI “agents” are actually chatbots with limited capabilities; true multi-step agents remain rare. Two-thirds of enterprises allow automated agent actions without human review despite low trust in evaluations, leading to frequent failures. Credential sharing among agents is common and correlates with increased security incidents, emphasizing the need for scoped identities. GPU utilization is often below 50%, highlighting inefficiencies in current AI infrastructure. Agents frequently provide confident but incorrect answers due to inconsistent or missing business context, underscoring the need for better data governance. Across all layers, many enterprises plan vendor changes or additions within a year, signaling a market in flux with no dominant incumbent platforms. The research draws on responses from over 570 professionals at organizations with 100+ employees, illustrating broad industry trends in AI governance challenges and investments.
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