After speaking with companies evaluating document automation tools, here are some of the most common challenges, misconceptions, and lessons about implementing AI-powered document processing.
Introduction
Working in AI sales has allowed me to connect with many companies about one area they’re keen to improve: document processing.
Whether it’s receipts, invoices, bank statements, or checks, a surprising number of teams are still relying on manual processes to capture and input data. What initially seems like a simple task often turns into hours of repetitive work, opportunities for human error, and delays in critical business workflows. Tools like Veryfi are helping companies tackle these challenges.
Through these conversations, I’ve started to notice a few consistent patterns. Many organizations recognize that manual data entry isn’t scalable, but they’re not always sure where automation fits into their workflow.
Here are a few key lessons I’ve learned from talking with companies that are exploring document automation.
1. Manual Data Entry Is Still More Common Than People Think
One of the biggest surprises for me has been how many organizations still rely on manual data entry for critical processes.
In many cases, teams are manually reviewing receipts, invoices, and other unstructured documents and inputting that data into their internal systems. While this approach works at small volumes, it quickly becomes inefficient as business scales.
Manual processes introduce several challenges:
- Time-consuming workflows
- Increased risk of data entry errors
- Limited scalability
- Delays in reporting and decision-making
For many teams, the realization that these inefficiencies exist is the first step toward exploring automation.
2. Many Companies Start Looking for Automation After a Breaking Point
Another pattern I’ve seen is that companies usually don’t start searching for automation tools until they reach a clear operational bottleneck.
This often happens when:
- Document volume increases significantly
- A team is spending too much time on repetitive data entry
- Errors start impacting financial reporting or customer experience
- Leadership begins looking for ways to scale operations more efficiently
At that point, automation becomes less of a “nice-to-have” and more of a necessity.
3. Not All OCR Technology Is the Same
When companies first begin researching solutions, many assume that all OCR (optical character recognition) technology works the same way.
Traditional OCR tools can extract text from images, but they often struggle with more complex tasks such as:
- Interpreting structured data
- Handling different document formats
- Maintaining high accuracy across varying image quality
Solutions like Veryfi go beyond basic OCR by leveraging AI and machine learning to understand document structure and extract relevant data with greater accuracy.
Understanding this difference can make a big impact when evaluating potential solutions.
4. Implementation Concerns Are Often Bigger Than the Technology
Interestingly, one of the biggest concerns companies have isn’t the technology itself, it’s the implementation process.
Teams often ask questions like:
- How difficult will this be to integrate into our current systems?
- How long will the implementation process take?
These are valid concerns. The best automation tools are designed to minimize friction by offering flexible multi-model data extraction APIs, strong documentation, and developer-friendly integration options.
For many organizations, ease of implementation ends up being just as important as the capabilities of the technology.
5. The Goal Isn’t Just Automation, It’s Better Workflows
One important takeaway from these conversations is that companies aren’t just looking to automate tasks. They’re looking to improve how their teams work.
When document processing is automated effectively, it can help organizations:
- Reduce manual workloads
- Improve data accuracy / confidence scores
- Speed up financial and operational processes
- Allow employees to focus on higher-value work
Instead of spending hours entering data, teams can spend more time analyzing information and making strategic decisions.
Conclusion
Document processing may fly under the radar, but it’s essential for how businesses handle information and make informed decisions.
Through conversations with companies exploring automation, it’s clear that many teams are actively searching for ways to streamline these workflows and eliminate manual bottlenecks.
As AI-powered tools continue to improve, automating document processing is becoming more accessible and impactful for organizations of all sizes.
For businesses still relying heavily on manual data entry, now is an ideal time to explore how automation, powered by tools like Veryfi, can transform operations.
– Taylor Abbott
Author Bio:
Taylor works in Sales Development at Veryfi. She meets with prospects to uncover use cases, assess alignment, and explore potential solutions. She writes about practical insights and trends in automation, sharing lessons learned from working with businesses as they transform their workflows.
Have questions? Book a call with Taylor for expert guidance.