So, how can we leverage the power of Artificial Intelligence to efficiently handle customer interactions while at the same time mind the needs of the customer? The answer can be found in intelligent assistance. With intelligent assistance the human agent is in control and makes the final call. It’s the collaboration between human and machine that will significantly increase efficiency while at the same maintain the personal touch.
In practice, this means that when there is an incoming question, the smart algorithm is analyzing the text in real-time and can assist the human agent by giving two types of proposed answers: a suggested answer based on the collective memory of all historical questions and the corresponding answers given by human agents in the past. The algorithm predicts which question was most similar in the past and provides the answer that was given by the human agent at that time. Or, the algorithm can provide a ‘standardized’ answer on various clusters of questions by predicting the topic of the question like the traditional chatbot explained earlier. However, in this case the bot only suggests these two answers and doesn’t put them directly into the conversation. The human agent can decide if the answer is suitable to the question or not, and if necessary adjust the answer to the context or provide an entirely new answer.
In this way, the AI does not take over the conversation but is providing the agent with relevant input to enhance the speed and accuracy of the conversation. Because the human does not have to think about or search for the correct answer, but only has to place it in context and add human emotions.
By accepting and or adjusting the proposed answers, the agent is in fact giving feedback to the bot. By capturing this feedback in the collective memory and using it in future predictions, the algorithm will become smarter over-time and will provide more accurate answers in various contexts.