The rise and risks of agent management platforms

Enterprises worldwide have 28.6 million active agents, a figure forecast to exceed 2.2 billion by 2030, according to Statista. The rapid growth of AI agents has given rise to a new technology category: agent management systems. These platforms aim to manage networks of AI agents, providing a digital HR department for AI.

Agent wranglers are required to bring management sensibilities to this growing space. Some vendors are giving it a try, leading to a new technology category, agent management systems, that are tasked with managing networks of AI agents. Shelly Palmer, professor at Syracuse University and CEO of The Palmer Group, notes that agents running outside of management frameworks are essentially the AI equivalent of shadow IT.

"It works until it doesn't, and when it stops working, you have no audit trail, no version control, and no governance to fall back on," she said. Agent management solutions on the market include Google Vertex AI Agent Builder, Amazon Bedrock Agents, Microsoft 365 Copilot, Decagon AI, and Sierra AI, serving various purposes from orchestrating systems to multi-agent automation. Diptamay Sanyal, principal engineer at CrowdStrike, emphasizes the importance of treating agents as infrastructure rather than features.

"The problem is you end up with dozens of agents with no shared context model, no consistent governance, and no reusable patterns," Sanyal said. The big hurdle is that agents all want access to the same data, creating an AI governance challenge. Manu Narayan, CIO at GitLab, warns that if you don't build your AI stack intentionally, you could end up with dozens of vendors, and all of their agents, holding the keys to the kingdom.

Monika Malik, a lead data and AI engineer at AT&T, notes that many vendors and internal teams are building agent solutions for specific use cases, but often they lack shared identity models, lifecycle policies, or risk frameworks. Agent management platforms offer benefits such as observability, governance, and value realization. Brian Jackson, principal research director at Info-Tech Research Group, notes that these platforms enable governance by "using a central policy to set guardrails for what agents can and can't do and keep them aligned with enterprise goals." However, the competition between vendors to own the agentic management space is fierce, and professionals should prioritize flexibility when moving to an agent management platform.

Experts stress the importance of involving cross-functional stakeholders, including security, data, and business leaders, in decisions about agent management platforms. "The primary obstacle is averting fragmented adoption," Malik said. "Organizations should view agent platforms as long-term operating infrastructure, not just another purchase of an AI tool."