Erik Newton

One of the most sought after applications of AI is the automated customer learning they provide by maximizing chat data. This functionality can provide brands with a myriad of solutions for personalization, customer mapping, and prediction capabilities.   Even with continued innovation - it is important to consider that chatbots are continuously learning.  They may have limited responses or find  nuanced decision-making challenging. These challenges require greater transparency of the AI-learning process learning process for chatbots. How do they access the data that feeds their algorithms? In this panel, we’ll consider whether chatbots are asking the right questions and how they process differing responses.  

Topics may include:

•  Developing a brand-specific chatbot strategy  
• Examining key details of the AI-learning process
• Aligning AI decision-making with greater empathy