Artificial Intelligence (AI) has been transforming many aspects of business life, especially when it comes to business analytics: that is, interpreting the billions of data points that come at an organization annually. Another crucial use of AI technology is in automating and improving document-centric tasks, such as invoicing processing and contract validation. AI also underpins the emerging area of robotic process automation (RPA), where electronic “bots” automatically perform tasks that were previously done by humans.
When it comes to the document capture space, one of the earliest developers to introduce an AI engine was the Greenwood Village, Colorado–based Digitech Systems. The company’s PaperVision Forms Magic intelligent forms parsing/processing tool debuted in 2016 using home-grown AI technology. The company’s processing engine goes beyond just a combination of an OCR engine and keyword recognition found in some systems, and instead includes a patented AI algorithm purpose-built for document classification. This lets Forms Magic (when used in conjunction with the company’s PaperVision Capture platform) eliminate manual data entry for captured documents by automatically recognizing, classifying, and extracting data without the lengthy setup process required by traditional capture/extraction software. The engine “learns” the types of structured documents an organization receives to intelligently group like documents together based on a range of parameters and commonalities, including the text itself and the position of the text on the page.
The technology can be a true money-saver. Take just one area of a business as an example: invoices. Our research has shown that processing invoices manually costs $10 to $35 apiece, depending on how complex the process is, the prevailing pay rate in a given locale, and other factors. And that’s not considering other costs, such as missing out on early-payment incentives (or incurring late-payment penalties) that likely arrive from missing deadlines due to an inefficient manual process.
With an intelligent, automated Accounts Payable system, invoices can be slipstreamed into the workflow approval process much more quickly, with little to no human intervention. It can also help improve employee satisfaction and retention, since the tedious, repetitive tasks that no one likes are offloaded to the automated solution—freeing up knowledge workers for more fulfilling work that is of higher value to the organization. The technology is similarly useful in areas such as HR and in document-heavy vertical markets such as financial services, healthcare, education, and government—anywhere that relies on structured documents to collect and process data.
The next step after automated extraction, classification, and processing of incoming data is doing something with it. That’s where RPA can give a boost. Digitech Systems’ PaperVision Automation Manager and PaperVision Integration Manager custom “bots” eliminate manual tasks and integrate captured information across the organization. Captured data can be exported and sent to electronic workflows and line-of-business applications, streamlining information onboarding, and (in turn) improving decision-making throughout the organization.
A prime example here is contract management. With an AI-powered capture solution and RPA bots in place, an organization can extract and classify the contracts, then seamlessly share the critical information with one (or multiple) line-of-business systems without rekeying or other human intervention. This means a human only has to get involved at the later (and more crucial) stages of contract review.
The company is now readying its second-generation RPA solution, which will deliver a more streamlined UI for building bots so a customer’s business analysts and IT personnel can create and deploy the helpers they need.
Clearly, AI and RPA will continue to help advance document capture and workflow solutions. They aren’t a replacement for humans in the workplace, but rather a valued colleague willing to take on the mundane but necessary aspects of document-centric jobs.
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