Data Action Layer August 30, 2022
Technology trends hold great promise for IT leaders and the organizations they serve. In recent months, artificial intelligence, data science, and machine learning have compelled analysts to examine the trajectories of those trends as well as their associated impact on the business community.
Advances in these areas are driving one of the latest technology trends: natural language technologies (NLT) and intelligent document processing (IDP). In July of this year, Gartner released the Hype Cycle for Natural Language Technologies, 2022 report, underscoring NLT’s importance in the market.
According to the Gartner report, NLT “encompasses technologies and methods that enable human-language-based communication between humans and systems, as well as the analysis of those communications.” In other words, NLT fills the gap between human communication and computer comprehension and includes a range of technologies with differing degrees of adoption, from chatbots to intelligent document processing. It’s already common in our everyday lives to experience computers or devices that can understand and respond to the human voice. Google Translate and Siri or Alexa are good examples.
There are beneficial applications in the business world as well, including enterprise solutions that help simplify complex processes, increase productivity, or enhance customer service (think chatbots). NLT solutions matter to IT leaders when they help overcome specific operational challenges and provide measurable business value.
Gartner’s Priority Matrix addresses the measure of value for innovations like NLT to help IT leaders assess technology investments for their own unique use cases. The chart below illustrates how Gartner maps the benefit of each innovation profile against the amount of time it takes to achieve mainstream adoption. It is clear that many natural language technologies—from intelligent document processing and text summarization to virtual assistants and conversational AI platforms—offer near-term benefits, reflecting “the tremendous impact that new AI methods have on NLT methods.”
The report’s findings further highlight NLT-related solutions that fall along the Hype Cycle chart, along with their drivers, business impact, obstacles, and recommendations.
Just a few among these are:
Intelligent document processing, in particular, deserves extra examination. Gartner’s Priority Matrix assigns a benefit of “high” to IDP, also noting a relatively high market penetration of up to 50%. In Gartner’s own language, this ranking means that a solution “enables new ways of performing horizontal or vertical processes that will result in significantly increased revenue or cost savings for an enterprise.” That’s some powerful potential.
But what, exactly, is IDP? Gartner explains IDP solutions as those that “extract data to support automation of high-volume, repetitive document processing tasks for analysis and insight.” As the report notes, “IDP uses natural language technologies and computer vision to extract data from structured and unstructured content, especially from documents, to support automation and augmentation.”
At Alkymi, we think of IDP as a way to turn operational data headaches into a source of efficiency, and we were glad to be listed as a noted IDP vendor in the report. Our Data Inbox, Patterns, and Patterns Studio products allow businesses to extract, analyze, and take action on critical business data in emails and documents. We’ve seen our own customers experience the “high” benefits Gartner notes through accelerated decision making, improved customer satisfaction, and employees’ realigned focus on high-value, rewarding work.
Gartner’s report highlighted how IDP use cases can be found across many industries and departments. At Alkymi, we’ve seen this bear out in practice. Financial institutions using Alkymi can onboard banking customers 98% faster with workflow automation technology. For fleet operations, extracting and unifying data from PDFs creates full cost transparency. In healthcare, our platform’s use of computer vision and visual mapping in conjunction with natural language processing reduces manual efforts and ensures data accuracy. Investment firms using Alkymi can instantly access, use, and act on ESG data from diverse document formats.
Regardless of industry, using Alkymi to automate document processing turns 20-minute (or longer) data entry sessions and 48-hour SLAs into near instant turnaround times with zero time spent on manual processing. Instantly and automatically capturing targeted data makes any workflow actually flow, while users get more out of thousands of enterprise applications. These benefits make IDP the logical next step for any business.
As we look toward the future of business, competitive advantage comes down to who can make raw, unstructured data actionable the fastest without impacting accuracy and ensuring traceability. Finding the right IDP solution provider is a key component of optimizing your investment in this area.
As you get started, Gartner offers the following among its recommendations:
Reference the full report, Hype Cycle for Natural Language Technologies, 2022, for all the details. To begin or continue on your own IDP journey, start a free trial or schedule an Alkymi demo today.
Fine-tuning is not the only way to get relevant, domain-specific responses out of an LLM. Alkymi’s team of expert data scientists explain an alternate route.
Find out which type of automated document processing solution is right for you: data extraction, an IDP, or a complete business system for unstructured data.
We’re partnering with Portfolio BI, a provider of portfolio analytics and reporting solutions, to bring structured and unstructured data sources together.