AI in Documents: Where AI Makes the Most Impact in Business

AI in Documents: Where AI Makes the Most Impact in Business

abbyy logoWe are witnessing unprecedented change in the way companies do business. Companies are finding new and imaginative ways to improve their business and customer interactions by employing transformative digital technologies. It’s how digital startups turned into industry behemoths such as Airbnb, Uber and Venmo.

However, for established companies transitioning from old models of doing business to new ways fueled by innovative technologies is challenging for enterprise organizations. Replacing older legacy systems and processes can be extremely costly and time consuming requiring large IT investments and lengthy transitions. While many enterprise organizations have invested in their existing infrastructure, often this has been done in a piece-meal approach leading to a patchwork of systems and infrastructure that isn’t very effective.

For those companies, change is seemingly inextricable, and the adoption of new technologies is typically painful, costly and difficult. Yet, the hype of artificial intelligence is promising enough to the C-suite that they are funding initiatives that look at how it can make a difference to their organization.

Currently, only 15% of enterprises are using AI, but 31% said it is on the agenda for the next 12 months. One area proving to deliver the most impact to companies is applying AI technologies to content. Sarah Burnett, Executive Vice President and Distinguished Analyst at Everest Group, agrees saying executives are searching for the best approach to get started on the AI automation journey and notes that intelligent process technology (IDP) is the catalyst for launching AI in the most critical area of a company – within its documents.

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The AI Umbrella

Intelligent document processing solutions contain advanced AI technologies such computer vision technology, Machine Learning (ML), and Natural Language Processing (NLP) used to understand all kinds of content including documents, images, text, and communications.

More specifically, applying AI for content is critical because organizations rely on information that is often contained within the documents as part of a business process. They’re used in almost every transaction, and part of customer, partner and employee engagements, contracts, meeting compliance standards and more.

Additionally, documents and content-centric processes are often the first area organizations look to digitize and automate when companies ramp up their digital transformation initiatives. Documents, and the data they hold, are ripe for benefiting from AI to deliver understanding and insight around the information, and make document processing more efficient.

Combining AI with RPA

In the past few years, robotic process automation (RPA) has exploded. UiPath, for example, just received another $568 million investment raising the value of the company to $7 billion. It, along with other RPA vendors, are deploying hundreds of digital workers within enterprises to automate human-like, structured, repetitive tasks within processes. A complementary tool to RPA is AI. Companies are deploying RPA robots to further automate human-like, repetitive task within processes.

Furthermore, RPA can automatically predict and schedule content-centric processes and then apply AI to radically reconfigure those processes to be more responsive and productive. It is this capability that makes AI the perfect companion tool with RPA.

Burnett concurs, “RPA and AI are highly complementary technologies. When optimally combined enterprises can automate more of each process and more processes end-to-end. As an example, AI can read, parse, and classify the content of received documents. It can understand their meaning and sentiment, create actionable content IQ and pass it on to RPA to do the resulting work.”

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Content IQ Delivers Understanding and Finds Meaning from Documents

Using RPA and AI in combination within content delivers Content IQ –  the ability to automatically extract all relevant information from documents and break down processing of content into easy to use and consume technology that can be leveraged directly within an automation solution like RPA.

Content IQ is changing the way we work by powering RPA digital workers, also referred to as the new digital workforce, with the skills and understanding needed to make intelligent business decisions. It helps companies transform their operations, dramatically improve the customer experience, and siagnificantly reduce operating costs. The use of AI technology that can understand and derive meaning from content can provide detailed insights into content which can then be used to better manage individual transactions, as well as, support formulating new business strategies for competitive advantage when implemented across millions of transactions.

Content IQ can be summarized as providing the following skills:

  • Provides understanding of content associated with the process
  • Mimics human thought process through vision, language, and pattern detection
  • Process structured, semi-structured, and unstructured content
  • Supervised learning of documents, and improves over time based on human input
  • Applies learning, but can also have safeguards built in that involve humans
  • Highly skilled digital worker with understanding of content

Many businesses are creating centers of excellence around RPA for leading digital transformation company-wide with the goal of empowering business and IT to work more closely together while giving more ownership to business leaders when it comes to building out the digital workforce with the right “content skills” without relying heavily on IT. However, building AI models and integrating, deploying and managing these enabling technologies has traditionally required technical expertise, but not anymore.

Businesses can gain access to content IQ skills to enable a smarter digital workforce by essentially connecting various pre-built cognitive skills into a digital process and training the digital worker over time to understand and process all types of unstructured pieces of content. These are available by working with technology vendors, RPA vendors and/or access them directly from RPA digital marketplaces, or engaging with value added resellers. Leveraging AI within unstructured document process is now easier than ever.

While not exactly the most glamorous use case when you think of AI, it’s certainly one of the most impactful in terms of productivity gains, cost savings and gaining intelligence to identify new revenue opportunities.

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Picture of Anthony Macciola

Anthony Macciola

Anthony Macciola is Chief Innovation Officer at ABBYY, holds more than 45 patents for technologies in mobility, text analytics, image processing, and process automation. He is spearheading AI initiatives at ABBYY that leverage machine learning, robotic process automation, natural language processing and text analytics including ABBYY Vantage. His goal is to help organizations use AI-enabling technologies to identify meaningful insights, data, and relationships to improve business outcomes.

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