One of the more boring but most important aspects of AI is its ability to take messy data—like PDFs and tables—and organize it.

While AI often impresses with its latest capabilities, the business world moves more slowly and, in many cases, still runs on paper. Before LLMs, turning a printout into digital data required the document to be fairly clean and standardized.

To understand the current state of this market, known as document processing, I spoke with Alan Pelz-Sharpe, founder of research firm Deep Analysis and an analyst who has covered this space for more than two decades.

This interview has been edited for clarity and length.

“I’ve been an industry analyst 26 years. I’ve always covered document management and workflow. One of the reasons is it doesn’t matter whether it’s a boom or a recession — there’s always a need for document management. It’s the most boring topic in technology by a country mile, but at the end of the day, what is the currency of business? Whether it’s finance, whether it’s supply chain — it’s documents, and it always will be.”

“In this world of agentic AI and generative AI, when you really look at the projects, where do they all start? Documents. We have this world now we call intelligent document processing. Take Salesforce — up until two years ago, they didn’t do document processing. Now they do, because if they’re going to have an agentic future, documents are a real part of it.”

“Within the last decade, unstructured data — PDFs, Word docs, videos, anything not neatly in a database — has gone from hard to handle to central to AI. We track well over 400 vendors in that space. Roll the clock back ten years and I could have named you ten. It’s been an explosion.”

“Roughly 80% of enterprise data is unstructured. Up to now, when you think about data lakes, data warehousing, ETL, business intelligence — it’s been focused on the 20%. That’s a massive shift. You can now process invoices or contracts without a human ever looking at them. There’ll always be exceptions, but that’s transformational.”

“If I’m using AI to process invoices, what am I going to a worldwide network of data centers for? You’re burning a lot of compute power to process an invoice. It should cost a fraction of a penny. I can run run that task with a small language model on premises.”

“Tech moves quickly, but the real world doesn’t. It’ll happen slower than investors want. We finally have the technology to read the world’s documents — now we’ve got 40 years of paper, mainframes, and custom code to untangle. Customer service and invoice processing are the low-hanging fruit. Beyond that, it’s going to take time.”