AI's Untapped Goldmine: Automating Data Entry
We never expected data entry to become one of our biggest opportunities at Nomad Data. When we created Doc Chat, we aimed for complex AI applications. But customer after customer kept asking about the same thing: "Can this help us with our data entry problem?"
It became impossible to ignore.
Companies across every industry face an avalanche of documents. They employ teams of people whose sole job is extracting specific information and inputting it elsewhere. When we looked closer, we realized something surprising.
Even the most complicated use cases ultimately boil down to data entry.
The only differences? The complexity of the task, the cost of the employees, and the time required to complete it.
The Hidden Data Entry Problem
This challenge isn't limited to any single industry or business type. It's everywhere.
Insurance brokers manually extract information from thousands of client policy documents. Wealth managers wade through dozens of investment statements per client, all in different formats. Private equity firms review thousands of employment agreements to verify cap tables.
Even expense reports represent a data entry problem. Highly-paid employees look at receipts, extract structured data, and input it elsewhere. Not exactly the best use of their talents.
In procurement, when invoices arrive, someone must pull the contract, check if the service is covered, and determine if it should be paid. This happens every day, all day, across businesses worldwide.
Studies show approximately 70% of data entry tasks can be automated through intelligent document processing solutions, allowing workers to focus on exceptions or analytical duties. The financial impact is substantial - implementing intelligent document processing often delivers ROI of 30-200% in the first year, mainly from labor cost savings. Symtrax found businesses achieve an average ROI of 240%, typically recouping their investment within six to nine months.
Why Companies Miss This Opportunity
Many early AI startups focused on automating the most complex, "sexiest" problems. But the real pain points for most businesses are far simpler.
We've experienced this firsthand. We'll demonstrate sophisticated capabilities like processing insurance claims or evaluating deal rooms, and customers respond: "What about this simpler problem? Can Doc Chat help with that?"
The answer is nearly always yes. Doc Chat excels at processing thousands of documents, extracting structured information from materials in wildly different formats.
Previous automation attempts fell short because machine learning approaches couldn't be trained on enough data to consistently find information across extremely different documents. The game-changer? AI's ability to understand context.
The Doc Chat Difference
Doc Chat functions as an enterprise-grade solution with pipelines capable of processing millions of pages. It handles failures, manages scalability, and integrates seamlessly into existing processes.
Building such infrastructure from scratch requires extensive AI expertise and robust infrastructure. Doc Chat delivers this in a plug-and-play solution.
What sets Nomad Data's approach apart is customization. We don't offer a one-size-fits-all product. Instead, we understand each client's exact workflow and tailor the solution accordingly - customizing output formats and integrating other data sources to create a complete solution.
Think of it as training technology to perform a specific task for each client, similar to onboarding a new employee. Nomad doesn’t deliver a set of tools to a client, but rather a final solution, fully tuned to their way of doing business.
Real-World Transformation
One of our clients, a technology company with thousands of partners, demonstrates the power of this approach. Their partner onboarding process previously required employees to manually review numerous documents and visit partner websites to gather structured information.
This took 30-60 minutes per partner profile at a minimum. Today, Doc Chat ingests all partner documents and even browses company websites automatically, compiling structured information in seconds. They can process a thousand profiles simultaneously, creating dramatic time and cost savings.
The ROI metrics we see are consistently shocking. Many companies maintain large teams for these tasks, creating significant budget constraints. When tasks that once took 30-60 minutes per document can be completed in seconds - and thousands can be processed simultaneously - the math changes dramatically.
A quarter's worth of work can be completed in minutes. Tasks that once dominated budgets and schedules simply blend into the background - they just get done, quickly and efficiently.
Beyond Efficiency: The Human Impact
The benefits extend far beyond time and cost savings. Employee satisfaction increases dramatically when people are freed from repetitive tasks. They enjoy better work-life balance, especially during traditionally busy periods, and focus on higher-value activities instead of mundane work.
This shift positively impacts attrition rates. Rote, repetitive work breeds boredom and disengagement. When employees focus on more meaningful contributions, they find greater satisfaction and purpose.
Perhaps most exciting are the new possibilities that emerge. Tasks that might have taken five years of manual effort can now be completed in a day. This mathematical transformation opens doors to new sales approaches, marketing strategies, and research methods previously considered impossible.
Research confirms these benefits. AI and automation tools save professionals an estimated 2 hours and 15 minutes daily by automating tasks like data entry. In complex document processing scenarios, companies have seen processing accuracy improved by 45% while operational costs decreased by 30%, according to McKinsey.
Addressing Common Concerns
Companies often express concerns about data privacy and AI "hallucinations" when considering these solutions. However, when extracting data from documents, large language models rarely hallucinate. They perform remarkably well when asked to identify specific information within defined materials.
Regarding data security, the conversation parallels early concerns about cloud computing. Today, established compliance processes and security frameworks address these issues. Nomad Data maintains SOC 2 Type 2 certification, providing customers with confidence in our security practices.
Another misconception involves client data being used to train models. This is almost never the case - it's an opt-in choice for companies. Foundation model providers like Anthropic or OpenAI don't train on customer data by default. Some early, poorly explained articles created unwarranted concerns in this area.
Getting Started: Finding Your Opportunities
For companies exploring automation opportunities, we recommend focusing on truly needle-moving activities. Look for processes where dozens or hundreds of people perform the same task repeatedly - extracting information from documents, browsing websites, or completing standardized reports.
Prioritize repetitive processes that consume significant time or money. These represent your best automation opportunities.
The Future of Document Intelligence
Looking ahead, we're expanding Doc Chat's capabilities by connecting it to commercial data sources. While most AI systems today rely on web data or initial training sets, valuable commercial data remains inaccessible to them.
At Nomad Data, we're building connections between AI document systems and third-party data, enabling enrichment, verification, and deeper insights. This advancement plays a crucial role in validating data across industries from insurance to private equity.
For professionals in data entry roles, the future demands a shift toward uniquely human skills. As routine tasks become automated, the ability to think creatively and critically becomes increasingly valuable. Humans excel at generating novel ideas and patterns - areas where AI, trained on existing patterns, still struggles.
The most successful professionals will adapt by focusing on creativity and critical thinking - the aspects of work that remain distinctly human.
We believe the greatest AI opportunity isn't in replacing complex human judgment but in eliminating the mundane tasks that prevent people from applying that judgment more broadly. By recognizing data entry as a prime automation target, companies can unlock unprecedented efficiency while enabling their people to contribute in more meaningful ways.
The goldmine isn't just in saving time and money - it's in freeing human potential.
