Chatbots vs Conversational AI: Is There Any Difference?

Chatbots also have issues with “learning” because they only derive information from decision trees. If those don’t get updated, like when you add a new product or service, they’ll be of no help. Filing tax returns in India is a cumbersome process, and there were a lot of questions that customers asked the Chartered Accountants (CAs) before filing their returns. Taxbuddy felt that a chat interface was the best way to prevent the CAs from being overburdened.

Don’t use a robotic, limited chatbot solution that plummets your CSAT. While rule-based bots have a less flexible conversational flow, these guard rails are also an advantage. You can better guarantee the experience they will deliver, whereas chatbots that rely on machine learning are a bit less predictable.

This can relieve burden from administrative staff while providing prospective students with instant access to assistance. With this in mind, leading organizations are turning to new forms of technology to meet the needs of their growing customer bases. ChatGPT and Google Bard provide similar services but work in different ways. Get your free guide on eight ways to transform your support strategy with messaging—from WhatsApp to live chat and everything in between.

Conversational AI and its unique features

Taxbuddy looked for a Conversational AI chatbot solution, and found the perfect partner in Kommunicate. With was able to save close to 2000+ hours, and saw an increase of 13x in its productivity. This is a classic case of Conversational AI solving an everyday problem, and you can read the full story here. Conversational AI software can be used to help customers solve common problems and automate repetitive tasks using natural language commands. Examples of Conversational AI Software include Kommunicate.io (Chatbot),  Amelia, LivePerson, Haptik, Ada, ServiceNext among others.

As the name suggests, they use a series of defined rules to answer common customer questions. These rules are the basis for the types of problems the chatbot is familiar with and can deliver solutions for. Here at Kindly, our chatbots are easy-to-use solutions that improve your customer experience and empower your brand with 24/7 global customer support. We’ve seen examples of live chat sessions being reduced by up to 75% and calls to customer support lines down by 50%. A chatbot is an AI-powered technology that uses human-like dialogue in order to answer customer questions and guide them on the easiest path toward conversion.

Benefits of conversational AI over traditional chatbots

One can say that chatbots communicate with the customers based on the specifically designed workflow and are not smart enough to understand and utilise the previous conversations to resolve the current query. Conversational AI enhances the chatbot’s ability to understand human language more accurately and provide tailored user interactions. This conversational AI chatbot (Watson Assistant) acts as a virtual agent, helping customers solve issues immediately.

Also, they only perform and work with the scenarios you train them for. For chatbots to provide a great customer experience, the customer’s questions have to be super simple. Anything with the slightest complexity, such as changing a subscription or asking about an invoice, and the chatbot can’t respond. 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. Chatbots are a type of conversational AI, but not all chatbots are conversational AI.

The global Conversational AI market size is projected to reach $32.62 billion by 2030

Traditional chatbots, smart home assistants, and some types of customer service software are all varieties of conversational AI. KLM Airlines is a good example of how to use a chatbot to simplify travel plans for users and also streamline procedures for businesses. The chatbot named BB will be accessible 24×7,  can support multiple languages, and provide faster responses. Using the chatbot, the airline is able to handle hundreds of travel queries efficiently, offer all the booking information with a click, and make customer support as effortless as it could get. When conversational AI technology is used, interactions can happen through a chatbot in a messaging channel or through a voice assistant over the phone. Unlike chatbots, it can determine user intent and also easily understand human language.

• Thanks to chatbots, customers can now order food without making a phone call.
• It’s important to understand why modern artificial intelligence chatbots (also known as Conversational AI or AI agents) differ greatly from first-generation (rule-based) chatbots.
• Conversational artificial intelligence (AI), on the other hand, is a broader term for any AI technology that helps computers mimic human interactions.
• Snapchat made a name for itself by introducing disappearing messages into the social media scene.
• The biggest thing to remember is that most of these AI chatbots use the same language model as ChatGPT, and the ones that don’t sound pretty similar anyway…at least if you squint.

While some chatbots work based on a predefined conversation flow, others use technologies like artificial intelligence (AI) and natural language processing (NLP) to converse with users. Chatbots are often so advanced that they can easily decipher user questions and offer automated responses in real time. Compared to traditional chatbots, conversational AI chatbots offer much higher levels of engagement and accuracy in understanding human language. The ability of these bots to recognize user intent and understand natural languages makes them far superior when it comes to providing personalized customer support experiences. In addition, AI-enabled bots are easily scalable since they learn from interactions, meaning they can grow and improve with each conversation had.

They can be used to drive personalized, human-like interactions and foster engagement across multiple channels. Organizations looking to increase sales or service productivity may adopt chatbots for time savings and efficiency, as artificial intelligence (AI) chatbots can converse with users and answer recurring questions. Artificial intelligence in chatbots uses natural language understanding(NLU) to process human language and make the chatbots converse naturally. A rule-based chatbot works with the data set that you induce in the bot.

Traditional rule-based chatbots can only perform a limited number of pre-determined tasks and are not powered by Conversational AI. Let’s consider an example where a realtor wants to schedule a site visit. The bot will first send an automated greeting message from the company and then ask if the user wants to make a site visit. Since a bot builder has a calendar integration, a user can immediately pick a date and confirm the appointment.

Professional Services

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. They use artificial intelligence to remember (machine learning), understand (natural language processing), and respond (intelligent analysis) to customer queries.

Rule-based chatbots are not scalable and offer limited responses to the users. Rule-based chatbots give mechanical responses when customers ask questions that differ from the programmed set of rules. It is relatively easy to integrate rule-based chatbots, as they have no role in collecting or analyzing customer data. And conditional statements are easier to add to a site than AI bots that require analytical algorithms and a body of customer data. Conversing with the rule-based chatbots might be frustrating for customers since rule-based bots don’t have Artificial intelligence behind them to understand every question. Rule-based chatbots don’t jump from one question to another, they don’t link new questions to the previous conversation.

Machine learning is a branch of computer science that lets computers acquire knowledge without being specifically programmed. Machine learning algorithms may automatically improve as they are immersed in more data. The rapidly evolving digital world is altering and increasing customer expectations. Many consumers expect organizations to be available 24/7 and believe an organization’s CX is as important as its product or service quality. Furthermore, buyers are more informed about the variety of products and services available and are less likely to remain loyal to a specific brand.

This can be done by training algorithms used in these chatbots with historical data from real user responses and can be optimized with ongoing user feedback (reinforcement learning). Like humans, AI virtual agents are able to decide the next best action based on a variety of things including contextual-factors, customer profiles, sentiment, or business policies. Furthermore, it can alter how it responds based on real-time sentiment analysis.

Once the platform is switched, the complete query needs to be initiated, hampering efficiency. With simple design and workflow, the bots can easily navigate and apply for a specific purpose. Although “Chatbots” and “Conversational AI” are often used interchangeably, they are not the same. Let’s simplify everything for you so you can choose which one will best optimise your internal processes and overall engagement experience.

• Chatbots are often so advanced that they can easily decipher user questions and offer automated responses in real time.
• He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade.
• We would love to have you on board to have a first-hand experience of Kommunicate.
• There are hundreds if not thousands of conversational AI applications out there.
• If you need more complex conversational flows, setting up a rule-based bot can be very time-consuming.

Conversational AI, on the other hand, takes chatbots to the next level. It combines artificial intelligence, natural language processing, and machine learning to create more advanced and interactive conversations. Conversational AI chatbots, however, excel in understanding natural language, context, and user intents. They can provide tailored responses, engage in meaningful conversations, and even offer proactive suggestions. While chatbots operate within predefined rules, Conversational AI, powered by artificial intelligence and machine learning, engages in more natural and fluid conversations. Conversational AI is transforming customer service, enhancing user experiences, and enabling businesses to offer more personalized interactions.

Read more about Chatbot vs Conversational Differences You Should Know here.