At Opus Research we’ve been writing about the concept of Intelligent Assistance for nearly a decade. In fact, we’re about to release a comprehensive new report — an update to last year’s Decision Maker’s Guide to Enterprise Intelligent Assistants.

Now the term “Intelligent Automation” is starting to come up more frequently in the C-Suites of organizations and service providers. Recent announcements, such as the acquisition by ServiceNow of DxContinuum, underscore the growing momentum towards automation.

How do the concepts of Intelligent Assistance and Intelligent Automation relate to each other?

Intelligent Automation is an umbrella term encompassing an array of technologies. These technologies, such as machine learning, enable a company to automate tasks once performed by humans. At the low end of the Intelligent Automation spectrum are Robotic Process Automation (RPA) tools. Using RPA tools an organization can script routine tasks, such as data entry or sending IT system alerts, and have these tasks performed by software “robots.”

At the higher end of the Intelligent Automation spectrum are cognitive assistants that employ natural language understanding, machine learning, and analytical capabilities. Higher order automated assistants can be trained to detect patterns in data, for example, and then make predictions based on these patterns. Both Automatic Speech Recognition and Visual Recognition rely on the software’s ability to predict patterns, based on the vast training sets it has consumed.

At Opus Research we use the term “intelligent assistance” to describe a class of technologies and capabilities that enable a company to understand and assist its customers in powerful new ways. The key technologies underpinning intelligent assistance are natural language processing and understanding and speech recognition, mated with information processing and business logic to route conversations to the right resource and provide correct answers.

Intelligent Assistance is at the higher end of the Intelligent Automation spectrum. As organizations continue along the path of digitization and automation, tools from across the spectrum will likely meet and join forces. Intelligent assistants can benefit from integration with RPA tools, for example, to provide a more complete service experience. The growing momentum behind Intelligent Automation is likely to continue to propel Intelligent Assistance forward, both in terms of technologies and use cases.

Categories: Conversational Intelligence, Intelligent Assistants, Intelligent Authentication, Articles

Tags: Intelligent Assistance, Bots, Intelligent Automation