---
title: "New research: Customer service team evolution"
description: "An analysis of 166 interviews examines how customer service roles, workflows, and team structures changed after adopting Fin or similar AI agents. Using interviews with Intercom customers or prospects, the researchers cleaned conversation transcripts with Python and coded them through the OpenAI API against a closed codebook. Workflow disruption was reported by 94.58% of participants, while 82.53% reported changed responsibilities; 27.71% reported headcount or hiring effects, and 6.02% reported changed team structures or reporting lines. The findings describe hybrid human–AI operations in which AI handles triage, routing, translation, repetitive responses, and some refunds, while people increasingly oversee quality, testing, metrics, and complex or sensitive interactions, although organizational strategies and required skills remain uneven."
---

# New research: Customer service team evolution

[Intercom](https://yomu.fyi/company/intercom) · Emiliano Melchiorre · Jan 5, 2026

**Type:** Explainer

## Summary

An analysis of 166 interviews examines how customer service roles, workflows, and team structures changed after adopting Fin or similar AI agents. Using interviews with Intercom customers or prospects, the researchers cleaned conversation transcripts with Python and coded them through the OpenAI API against a closed codebook. Workflow disruption was reported by 94.58% of participants, while 82.53% reported changed responsibilities; 27.71% reported headcount or hiring effects, and 6.02% reported changed team structures or reporting lines. The findings describe hybrid human–AI operations in which AI handles triage, routing, translation, repetitive responses, and some refunds, while people increasingly oversee quality, testing, metrics, and complex or sensitive interactions, although organizational strategies and required skills remain uneven.

## Context

The research draws on 166 interviews conducted with Intercom customers or prospects between 01-01-2025 and 14-10-2025. The sample is reported as representative at a 90% confidence level with a ±6.4% margin of error, while the excerpt notes that the study data came from interviews focused on participants’ individual experiences.

## Approach / What changed

The researchers retrieved interviews from Gong using Snowflake, cleaned each conversation corpus with a Python script, removed common English stopwords and non-participant speech, then used the OpenAI API and a prompt to assign closed codes from a defined codebook. The codes covered workflow, role, headcount, team-structure, and other organizational changes linked to Fin or similar AI products.

## Takeaways

- 94.58% of participants reported workflow or process changes, including automation of triage, routing, translation, repetitive responses, testing, and escalation flows.
- Customer service work is shifting toward AI oversight: people review outputs, monitor metrics, test behavior, improve automation, and handle queries that require nuance or sensitive judgment.
- 27.71% reported headcount or hiring impacts, including Tier 1 reductions, hiring slowdowns, or freezes; some organizations instead reallocated staff or created AI-focused roles.

## FAQ

### Which customer service tasks are increasingly handled by AI agents?

The research identifies ticket triage, routing, translation, repetitive responses, refunds, and some sales-process tasks as activities handled by Fin or similar AI systems. Customer interactions may enter the AI agent first, with human review when it cannot resolve the issue.

### What new skills and responsibilities are becoming important for support teams?

Participants described greater demand for data analysis, quality assurance, debugging, AI testing, metric monitoring, and cross-functional communication. Agents and managers increasingly oversee AI performance and automation rather than handling only basic customer queries.

### Did every company reorganize its customer service team in the same way?

No. Some organizations created specialized AI teams or roles such as automation managers and Fin owners, while others retained traditional structures or reallocated existing staff. The research says the transformation is widespread but uneven, and long-term role strategies remain unclear for many companies.

**Tags:** [AI Agents](https://yomu.fyi/topic/ai-agents), [Automation](https://yomu.fyi/topic/automation), [Research](https://yomu.fyi/topic/research)

- Source: [Intercom](https://www.intercom.com/blog/new-research-customer-service-team-evolution)
- Source URL: https://www.intercom.com/blog/new-research-customer-service-team-evolution
- Ingested by Yomu: 2026-09-17T14:12:52.903Z

[Read original post](https://www.intercom.com/blog/new-research-customer-service-team-evolution)