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Working with Human Agents and AI Agents

Published on 2026-10-14

How to share roles between human and AI agents in customer service: complementarity, limits, handovers and supervision explained in practical terms.

Complementarity rather than replacement

The arrival of AI agents in customer service often raises the question of replacement. A more useful approach is to ask what each does best. AI agents can assist on repetitive tasks, retrieve information, suggest wording or handle simple requests. Human agents bring judgement, empathy and the ability to deal with the unexpected.

The right balance varies by profession and topic. It is built by observing what works, not by applying a general rule.

Assigning roles explicitly

• AI assists the human agent during a call: recalling information, suggestions, note-taking.
• AI handles certain simple, well-framed requests alone.
• The human takes over as soon as the situation becomes sensitive or ambiguous.
• Special cases are documented to improve the sharing rules.

The HARX Telephony offer, for example, includes an AI that assists, which illustrates this logic of support rather than substitution. In the TAAS model from HARX.ai, the network of professionals includes certified agents, human or AI, assessed in the same way on results.

Handle the handover with care

The moment a conversation passes from an AI to a human is crucial. If customers must repeat their problem, frustration rises. A good transfer preserves the context: what was asked, what has already been tried, what the customer expects.

It helps to define clear triggers for moving to a human: an explicit request from the customer, strong emotion, a sensitive subject, repeated failure to understand.

Transparency towards the customer

Customers appreciate knowing who they are talking to. Depending on context and applicable rules, it may be necessary to state that part of the exchange is assisted or handled by AI. Find out about the obligations in force in the countries where you operate and favour clarity.

Supervising and assessing both kinds of agents

An AI agent is not infallible, and neither is a human one. In both cases you need to assess interaction quality, spot recurring errors and correct them. Real-time assessment of each interaction lets you react quickly and keep an honest view of performance.

• Regularly listen to or reread exchanges of both kinds.
• Set the same quality criteria for everyone.
• Set up a channel for reporting errors.
• Train humans to work with assistance tools.

Looking after the teams

Starting small and learning

A sensible way to begin is to choose one type of request, define who handles what, and observe for a while. Gather feedback from agents and customers, look at where handovers went wrong, and adjust the rules before widening the scope.

Keep a written record of the decisions taken, so that new team members understand why the work is shared the way it is. The balance between human and AI contributions will keep evolving, and having the reasoning documented makes each change easier to discuss.

Introducing AI can raise worries among agents. Explaining it clearly, involving teams in choosing the uses and showing how the tool lightens tiresome tasks all ease adoption. To explore how humans and AI can coexist within a single task assessed on results, the TAAS approach from HARX.ai provides a framework for thought.

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