Conversational AI is how artificial intelligence will impact the communications industry most. Conversational AI refers to the use of messaging applications, speech-enabled assistants, intelligent virtual agents, and chatbots that automate communications interactions and provide individual customer experiences at scale.
Although AI is being blended into unified communications applications primarily in the form of meeting enhancements -- facial recognition, relationship intelligence, and virtual assistants -- its use in these areas pales in significance when compared with the revolution that is occurring because of AI in the customer experience arena. Conversational AI offers a set of capabilities that organizations will pay large sums for because it significantly impacts the business of the organization, whereas most AI in UC solutions comes for free as a product enhancement.
Fully understanding conversational AI’s impact requires a shift in how we think about “customer experience.” Typically, customer experience is thought of as the customer support an organization gives external customers who use, buy, contribute to, or rely on a particular product or service. However, a broader view of customer experience incorporates serving internal customers who may need HR information, medical plan coverage data, internal help desk support, and a host of other kinds of assistance. Wherever there is a customer, conversational AI likely has a role to play.
Why the Focus on Dialogflow
In this series, we’ve chosen to focus on how to develop conversational AI solutions using Google Dialogflow
. We made this choice because many contact center providers have announced partnerships with Google Contact Center AI
(CCAI) so that their customers can seamlessly use Google’s AI and natural language processing capabilities to add conversational AI (a.k.a., intelligent bots or intelligent virtual agents) to their multichannel contact center interfaces. Dialogflow is at the heart of CCAI. CCAI also offers agent assist and conversation modeling capabilities. Agent assist surfaces relevant contextual information to live agents in real time while conversation topic modeler analyzes audio and chat logs to uncover insights about topics and trends in customer interactions.
Introducing a Multi-Article Series
The interest at Enterprise Connect 2019 in AI and conversational AI was astonishing -- every session associated with these two topics was heavily attended. Given this relevance of conversational AI and the partnerships between Google and the contact center providers, KelCor conceived a series of articles on building bots using Dialogflow, then secured Google’s agreement to provide technical information and accuracy reviews on the content.
The series will comprise 12 articles focused on how to create conversational AI applications with a focus toward implementing them in Dialogflow. When appropriate, content relevant to the contact center partners will appear, particularly when discussing what these partners add, how they differentiate themselves, and the mechanics of interfacing with Dialogflow. Some articles will be completely germane to creating bots using any platform with an eye toward educating No Jitter readers on what to expect as they embark on this journey of intelligent bot creation.
The editorial calendar for the series is shown above; note that we may make minor adjustments to exact dates and topics as the series progresses throughout the year.
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