Exploring AI's Impact on Call Center Operations: Page 2 of 2
Is Replacing Humans on the Horizon?
There is a great quote by computer science pioneer Alan Perlis: "A year spent in artificial intelligence is enough to make one believe in God." That's not to say that AI is omnipotent. It's great at finding patterns, but it still needs the human in the loop to create the framework. AI doesn't work by simply shoveling all sorts of data into a computer oven that magically bakes relevant insights. The human mind still needs to structure and wrangle the data in order to give it relevance, because AI is still very deterministic and requires a human neural net. Data scientists are needed to train the AI to understand the right context so the programs can complement, instead of replace, human intuition and intelligence.
Today, whenever you have AI between the customer and a human, you're likely to have natural language errors. These types of errors can be cute when they happen with Alexa or Siri, but the customer won't be amused if the AI is making cheeky comments about medical data or financial records. The neural net driving current AI platforms currently can't keep up with all of the routes conversations can take. As a simplistic example, if the customer is on the phone and has to yell an aside to a child, "Timmy, you're in timeout," the AI might deduce the customer's device/program is "timing out," while the human of course will know Timmy is a misbehaving kid. In another scenario, if a customer is calling to complain about a missed delivery of a critical item, the AI machine voice may have difficulty de-escalating rising emotions. Currently a human touch is needed to exhibit the right amount of empathy.
Humans are still very much needed for customer service interactions that are more complex or involve a multi-layered explanation that takes into account many data points across disparate topics. Customers certainly aren't ready to talk to a robot voice when discussing sensitive or emotional topics or other scenarios where health hangs in the balance. A lot of calls cover many different tangents, and we just aren't there yet in terms of an AI that can think around all of the boxes and paths. Errors still happen, although the industry is pushing more testing to get to a state where information is propagated by the AI automatically with few or any errors at all.
A likely future for AI within the context of customer service is a three-way conversation between the customer, a human agent, and an AI-powered assistant. The agent can ask data-related questions of the AI bot during a call, which can then quickly pull up needed information. This approach allows the agent to answer questions immediately and provides a chance to build the customer's comfort with the AI robot. Perhaps next time that customer calls he'll have the option to just speak to the AI assistant directly. However, even in this scenario the human is still in the loop and will need to develop a partnership relationship with the chat assistant. Call center managers and staff should embrace AI as a tool to improve their job performance and decrease mundane tasks. And ultimately, it's a tool that can help delight the customer's expectations, and any agent that can accomplish this goal has a nice amount of job security.