How AI tools are revolutionizing document management.

AI is changing how we understand and process documents.

Most of the information companies collect no longer fits into tidy spreadsheets. IDC projects that by 2025 roughly 80 % of all data will be unstructured—think PDFs, emails, scans, chat transcripts, and images. Sifting through that mountain by hand is slow, error-prone, and expensive.

What “document AI” does

Modern platforms blend optical character recognition, large language models, and workflow automation. They read a scan that’s slightly tilted, decide whether it’s an invoice or a contract, pull out the fields you need—total due, renewal clause, patient ID—and flag anything unclear for a quick human check. Once the fields are captured, an API posts them straight into the finance or case-management system, so no one re-keys data.

A market growing fast

Analysts value the intelligent-document-processing (IDP) market at about US $2.3 billion in 2024, with forecasts of 25-30 % compound growth for the rest of the decade.

What the results look like in real life

• Omega Healthcare, which processes 250 million medical-billing transactions a year, plugged UiPath’s Document Understanding into its workflow. The system now automates 60–70 % of client paperwork, saving 15 000 employee hours every month, cutting documentation time by 40 %, and hitting 99.5 % accuracy.

• Bain & Company’s 2024 Automation Scorecard shows that firms already deep into automation cut process costs by 22 % in 2023, while laggards managed only 8 %.

Broader productivity upside

A Thomson Reuters survey of knowledge workers finds they expect AI to free four hours per week today and up to 12 hours a week by 2029—around 200 hours a year per person. McKinsey estimates that pairing generative AI with other automation could lift annual labor-productivity growth by 0.5–3.4 percentage points across the economy.

How to get started without boiling the ocean

Pick one high-volume document where errors hurt—say, invoices or insurance forms—and pilot an off-the-shelf tool. Keep people in the loop for edge cases; their feedback improves the model and keeps auditors happy. Track three numbers: time per document, error rate, and re-work hours. If you aren’t seeing double-digit gains within a quarter, adjust the workflow or pick a different document type.

Bottom line

Document AI doesn’t just read faster; it turns a backlog of unstructured files into clean, structured data your systems—and people—can act on. The companies that automate now are opening a growing efficiency gap over those that stay manual.

Sources

• IDC projection that 80 % of data will be unstructured by 2025 – IBM Think blog citing IDC research.ibm.com

• Intelligent Document Processing Market Size report, Global Market Insights, 2024 (valued at US $2.3 billion).gminsights.com

• “Omega Healthcare is using AI to save employees 15 000 hours a month,” Business Insider, June 2025.businessinsider.com

• Automation Scorecard 2024: Lessons Learned Can Inform Deployment of Generative AI, Bain & Company.bain.com

• “AI set to save professionals 12 hours per week by 2029,” Thomson Reuters press release, 2024.thomsonreuters.com

• The Economic Potential of Generative AI: The Next Productivity Frontier, McKinsey & Company, 2023.mckinsey.com