Workato AIRO: from building integrations to describing outcomes

At its World of Workato conference in Las Vegas (22–24 September 2026), Workato did more than add features. It changed how it wants customers to think about the platform. AIRO, a multi-agent system, is now the main interface for building, deploying and governing automations and AI on Workato.

What was announced

AIRO is meant to help users analyse a business process, suggest improvements, design the solution, test it and fix problems. Around it, Workato launched several new layers:

• Live Process Graph gives AI context about how the business actually works: documented policies, the processes that have been designed, and what really happens at runtime.
• Enterprise AI control plane is a governance, security and cost layer for AI assets, including assets built outside Workato.
• AI Gateway covers model, MCP, agent and API traffic. Its Model Gateway picks between OpenAI, Anthropic, Gemini, open-weight or custom models based on cost, latency, geography and data sensitivity.
• AI Registry is a central catalogue of approved AI assets.
• Agent Evals scores deployed agents on correctness, tool selection, policy adherence, safety and outcome quality.
• Workato XChange is an internal marketplace for reusable MCP servers, agents, APIs, connectors and workflows.

Why it matters

The interesting part is the shift in model. Traditional iPaaS asks you to specify how: which trigger, which mapping, which error handling. Workato now argues that users should describe the outcome they want and let the platform work out the execution. diginomica calls it a move from implementation to intent.

For buyers, this changes the evaluation. The question is no longer only “how many connectors do you have?” but “how much context does the platform have about our processes, and can we trust what it decides?” Live Process Graph is Workato’s answer to the second part: agents need business context, not just API access.

It also positions Workato as a neutral control layer across AI vendors. That is a direct answer to a real worry in many organisations: agents are being built in many places at once, with little shared governance.

How it compares

Workato is not alone. MuleSoft launched Agent Fabric at Dreamforce the week before, with a registry, governance and cost control for agents regardless of where they were built. Boomi has Agent Control Tower and an MCP registry in its API management. The vocabulary differs, but the direction is the same: the integration platform wants to be the place where AI agents are registered, governed and connected to business systems.

What sets Workato apart this time is the ambition in the user experience: one conversational front door for everyone, from business users to integration specialists.

What to watch

diginomica notes that the intent-based model is still at an early stage. Three things are worth following:

1. Transparency. When the platform chooses how to execute, can architects still see and control what happens? This matters for audits and incident handling.
2. Model Gateway in practice. Routing between models on cost and sensitivity is attractive, but the policies must be set by you, not the vendor.
3. Lock-in. A neutral control layer is only neutral if assets can be moved. Ask how agents, evals and registry entries can be exported.

If you already run Workato, the new capabilities are worth testing on a limited process with clear success criteria. If you are evaluating platforms, ask all vendors the same questions about agent governance. That is where the market is competing now.