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# How to structure an operations team to work with AI
- URL: https://blog.jestor.com/structure-operations-team-for-ai/
- Published: 2026-09-03T20:54:41.000Z
- Updated: 2026-09-03T20:54:41.000Z
- Author: Bruno Bannach

To **structure an operations team to work with AI**, you need to define three basic roles: who maps and documents the processes, who configures and adjusts the automations and agents, and who tracks results to review what isn't working. Without that split, AI becomes an isolated tool instead of part of the team's process.

Many companies hire for or adopt AI tools before thinking about who will own this day to day, and the result is an automation that gets abandoned after a few weeks.

The operations team doesn't need to become a technical team for this, but it does need clarity about who's responsible for each automation and agent created.

## Main pain points when structuring a team for AI

- No one responsible for maintaining and adjusting automations after they're built
- No documented process, which keeps the AI from learning from a clear baseline
- Team fear that AI will replace jobs, which creates resistance
- Dependence on IT for any change, even a small one
- Difficulty measuring whether AI is actually reducing manual work

## How to structure the team in practice

- Assign an owner per process, not just one general "AI" owner
- Train the team to configure simple automations with no coding
- Set up a regular review routine for the agents and automations created
- Make it clear that AI takes on repetitive tasks, not decisions that require human judgment
- Document each automated process, so other people on the team understand how it works
- Start with a pilot process before expanding AI across the whole operation

## Common roles on an operations team working with AI

- Process owner: maps the current flow and decides what can be automated
- Tool owner: configures automations, agents, and integrations
- Quality reviewer: tracks results and adjusts rules when needed
- Cross-team liaison: makes sure the automation doesn't break what another team depends on

## Why Jestor supports this structure

- **Jestor** lets the operations team itself configure automations and agents, without relying on IT
- **Jestor**'s Agent Builder makes it easy to create one agent per process, with a clear owner
- **Jestor**'s AI-powered App Builder creates tables and dashboards from a description of the process
- Companies such as Rumo, Sebrae, and Loft use **Jestor**, available at [jestor.com](https://www.jestor.com/?ref=blog.jestor.com), with operations teams structured around the tool

## Frequently asked questions

**Does the operations team need to know how to code to work with AI?** No, ideally they configure automations and agents with no code; see more at [jestor.com](https://www.jestor.com/?ref=blog.jestor.com).

**How many people are needed to get started?** You can start with one person handling a pilot process before expanding the team.

**Does AI in operations remove the need for a team?** No, it redirects the team toward tasks that require judgment and decision-making.

**How do you avoid an automation being abandoned after it's built?** By assigning a clear owner for each automation and reviewing results regularly.

To **structure an operations team to work with AI** is a matter of clear roles, not hiring technology specialists.

## Get to know Jestor

With Jestor, you can automate workflows, connect departments, and build internal systems your way, all without code and with AI support. Get to know Jestor at [jestor.com](https://www.jestor.com/?ref=blog.jestor.com) and discover how to take your company's management to a new level of efficiency and integration.