Conversational AI Bots Are So Much More Than Just Chatbots

When company owners and call center agents see the array of call center solutions and the technologies they involve, it can be easy to sort technologies into categories, assuming that they’re the exact same as others, or at least very similar. Because even the best AI conversation bots still count as bots, people often mistakenly conclude that they behave just like rule-based chatbots and that they fulfill the role of chatbots in a call center. 

But this is simply not true. When you dig deeper into the technology behind AI chatbot conversation, it is far more complex – and it has many more capabilities. And you’ll see the benefits of these bots within your own call center when you start using a conversational AI bot to answer your customer service calls. 

What is the History Of Conversational AI Bots?

Smart conversational AI bots combine several technologies, including natural language understanding, machine learning, and artificial intelligence. But these bots weren’t developed in a day. Though AI bots aren’t the same as rule-based chatbots, they developed from them; software developers realized that chatbots had user experience issues and solved those issues through better technology. 

Alan Turing came up with the basic idea of chatbots in 1966, realizing that computer programs could potentially interact with humans. The first chatbot, named Eliza, was then created, and many iterations of this chatbot soon followed. Call centers realized they could be extremely helpful in customer service, and they weren’t wrong. But, as Forbes put it, these traditional chatbots only “offered scripted and robotic user experiences.”

However, with the advent of AI technology, conversational AI bots have evolved into something far beyond the traditional chatbot. 

Are Chatbots the Same as Conversational AI Bots?

No, chatbots and conversational AI bots aren’t the same, and they offer very different digital experiences. The biggest difference is in the level of intelligence each technology has. Forrester says that, for chatbots to delight customers, designers “need to master conversation design.” Conversational AI is the tool that makes that possible. AI for chatbots allows them to self-improve using data from past conversations, speak naturally to customers, and understand natural speech and complex questions.

What Are Examples of Conversational AI Bots in a Call Center?

Suppose a customer calls the customer service number. A conversational AI bot answers the call immediately and determines that the customer wants to know how to edit personal information. The bot walks the customer through that process. If at any point, the conversational AI bot realizes that it can’t solve the customer’s issue, it can escalate the call to an agent. 

Compare that to a chatbot. It may answer the phone immediately, but it will force the customer to communicate beneath its rigid structure. That may mean using specific keywords or pressing numbers to select a question or category. 

While chatbots are occasionally able to resolve customer requests, customers tend to get stuck in the system because chatbots often don’t understand customer requests, resolve them, or know when to escalate calls. And when they do manage to redirect customers in the right direction, agents are typically so overloaded with calls that customers have to wait anywhere from five minutes to two hours to talk to a human. 

Try Replicant’s Solution

There was a time when a chatbot was the best contact center solution you could get. But technology has moved far beyond that, and it’s time to take advantage of it. When you implement Replicant’s AI bots, you’ll see your conversational AI ROI skyrocket.

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