Workato Otto: an agent that takes a goal instead of a recipe

For most of its history, Workato has been a tool for building recipes: someone decides the steps, and the platform runs them. On 5 May, Workato launched something different. Otto is an AI agent that is given a goal and works out the steps itself, across the company’s applications, while IT keeps control of what it can reach.

What Workato launched

Workato describes Otto as a trusted AI teammate. According to the announcement, it:

• runs around the clock in the cloud and keeps working on a task without someone watching it,
• handles multi-step work such as data analysis, reports and writing code, and can coordinate with other people along the way,
• is available in Slack, Microsoft Teams and other enterprise applications,
• reaches business systems through Workato Enterprise MCP, which Workato calls the control and action plane for enterprise AI.

The governance features are the same ones Workato already offers for integrations: role-based access, audit trails for every action, logging and credentials that are kept separate from the agent. Workato says more than 1,000 people already use Otto every day in an early programme. General availability was described as coming soon, without a date.

Why it matters

The interesting part is not that Workato has an agent. Most iPaaS vendors do. It is where the agent gets its access. Otto does not get its own direct connections to Salesforce, SAP or Workday. It uses the same MCP layer, with the same connectors, permissions and logs, that the integration team already runs.

That is the argument integration vendors are making in the agent market: the hard part of an enterprise agent is not the model, but safe and auditable access to business systems. An integration platform already has that access, so it can offer agents that IT is willing to switch on.

How it compares

Otto competes on two fronts. Against general AI assistants, Workato’s argument is control: the assistants are good at reasoning but need a governed way into business systems. Against other iPaaS vendors, the comparison is about how much of the agent is built in. Several vendors offer tools for building agents, while Otto is a ready-made agent that business users can use directly.

The risk with an agent that works on its own for a long time is the same as with any automation that no one watches: small errors can grow before anyone notices. Logs and approval steps are only useful if someone reads them.

What to ask

1. What can the agent reach? Check whether Otto’s access follows the same roles and connectors as your existing recipes, or whether it needs broader rights.
2. When does it stop and ask? Find out which actions require a human to approve, and whether you can set that per system or per type of action.
3. Who owns the results? Decide who is responsible for a task Otto has done, and how its work is reviewed after the fact.