Data entry was a big part of the economy ten years ago. Companies needed legions of workers to populate their tables and datasets, ensuring they had the foundations for their business intelligence systems. They needed it all for “big data,” a term that almost seems irrelevant at the tail end of 2025, thanks to the relentless march of AI.
However, now even this task seems likely to be taken over by AI. Now, systems like Apryse’s Smart Data Extraction SDK Evaluation are changing the game completely, enabling far more automation than ever before. Oversight and high-stakes verification are still recommended in many situations, but it is clear that machines are becoming increasingly more accurate.
“Many people think that the key technology that enables machines to carry out data entry is optical character recognition,” Apryse explains. “However, it is much more than that. New tools can actually model the structure of the data and make intelligent decisions about where new data should be added when creating or updating existing datasets. Multiple overlapping AI systems work in tandem to recreate human-like results with minimal time and cost.”
The Scale Of Automation
The scale of automation is actually quite remarkable, according to industry insiders. Entry-level manual work, such as data entry, was once something highly sought after by interns. But now, scanning with cameras and feeding information into AI is changing everything.
The need for staff to scan documents and enter the data they contain manually is slowly disappearing. Human workers engaged in this task typically have an error rate of between 2% and 5%, which is relatively high, especially when dealing with smaller datasets that are more susceptible to inaccuracies. By contrast, a lot of AIs have error rates in the 0.1% range, meaning that they only make one mistake for every one thousand entries that they make.
Many people are noticing that data entry tasks are disappearing from their roles due to this technology. For example, historically, it has been challenging to automate conversions from PDF to a spreadsheet. Workers had to do it all by hand (unless they could somehow find the original XML file). However, that’s all changed with this new technology. AI is able to implement vision systems similar to humans, but without cumbersome hands to slow down the transcription process.
“Even the government is now looking into whether it can make better use of AI in data entry,” explains Apryse. “Officials see it as a way to boost efficiency and enable workers to get more done in a given space of time, especially with so many demands from the public for superior service.”
Why Data Entry Is Vulnerable
The primary reason data entry is vulnerable to automation is that it leverages AI’s strengths. Artificial intelligence systems love to engage in repetitive, rule-based tasks, and that’s essentially what data entry has become in the modern workplace. Like humans, systems simply scan information on one page, store it to memory, and then copy it to another page.
The only issue right now getting in the way of full automation is the so-called “edge cases”. While humans can deal with these issues by applying common sense, machines struggle because they find it challenging to step outside their training data.
Hybrid Roles
For this reason, many hybrid roles are persisting. These often require a human to initiate the AI-based data entry program, then check and evaluate the results for accuracy. Sometimes, AIs can misread characters while humans are better able to understand the context.
“The fact that data entry now takes far less time is important,” explains Apryse. “It means that workers can focus on higher-value tasks, like engineering better prompts and enabling higher throughput. With AI, companies can process hundreds of times more data without needing to hire hundreds more staff, enabling more data mining from existing employees.
This change in the data entry market is affecting nearly all white-collar work. The idea that people should be spending their days entering data is now coming to an end, according to many. But, as with spreadsheets getting rid of manual ledgers, it is likely that AI will simply push the required human input back a notch, potentially creating more skilled jobs overall, and enabling wages to rise once more.
Of course, some in the industry are pessimistic. Anthropic’s CEO has famously stated that he believes AI could lead to permanent unemployment rates of 20% or higher. Meanwhile, optimists point out that the gains from AI massively outweigh the losses, enabling companies to take more risks with the number of people they hire.
Reskill
There’s also a race among many firms to reskill their staff so that they are ready to take advantage of new AI technologies as they arrive. Firms that are well-positioned to benefit from these features are much more likely to be the ones that massively progress in the future and outwit their opponents.
Workers, too, can pivot. For example, many are now learning AI prompting so that they can be more beneficial to employers leveraging AI tools. Others are learning Python to enhance their analysis skills, or delving into more advanced areas like verification, which involves verifying data in high-stakes situations.
There is also a general shift in direction toward creative judgment. Many people are shifting their focus away from rote tasks and toward things that truly make a difference in their lives.
Lastly, many workers are simply using AI in the same way companies do to further their own financial objectives. In many ways, artificial intelligence has become a great equalizer, giving every worker the equivalent of a team of smart postgraduate students in their pocket.
“AI is essentially eliminating a lot of rote tasks in many roles, including data entry,” says Apryse. “This means that existing workers are upskilling and looking for new opportunities to engage in higher-value activities. It is an exciting time to be a company owner, and an exciting time to be alive,” the brand explains.
Photos by Tima Miroshnichenko and Artem Podrez; Pexels
