The Work Before the Work: Where Document Bottlenecks Begin

Land professionals are hired for their expertise: interpreting information, evaluating risk, understanding context, and making decisions.

But before any of that can happen, there is often another layer of work.

Find the right document. Open the file. Locate the relevant language. Review the provision. Capture the information. Verify it. Move it where it needs to go.

Each step may seem small. Across hundreds or thousands of documents, they can become the work that eats the week.

Four Ways to Evaluate a Document Workflow

During his NALTA session on rethinking document management in the age of AI, EAG Senior Land Analyst Richard Courtney offered a simple way to evaluate the health of a document workflow. He pointed to four areas: speed, consistency, flow, and effort.

Speed: How quickly can someone find the information they need?

Consistency: Is information being captured and coded the same way across people and workflows?

Flow: How easily does information move between teams and systems?

Effort: How much work has to happen before analysis can actually begin?

Together, those four areas reveal something that can be easy to overlook: the bottleneck isn’t always the analysis.

Sometimes, it’s everything required to get there.

When the Documents Become the Bottleneck

One project involving roughly 7,500 documents showed what this can look like in practice.

The goal was to extract lease provisions from the document set. But before that could happen, there was a more basic challenge: identifying where the leases were within thousands of files.

The technology to extract the information existed. The documents simply weren’t organized in a way that allowed the team to use it effectively. Classification had to come first.

That’s an important distinction.

Adding AI to a disorganized document workflow doesn’t automatically remove the bottleneck. Before technology can accelerate the work, teams need to understand where the friction actually begins.

Start in the Right Order

A better document workflow starts with the foundation:

Organize. Automate. Apply AI. Integrate.

First, establish structure through metadata, naming conventions, and organized repositories. Then identify repetitive workflows and handoffs that can be automated. Once that foundation exists, AI can support document classification and data extraction. Finally, that information can flow into the land, accounting, GIS, and other systems teams rely on.

The order matters because technology works best when it is applied to a defined problem, not simply layered onto an inefficient process.

Make More Room for the Work That Requires Expertise

The goal isn’t to automate every part of land work.

It’s to distinguish between the work that requires a land professional’s expertise and the work that has to happen before that expertise can be applied.

As Richard put it during his session:

“None of us joined this industry to just type.”

Searching for documents, organizing files, re-keying information, and moving data between systems can consume significant capacity without necessarily requiring the experience teams hired their land professionals to provide.

That doesn’t mean removing people from the process. AI should function as a co-pilot, not an autopilot. Human review remains essential, particularly when interpretation, context, risk, and judgment enter the workflow.

The opportunity is to reduce the work that happens before those decisions so experienced professionals can spend more of their time making them.

Before asking where AI belongs in a document workflow, there may be a better question to start with:

Where is the work before the work happening on your team?

Inspired by Richard Courtney's NALTA session, "Rethinking Document Management in the Age of AI: Moving Beyond Paper-Era Workflows Through Automation, Integration, and Intelligence."