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Conversational AI automates written or verbal communication in a natural, human way. It also understands conversational human inputs. Today, AI has manifests itself in fairly linear ways: namely machine learning (ML), deep learning, natural language processing (NLP), and predictive analytics. Each operates in silos or small sets to accomplish their specific, pre-defined tasks. But with the recent and exponential increase in computing power, in part due to cloud computing and the invention of fiber optics, the goal of conversational AI is to combine these AI tools into one seamless enterprise experience.

How does Conversational AI fit into the future of enterprise?

With conversational AI, employees also have the ability to search company data for processes and procedures that they haven't committed to memory. They can seek out new regulations that affect a particular industry vertical work as a barrier to productivity. They can avoid time and energy wasted on cross-referencing compliance procedures. With conversational AI, any question an employee has across the workflow can be asked and answered in seconds—no research necessary.


25 AUG
11:00am ET: Opening Remarks
Seth Adler, IQPC Digital
11:00am ET: Conversational AI for employees and customers

  • Assuming that the future of the enterprise user interface (UI) will be powered entirely by conversational AI
  • Benefiting your internal and external customers with machines which can recognize the mood of communications
  • Ensuring any question a customer or an employee has across any workflow can be asked and answered immediately
  • Deploying enterprise-specific conversational AI faster, easier, and more affordably—without the necessity of several data scientists

12:00pm ET: Exploring the evolution to the third wave of conversational AI
  • Remembering the first chatbot
  • 1st Generation: Rules-based
  • Learning from the interactive chatbot
  • 2nd Generation: Rules-based + Supervised ML
  • Taking the next step with conversational AI
  • 3rd Generation: Gen 1 & 2 + Unsupervised ML

26 AUG
11:00am ET: Expediting Conversational AI Training 
  • Realizing that retrieval-based training is time intensive yet low-risk
  • Deliberate, rules-based, pre-programmed answers
  • Understanding that generative training is quicker yet error-prone
  • Unsupervised, self-generated answers leading to syntax error as well as potential enterprise risk
  • Dovetailing retrieval-based and generative training with a human-in-the-loop for the deepest enterprise impact
  • Keeping focus on the horizon for the next step of conversational AI

12:00pm ET: Unpacking sentiment analysis with conversational AI