Conversational AI: How Is It Different from Chatbots?
by: Kim del Fierro, VP of Marketing at Aisera.
Until recently, companies and other organizations have used the word “chatbot” to describe any technology that automates customer interactions. But now, businesses are starting to use artificial intelligence (AI) to assist customers with unparalleled efficiency.
Confused by these buzzwords, some businesses might write off conversational AI as another version of a chatbot. But Conversational AI is so much more; AI is literally generations beyond the chatbot, and it’s slowly becoming a new standard for customer experience.
In 2019, Gartner predicted that by 2021, 15 percent of the world’s customer interactions would be handled entirely by AI, a 400 percent increase from 2017!
What is a Chatbot?
A chatbot is a computer program that processes and simulates either written or spoken human conversation, allowing people to interact with digital devices as if communicating with a real person. At the most basic level, chatbots are rudimentary programs that answer simple queries with a single-line response.
What is Conversational AI?
Conversational AI is a technology that lets people communicate with applications, websites and devices in everyday language. It enables an organization to resolve user requests through self-service by means of maintaining conversational dialogues over the omnichannel — web portal, text, phone, email, or chat.
Conversational AI uses Natural Language Processing (NLP) to arrange the text input or the user’s voice into words and sentences, which it analyzes. Both simple chatbots, and next-generation Virtual Assistants use NLP to comprehend, understand and respond to a user’s words in that user’s language, Conversational AI then creates the best response based on the available data. These responses can be in either voice or text form or may even be an action.
The Contrast: Chatbots vs. Conversational AI
1. Natural Language Processing
Though most chatbots also use natural language processing, they rely on algorithms and linguistic rules to infer a question’s meaning and choose an appropriate answer. The chatbot becomes unhelpful when customers ask a question that isn’t scripted to an answer.
Even though Conversational AI employs linguistic rules, it also leverages machine learning (ML) and contextual awareness to generate responses. Conversational AI doesn’t just interpret a user’s request; it personalizes answers and anticipates needs.
2. Contextual Awareness
Chatbots typically don’t know anything about their users beyond what is shared during the interaction. Every time the user engages with the chatbot they must provide information that the business already has to receive a service.
On the other hand, Conversational AI remembers past interactions with every user, whether they occurred online, via SMS or over the phone. It can pull from the user’s personal information, order history, owned products and other data to create immersive, accurate and relevant conversations.
3. Multi-Intent Understanding
Most chatbots have difficulty understanding and responding to two-step requests. If a user asks more than one question, they must repeat the second question to get that answer.
Conversational AI, by contrast, can recognize both requests, addressing one after the other. Since it’s capable of topic and context-switching, users don’t have to repeat themselves or call back to fix leftover issues.
Enterprise-Wide Benefits
AI and self-service automation are rapidly becoming vital in today’s increasingly work-from-anywhere environment. With the IT service desk a mission-critical asset, Conversational AI lets users scale and speed up issue-resolution and carry out key processes with unprecedented cost-efficiency. Conversational AI has been slashing resolution times by up to 90 percent, and reducing training times from hours to minutes. With 65 percent of support requests now capable of auto-resolution, customer satisfaction scores are reaching 80 percent.
