We’ve all seen them. The minute you land on any website these days, a chatbot cheerfully pops up offering assistance or help.
Look behind the curtain, you’ll quickly see that all chatbots are not created equal.
In fairness, chatbots are used for different reasons and all needs are not equal either—in many cases, a technologically simple, or “dumb” chat client will work just fine.
For organizations looking to benefit from robust, AI-driven chatbots capable of strategically reducing the cost of delivering customer support, ThoughtFocus has authored a new white paper that outlines some of the critical AI training that must take place to ensure a smooth AI to human handoff and escalation process. This new white paper guide is for organizations interested in scaling a customer service or support team by offloading routine queries to an AI chatbot in order to manage the costs of scaling the contact or support team.
AI-Human Hybrid Chatbot
There is no question that AI technology is advancing very rapidly; however, in and of itself is still not the answer to excellent customer service. Enabling methodologies like machine learning, deep learning, natural language processing, computer vision and speech recognition, are the focus of major investments and development. However, today’s AI-based customer service chatbots still require human intervention to help provide that context, enabling a better understanding of the bigger picture.
AI-driven chatbots excel from the standpoint of speed, accuracy, ability to scale, and lower costs. In many customer service organizations, AI-driven chatbots can successfully manage a significant percentage of customers’ need for information and service, allowing the much more expensive human customer service agents spend their time dealing with more nuanced or complicated scenarios.
How Human Intelligence and AI Partner to Reduce the Costs of Delivering Continually Improving Customer Service
As the new white paper explains, the key to continually reducing customer service costs is ongoing training of the AI-driven chatbot—ultimately allowing it to get smarter and more capable. Upon its launch, an AI-driven chatbot will have been thoughtfully trained and given access to large data sets helping it to become increasingly intelligence. However, despite the best training and application of NLP, the AI-driven chatbot will have a lot to learn.
Just like an human apprentice, an AI-driven chatbot learns at the side of its more experienced human co-workers.
Go Behind the Scenes of the Human Intelligence-Artificial Intelligence Training Process with ThoughtFocus
Get the new paper from ThoughtFocus.
Chatbots and a supporting ecosystem grew tremendously between 2015 and 2017. While chatbot implementation continues to move forward within many organizations, a greater appreciation of the challenge of chatbot training has manifest. We’ve learned that chatbot training can go considerably wrong (see leading chatbot deployment mistakes) and technological limitations remain.