AI isn’t coming for your service team – it’s already here. While companies are considering which tasks AI can automate, a more strategic question is being overlooked: Who’s managing the AI? As AI agents embed themselves into service operations, executing tasks, resolving issues, and even guiding human colleagues, it’s time to stop thinking of them as tools. They’re coworkers. And just like human employees, they require oversight, accountability, and integration into the broader service team design.
The AI Agent as Coworker – Not Just a Tool
The legacy metaphor of AI as a “tool” no longer fits. Tools don’t make decisions. They don’t escalate edge cases or trigger workflows. Today’s AI agents triage service requests, fetch data from back-office systems, generate responses, and prompt human action. They operate continuously and autonomously, like a digital team member executing their part of the process.
If that’s the case, why don’t they appear in your org chart? Why don’t they have defined responsibilities, escalation paths, and performance metrics? The reality is, as organizations expand their operational capacity with AI agents, most haven’t built the management structures to support them.
The Unmanaged Workforce Problem
This lack of supervision creates risk. AI agents are scaling across channels and use cases without a clear owner. As a result, companies face a new kind of fragmentation: not just between systems, but between humans and machines.
Consider this: would you hire 100 interns and give them access to your customer systems without a supervisor or a feedback loop? That’s effectively what’s happening in many service organizations. AI agents are deployed to automate customer interactions and internal workflows, but without a formal governance structure, their performance is opaque and their alignment with CX goals is uncertain.
The result? Inconsistent experiences, unmonitored errors, and missed opportunities to optimize.
What Real AI Management Looks Like
Managing AI requires more than usage dashboards. It demands a rethinking of service operations. Start by treating your AI agents like part of the team:
- Define roles and responsibilities: Where does the AI agent take over, and where does a human step in? What tasks are delegated? What decisions are they authorized to make?
- Design escalation paths: When an agent encounters uncertainty, how does it hand off? Who owns the outcome?
- Monitor and coach: Just as you review agent performance, AI agents also need feedback, from logs, from customers, and from humans in the loop.
- Support team coordination: AI agents must integrate with human workflows, not just operate in parallel. A human agent should know what their AI counterparts have done and vice versa.
In short, AI agents need a place on the org chart. Not necessarily in a literal sense, but a mental model and operational structure that defines their place in customer experience.
Design Before Deployment
The place to start is with intentional design. Before deploying AI into your service flow, you must know what kind of experience you want to deliver. What does a “delightful” interaction look like in your brand voice, across your channels, with your unique customers? Only then can AI be shaped to enhance, rather than dilute, that experience.
That design work doesn’t just determine the quality of your customer experience – it defines the roles your AI agents will play. It tells you what they need to know, how they should interact with their human teammates, and what success looks like for them. In essence, your service experience blueprint becomes the operating manual for your AI workforce.
In my next post, I’ll dig deeper into what modern service experience design looks like in an AI-first world, and why it’s the critical foundation companies cannot skip.
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