The future of AI is evolving fast — but you don’t have to wait to start seeing results. Today, organizations are looking for ways to take advantage of powerful new capabilities while preserving the workflows and systems their teams already trust. At interop.io, we’ve uncovered how interoperability can create new possibilities for your AI strategy – specifically through what we call the “Agent-in-the-Loop” approach — a natural extension of our commitment to Human-Centered AI.

Understanding Human-in-the-Loop and Its Importance

The term “Human-in-the-Loop” refers to the critical role humans play in high-risk workflows where oversight is essential. This approach ensures appropriate human supervision and intervention at key decision points, as a checker with accept/reject responsibilities.

Human-in-the-Loop has become particularly important with the rise of autonomous AI agents (also known as agentic systems) designed to perform tasks with minimal human intervention. In these scenarios, humans typically act as supervisors or approvers, stepping in primarily at the beginning to set parameters and at the end to review outcomes (and additionally as “trainers” to coach the AI if it behaves errantly).

Human-in-the-Loop is important to AI and human processes, but when you add interoperability to the mix, the AI and human relationship becomes more of a partnership.

Introducing Agent-in-the-Loop: A Collaborative Extension

The benefits of a fully agentic approach to business are potentially significant — but the risks are still uncertain. That’s why we advocate for a Human-Centered approach to AI, where AI acts as a highly capable and experienced assistant, working alongside the user.

While traditional Human-in-the-Loop models focus on oversight, everyday enterprise workflows can benefit from deeper collaboration between humans and AI. That’s where our concept of Agent-in-the-Loop comes in: bringing AI into the human-centered, interoperable environments that teams already trust.

With io.Connect, AI and users work together inside apps that have workflows, logic, permissioning and guardrails already in place. Rather than constructing entirely new processes around AI systems, the Agent-in-the-Loop model integrates AI capabilities into existing human-centric workflows, allowing users to interact with the workflow using tools that are already in production.

This isn’t about replacing one approach with another—it’s about expanding the possibilities for human-AI collaboration, while providing the perfect framework to start learning the best ways for AI to support your business.

The Difference in Practice

In traditional Human-in-the-Loop models, humans typically:

• Define a task for the AI to complete
• Wait for the AI to work through the process
• Review and approve (or reject) the final output

With Agent-in-the-Loop (especially using ChatUI interfaces), humans and AI:

• Work together throughout the entire decision-making process, using familiar tools and applications.
• Keep the human as the orchestrator of the workflow, with AI acting as a trusted assistant.
• Use AI to offer insights, assistance, and take direct action inside user applications in real time.
• Collaborate inside existing applications, interfaces, and standards (such as FDC3), instead of needing new platforms.

The Strategic Advantage: Interoperability + AI

With io.Connect and Model Context Protocol (MCP), bringing AI into your current workflows is remarkably straightforward. There’s no need to break down or disrupt existing processes – the AI fits right in through our interoperability layer as an optional enhancement.

Interoperability combined with AI delivers significant advantages for organizations navigating the AI landscape and making decisions around how AI fits into their future strategy.

What are the benefits?

• Enables iterative adoption: Rather than making large upfront investments (and gambling that these solutions will be the right pick), you can introduce AI capabilities piece-by-piece into your existing workflows.
• Future-proofs your AI strategy: Who knows where AI technology will be in six months, let alone five years? By using interoperability to integrate AI into your systems today, you create flexibility to adapt as new capabilities emerge. For example, down the road you may need to change the balance between Agent and Human as systems progress, and your understanding of the limits and capabilities of AI develops.
• Reduces investment risk: Instead of committing to expensive specialized AI platforms and hiring teams of AI specialists for a monolithic approach, you can start leveraging AI value immediately within your current environment.
• Provides immediate practical value: The Agent-in-the-Loop approach answers the critical question: “How can you make AI work for you, right now?” By bringing AI into existing workflows, you get immediate and safe benefits without waiting for perfect solutions.
• Builds on proven foundations: Your interoperability platform becomes the stable foundation for AI experimentation and growth, letting you evolve your approach as technology advances.

Implementing Agent-in-the-Loop Today

If you already have an interop platform in place (and a bonus if you have a ChatUI interface already implemented) you can get started today. The MCP creates a bridge between these conversational AI systems and your existing applications, enabling the AI to access context and take actions.

This is good news for our clients who have already invested in interop-enabling their applications. They’ve laid the groundwork to safely AI-enable their workflows — quickly, and with minimal risk.

The Future of Work: Build the Right Foundation Now

Organizations that build a flexible, interoperable foundation today will be best positioned to adapt as AI capabilities expand — and as expectations for governance, transparency, and collaboration evolve.

Agent-in-the-Loop gives you a safe, scalable way to put AI to work immediately, while giving your teams the space to learn, adapt, and stay ahead of the change that’s already underway.