Avoiding the ‘multiple Agents’ trap

Why support is best placed to lead

Support teams have something no other function has: operational experience running AI at scale in a high-volume, high-stakes environment. They know how Agents perform in the real world, what breaks, what improves with better content, how to manage handoffs, and how to build feedback loops that drive performance over time. As Bobby Stapleton, Senior Director of Human Support at Fin, puts it: “You already manage the most complex, high-volume customer interactions; you have rich data on customer needs and behavior; and you know how Agents perform in the real world. Those insights will be invaluable as AI scales across your business.”

That expertise is what other departments are missing when they launch independently. Support can function as a center of excellence by setting shared standards, defining guardrails, and sharing hard-won knowledge about what actually works into the broader rollout.

How to act on the opportunity

Given the signal that many businesses recognize support’s expertise in effectively rolling out AI, here’s how to step up and take the lead.

Make the case for unified ownership early

The most effective organizations establish a central function, often anchored in support, that owns the standards, the content architecture, and the cross-functional coordination.

If the conversation about establishing a central function with a dedicated owner for AI hasn’t happened in your organization yet, initiate it. Frame it around the customer experience risk by asking what happens when a customer gets inconsistent answers from sales and support? What happens when no one owns the connection between those two touchpoints? The case for centralized ownership is easier to make before things fragment than after.

Bring your knowledge infrastructure with you

One of support’s biggest advantages is its content operation. Your knowledge base, resolution data, and deep understanding of what customers actually ask is the foundation an AI system needs to perform well.

Before other departments build their own content from scratch, identify what already exists in your knowledge base that’s relevant to their use cases. In many cases, you’ll likely find a significant overlap. A unified content layer, maintained by a team with experience managing it, is far more valuable than siloed knowledge that gets out of sync.

Define shared standards before deployment, not after

Guardrails are much easier to establish before Agents go live than to retrofit once they’re running. Work with the teams planning to deploy AI to agree on: what the Agent can and can’t do, how it handles escalations, what “good” looks like in their context, and how performance will be measured.

Support teams have already worked through these questions and that expertise can be exported to the rest of business.

Track the cross-functional customer experience, not just departmental metrics

Once AI spans multiple parts of the customer journey, individual team metrics stop telling the full story. A handoff from a Sales Agent to a Support Agent might look fine in isolation but create friction for the customer. Build ways to track the experience across touchpoints – customer effort, consistency of information, and resolution across stages.

Where to get started

Map your current and planned AI deployment against the full customer journey. Identify every point where a customer could move between your Agent and another department’s.

For each transition, ask: will the receiving team have the context they need? Will the experience be consistent? Wherever the answer is no, that’s where fragmentation will show up first – and where support expertise can make the biggest difference.