Why enterprises need an AI control plane for multi‑agent workflows
By Arun Meena, Co-Founder & CEO, RHA OneAI
The conversation about enterprise AI is shifting rapidly from experimentation to operating discipline. Moving from individual agent pilots towards workflows where multiple agents share tasks, tools and information, while maintaining control as the architecture becomes more fragmented, is emerging as a critical technology challenge.
For enterprise technology leaders, including the Chief Information Officer, the Chief Technology Officer and the Head of Information Technology, this makes the control plane an architectural question rather than simply another AI capability.
IBM describes an agent control plane as a system for deploying, operating, monitoring, and governing AI agents across the organisation. IBM recently introduced an agentic control plane within Watsonx Orchestrate, indicating that agent governance is becoming a defined enterprise technology category instead of just an architectural concept.
An individual agent typically receives a task, retrieves defined data and produces an output, whereas a multi-agent workflow...
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