Human in the Loop: What It Is and Why It’s Important 

By Steve Hatajlo

We live in an era of automation, smart systems, big data pipelines, and yet the world of transactional documents, supplier files, purchase orders, invoices, spreadsheets, and scanned attachments remains messy.

I’ve talked with business owners and managers who have looked at their manual processes and want to, “just automate it all,” but the reality of their daily life includes digital and paper documents. The dream of automating is rooted in the reality that this would require a technology upgrade and employee upskilling. Not to mention the fact that the behavior and workflow of your customers or vendors would also need to change.

You need trained, skilled humans to help run these systems/processes. That’s why at FSI, we have a “human-in-the-loop” approach.

Defining Human-in-the-Loop

It’s not a term from a sci-fi TV show. In plain terms, Human-in-the-Loop means you combine machine processing (data parsing, transformation, validation) with the oversight, correction, judgement and context of a human being. Machines go fast; humans catch what machines miss.

Why is this relevant for you? 

Because you don’t operate in an ideal world with perfect, standardized data streams. Your trading partners don’t all send the same format. Your suppliers change templates without warning. Some customers still fax. Some attach scanned PDFs. Some send Excel files with merged cells and formulas leaking into the wrong columns. And every one of those documents still needs to get into your system cleanly and reliably.

Automation alone can’t promise that.

Human-in-the-Loop gives you something machines can’t provide on their own. 

We’ve all tinkered with AI by now, everything from letting it spit out a grocery list to leaning on it for the tougher, messier tasks. It’s great until the task stops being neat and predictable. You need:

• Accuracy when things like layouts suddenly change.
• Judgment when a field doesn’t match expectations
• Intervention when key values are missing or ambiguous
• Protection from garbage entering your ERP or accounting system
• Confidence that exceptions won’t become operational fires
• A human assessment and intervention (i.e. when the sender has crossed something out and hand-written a correction.)

For that, you need human intervention. HITL is relevant for you because you’re not trying to build a perfect digital playground. You’re trying to run a business.

What does Human-in-the-Loop look like in document processing? 

So you might be thinking, “Human-In-The-Loop is just a fancy term for proofreading, right?” It’s a bit more complex when you’re talking about EDI document conversion.

Step 1: Capture & ingestion

A supplier emails you a PDF invoice. A customer faxes an order. A partner uploads a spreadsheet with creative formatting. Machines can ingest and extract the data, but unpredictable layouts, inconsistent quality, and missing fields are the norm, not the exception.

That’s where the human reviewer steps in by verifying that the important fields were extracted correctly (PO numbers, totals, ship-to codes), catching anomalies, and correcting layout-specific quirks before they snowball into downstream problems.

2. Transformation & normalization

Once fields are extracted, they must be mapped into your system structure. That means your data needs to be clean, proper date formats, and valid customer IDs. Machine learning can do streamline this until something unusual appears like an alternate template or a missing reference number

Human-in-the-Loop provides the judgment needed to keep data accurate even when the real world refuses to follow the rules.

Step 3. Validation, exception handling & business-rule enforcement

Machines can check totals and run validations. But when something doesn’t make sense like a mismatched line item, an unexpected discount code, a quantity that doesn’t align with packaging rules, only a human can decide whether to fix it, escalate it, or request clarification.
This is the loop that protects the integrity of your operations. It stops bad data at the door.

Step 4. Feedback & continuous improvement

At FSI, we’re proud of how often our automation gets it right, [percentage] of the time, it just works. But real life doesn’t always cooperate.

And here’s the part people often overlook: if you rely on machine output with zero human intervention, the system doesn’t actually learn. We’re not living in a world of self-aware robots. Models only improve when someone shows them what “right” looks like, especially when conditions change.

That’s why Human-in-the-Loop isn’t optional; it’s how automation evolves. Every correction, every edge case, every exception feeds back into the system. Over time, the pipeline doesn’t just get faster; it gets smarter and more resilient.

Creating a Human-in-the-Loop System is more than entering a prompt. 

Working directly with machine learning tools is still relatively new territory for many teams. AI and machine learning technology has become widely accessible to the public only in the last few years, and while it opens a lot of doors, it also introduces a lot of complexity.

After decades in this space, we’ve learned that building, tuning, and maintaining a reliable document conversion process is never just a technical project. It’s an operational commitment. It requires the right blend of OCR, AI, machine learning, and human oversight, all calibrated to handle even the most unique “messy” cases at scale. That’s difficult for most organizations to stand up internally, and even harder to sustain over time.

If you’re thinking about outsourcing this work, you’re not giving up control. You’re reducing risk, avoiding reinvention, and keeping your staff focused on what they’re actually hired to do. The goal isn’t “no human ever touches it.” The goal is accurate data, delivered consistently, without disrupting the systems you already rely on.

Sometimes the smartest move isn’t doing everything yourself; it’s recognizing when a specialized partner, with the right people and technology, can do it better, faster, and far more reliably.