HP, Allianz Partners, and ABN Amro are among the growing list of companies announcing large-scale layoffs while pointing to artificial intelligence as a driver of productivity gains. Public attention has focused on customer service, where chatbots are already replacing human agents. But a far larger workforce may now be exposed: AI document processing. Across finance, insurance, legal, and administrative functions, millions of jobs rely on manual document handling, precisely where AI is advancing the fastest. How far will this wave go?
If a Task Can Be Precisely Explained, It Could Be Handled by AI
Just a year ago, many companies remained skeptical about large language models. Concerns around hallucinations and reliability made AI appear unsuitable for enterprise-grade use cases, and real-world deployments at scale were still rare. That perception is now shifting rapidly.
“A year ago, AI was widely seen as unreliable for enterprise applications. Today, CEOs have a far more mature understanding of what AI can realistically handle. We increasingly see companies moving toward smaller teams overseeing semi-automated, AI-driven processes,” says Jules Ratier, founder of Koncile, an AI document processing company.
Insurance claims management, customer document review, identity verification, accounting operations, procurement workflows, and analyst work all share a common trait: they involve large volumes of documents that must be opened, read, structured, and validated. These tasks consume enormous amounts of human time, yet follow well-defined rules.
A simple rule of thumb is emerging inside organizations: if a task can be fully explained, step by step, with limited external context and few edge cases requiring human judgment, it is increasingly suitable for AI automation. The fewer human interactions, subjective decisions, or emotional considerations involved, the more exposed the task becomes.
No Industry Is Immune to This Shift
Document processing is not a niche activity. Studies from IDC, McKinsey, and Gartner show that 20% to 30% of white-collar work in large organizations is directly tied to handling documents: reading files, extracting data, validating information, and moving it across systems. Office employees spend 10% to 25% of their working time on manual data manipulation alone, including copy-paste and data entry. On average, this represents 2 to 5 hours per week, more than 50,000 copy-paste actions per year, and up to 2 hours per day spent searching for documents before they can even be processed.
This hidden workload explains why AI-driven automation is having such a disproportionate impact. In 2025, more than 130,000 job cuts publicly linked to AI adoption were reported worldwide, with document-heavy roles among the most exposed. Large banks, insurers, and enterprise software providers now report productivity gains of 30% to 60% once document workflows are automated end to end. What was long considered routine administrative work has become one of the most powerful levers for cost reduction and workforce reshaping, across virtually every industry.
Why AI-Savvy Employees Are Becoming More Valuable
As automation expands, the profile of the “ideal employee” is also changing. Companies are reshaping what they expect from their teams.
Routine execution is losing value, while the ability to supervise, configure, and improve AI-driven systems is becoming a differentiator. Employees who understand how AI tools work, how to monitor their outputs, and how to intervene when exceptions arise are increasingly promoted into higher-responsibility roles.
Non-technical employees are now directly contributing to automation, thanks to AI tools that are far more accessible and easier to operate than previous generations of software. Document automation is no longer the exclusive domain of developers or data scientists. “We now see teams with no engineers at all running full invoice data extraction projects on their own. That would have been unthinkable three years ago,” says Jules Ratier.
