Artificial intelligence (AI) and machine learning can radically improve the way businesses process the massive volume of documents in their organizations. To date, machine learning technologies have brought greater automation to document classification processes, which is helping businesses manage documents more efficiently. Machine learning refers to a field of computer science that allows computers to “learn” without being programmed. The technology can analyze document structure and contents to classify documents according to shared similarities and characteristics. For example, machine learning tools can detect document types by identifying obvious terminology such as “invoice” as well as more subtle language, such as “total due” and “due date.”
As AI technologies, of which machine learning is a segment, improve, document capture software will gain the ability to “read” and understand free-form text by incorporating natural language processing (NLP). NLP enables computers to understand and interpret human language, thus allowing documents to be processed with limited manual intervention
This technology is growing more prevalent in both professional and domestic settings, as evidenced by the growing popularity of smart home assistants. While AI for document management is still a nascent technology, here’s a glimpse at how this emerging technology will automate and secure document management and workflows.
Intelligent document routing
Transcending basic document categorization, AI technologies will be able to scan documents in order to interpret and derive meaning from unstructured text. For example, a document may contain language pertaining to an IP licensing agreement. That document could immediately be routed to a dedicated shared folder for IP attorneys, who would be alerted to it. AI will also bring greater granularity to the routing process. Consider an IP transfer document pertaining to a business agreement in Germany: the document would be routed, with pinpoint precision, to IP attorneys in the company’s German office.
Better customer service
As with the routing example above, AI technologies applied to document management will support faster, more convenient customer service by enabling documents to be processed more efficiently. In the case of processing insurance claims, for instance, AI will be able to derive meaning from the text to identify that the document is a home owner’s insurance claim – not a commercial claim – and even more specifically that it is a claim covering flood damage. Within large, multifaceted insurance companies, AI will route the claim more efficiently by eliminating unnecessary stops along the way and paving the way for a better overall customer service experience.
Today, machine learning can identify specific words in documents, such as “confidential,” and assign a higher level of security for these documents. For example, document capture software can identify high-risk terms and then restrict document access or redact or encrypt the file. This prevents the documents from being emailed to personal email addresses while requiring privileged user authentication before the documents can be printed or opened. AI will go further by intelligently extracting relevant information from massive amounts of data and ensuring only appropriate parties see the content that is pertinent to them. In the case of an IP transfer agreement, the IP attorneys may be able to view details relating to the licensing agreement, while confidential details regarding the licensee’s business strategy and go-to-market plans may not be visible to them.
Only the beginning
According to market research firm AIIM, up to 60 percent of enterprises characterize the management of unstructured data (documents, emails, etc.) as “chaotic.” This challenge will only grow as the volume of documents – and unstructured data within those documents – continues to increase. Machine learning is helping organizations achieve higher levels of efficiency and security in their document management processes, but the industry is just starting to scratch the surface of what is possible. As AI continues to evolve, we can expect organizations to leverage the technology to not just categorize, but to intelligently interpret text in order to streamline and supercharge document management-related tasks.