Enterprise AI is entering a more difficult phase. The first wave largely involved systems that assisted employees with recommendations, analysis, or content. Agentic AI changes that equation. Agents can increasingly act on enterprise systems, interact with infrastructure, generate machine data, and participate in security and IT operations.Now that creates a different risk. Enterprises are giving AI more autonomy at a time when many are still working out what those agents can access, what actions they can take, how much they cost to operate, and when humans need to intervene.Recent Cisco and Splunk announcements span agent observability, Cisco Data Fabric, private AI infrastructure, and agentic capabilities across security operations. The common thread is visibility into agents, machine data, costs, and the actions increasingly being handed over to AI systems. Do you think it is very hard to control something that can learn anything very quickly ?
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