Article • 7 min read
Chatbots vs. conversational AI: What’s the difference?
Chatbots and conversational AI are often used synonymously—but they shouldn’t be. Understand the differences before determining which technology is best for your customer service experience.
Von Court Bishop, Contributing Writer
Zuletzt aktualisiert: January 26, 2024
Today’s businesses are looking to provide customers with improved experiences while decreasing service costs—and they’re quickly learning that chatbots and conversational AI can facilitate these goals. By 2024, experts say the global chatbot market will reach $9.4 million.
What customer service leaders may not understand, however, is which of the two technologies could have the most impact on their buyers and their bottom line. Learn the difference between chatbot and conversational AI functionality so you can determine which one will best optimize your internal processes and your customer experience (CX).
What’s the difference between chatbots and conversational AI?
Chatbots are computer programs that simulate human conversations to create better experiences for customers. Some operate based on predefined conversation flows, while others use artificial intelligence and natural language processing (NLP) to decipher user questions and send automated responses in real-time.
Conversational AI is a broader term that refers to AI-driven communication technology such as chatbots and virtual assistants (e.g., Siri or Amazon Alexa). Conversational AI platforms use data, machine learning (ML), and NLP to recognize vocal and text inputs, mimic human interactions, and facilitate conversational flow.
What is a chatbot?
Today’s chatbots typically fall into one of two categories: rule-based chatbots or AI chatbots.
Rule-based chatbots—also known as decision-tree, menu-based, script-based, button-based, or basic chatbots—are the most rudimentary type of chatbots. They communicate through pre-set rules (if the customer says “X,” respond with “Y”). The conversations are sometimes designed like a decision-tree workflow where users can select answers depending on their use case.
These bots are similar to automated phone menus where the customer has to make a series of choices to reach the answers they’re looking for. The technology is ideal for answering FAQs and addressing basic customer issues.
AI customer service chatbots—also referred to as contextual chatbots or virtual agents—use machine learning, natural language processing, or both to understand user intent and form responses. These bots can continuously learn from conversations with customers, so they’re able to deliver more helpful responses as time goes on.
Both types of chatbots provide a layer of friendly self-service between a business and its customers.
Customer service teams handling 20,000 support requests on a monthly basis can save more than 240 hours per month by using chatbots.
What is conversational AI?
Conversational AI refers to technologies that can recognize and respond to speech and text inputs. In customer service, this technology is used to interact with buyers in a human-like way. The interaction can occur through a bot in a messaging channel or through a voice assistant on the phone. From a large set of training data, conversational AI helps deep learning algorithms determine user intent and better understand human language.
Approximately $12 billion in retail revenue will be driven by conversational AI in 2023.
How chatbots relate to conversational AI
Chatbots are a type of conversational AI, but not all chatbots are conversational AI. Rule-based chatbots use keywords and other language identifiers to trigger pre-written responses—these are not built on conversational AI technology.
See chatbots and conversational AI in action
Watch a quick demo to see how Zendesk AI can reduce costs and boost productivity.
Conversational AI chatbots are especially great at replicating human interactions, leading to an improved user experience and higher agent satisfaction. The bots can handle simple inquiries, while live agents can focus on more complex customer issues that require a human touch. This reduces wait times and allows agents to spend less time on repetitive questions.
Chatbot vs. conversational AI: Examples in customer service
Whether you use rule-based chatbots or some type of conversational AI, automated messaging technology goes a long way in helping brands offer quick customer support. Domino’s Pizza, Bank of America, and a number of other major companies are leading the way in using this tech to resolve customer requests efficiently and effectively.
Chatbots in customer service IRL
Both small and large businesses are saving time with chatbots. According to Zendesk’s user data, customer service teams handling 20,000 support requests on a monthly basis can save more than 240 hours per month by using chatbots.
Conversational AI in customer service IRL
Companies aren’t stalling on conversational AI. We predict that 20 percent of customer service will be handled by conversational AI agents in 2022. And Juniper Research forecasts that approximately $12 billion in retail revenue will be driven by conversational AI in 2023.
Conversational AI is the new customer service norm
Conversational AI and other AI solutions aren’t going anywhere in the customer service world. In a recent PwC study, 52 percent of companies said they ramped up their adoption of automation and conversational interfaces because of COVID-19. Additionally, 86 percent of the study’s respondents said that AI has become “mainstream technology” within their organization.
The most successful businesses are ahead of the curve with regard to adopting and implementing AI technology in their contact and call centers. To stay competitive, more and more customer service teams are using AI chatbots such as Zendesk’s Answer Bot to improve CX. Consider how conversational AI technology could help your business—and don’t get stuck behind the curve.
