Chatbot vs Conversational AI: What’s the difference?

So, chatbot vs conversational AI, it all sounds the same right? If you only look skin-deep, it might seem like the only differences that matter are for tech or grammar nerds. But, this couldn’t be further from the truth!

Equating chatbots with conversational AI is like comparing walkie-talkies with smartphones or buying a coffee from a vending machine vs a professional barista. 

In fact, conversational AI is not just a fancy tech buzzword but the next evolutionary step in making chatbots more useful and valuable to your business. Beyond that, it’s an essential component of building an AI customer service portfolio that will entirely transform your operations for the better.

Piqued your interest? Then let’s get into it!

What is a chatbot?

A chatbot is a software designed to mimic human conversations, typically using pre-defined, rule-based (canned) responses. Like someone following a teleprompter, it bases its responses on a script that it can’t deviate from on-the-fly. Instead, they simply analyze user input for specific phrases or keywords to choose the appropriate response.

If you ask it something it doesn’t have an answer for, you might just get a response like “I’m having trouble assisting with this query.” This is why chatbots often use a multiple-choice style query system to steer interactions in the right direction. 

Of course, one of the most useful things about chatbots is that they provide instead responses and work 24/7. They don’t need coffee breaks and aren’t tied to specific time zones. Plus, it doesn’t matter how many queries are coming in at the same time — it just scales effortlessly.

They are also super easy to set up and deploy. Most offer drag-and-drop rules to configure scripts and user paths and can be added to all website pages with a simple widget.

However, a new breed of chatbots, so-called AI bots or AI chatbots, is emerging to bridge the gap between their old-school counterparts and truly conversational AI tools like ChatGPT using conversational AI technology.

What is conversational AI?

While chatbots mimic AI to an extent, conversational AI is the real deal.

These systems use sophisticated forms of artificial intelligence (AI), or “true AI,” allowing them to engage in nuanced and fluid user interactions. They rely on foundational technologies, like natural language processing (NLP), natural language understanding (NLU), machine learning (ML), and generative AI to deliver conversational capabilities that are surprisingly human.

Some are even advanced enough to use sentiment analysis and data mining to paint a detailed picture of the users they’re interacting with to help serve them better. Unlike traditional chatbots, conversational AI excels in contextual understanding and dialogue flow management, adapting to user input in real time through active learning.

That means that conversational AI can “improvise,” if you will, to intelligently respond to queries it wasn’t pre-programmed for. Even if users ask something new or unusual, they can still expect useful answers, except for the most extreme cases.

Chatbots vs Conversational AI

The pressure of evolving customer experience expectations and growing business requirements is forcing the line between chatbots and conversational AI to become increasingly blurred.

Companies need to find ways to offer hyper-personalized and helpful interactions, at scale, while cutting costs and minimizing the strain on their human resources.

If you’ve been putting 2 and 2 together, you can see how combining chatbots with conversational AI can deliver exactly that, and so, so much more.

While 80% of consumers “love” chatbots, 36% still think that they aren’t accurate enough, according to Uberall. Specifically:

• 43% believe they need to better understand what customers are asking  for
• 19% want chatbots to sound more human and natural

These takeaways have “conversational AI” written all over them.

Don’t just take our word for it — a poll by the MIT Technology Review revealed that 9/10 firms have already added AI to their customer journeys for exactly this reason. The same percentage report that it has significantly sped up their complaint resolutions.

The core differences between chatbots and conversational AI come down to their complexity and adaptability. While chatbots follow predefined scripts to handle basic queries, conversational AI uses advanced technologies like NLP and ML to interpret contextual cues like customer history, intent, and tone.

This allows it to deliver more natural, personalized interactions that evolve over time. Both require some initial setup. You need to manually configure your chatbot’s rules based on your unique goals, customer needs, etc. Conversational AI, on the other hand, will need some initial data training and monitoring to ensure it develops in the right direction.

Neither option is universally a better option for ALL businesses, though. With that in mind, this table provides a quick summary of the most important differences between the two:

Chatbot vs Conversational AI: Use Cases In Customer Service

So, as we just mentioned, conversational AI is not necessarily a one-to-one replacement for traditional chatbots.

The traditional workhorse still has a potential role to play in many organizations, depending on your exact business model and customer service needs.

Below, we’ll break down the most common use cases for both options so you can see if they offer what you need:

Chatbot Use Cases

In general, the main benefits of chatbots remain—being an easy and scalable way to automate routine tasks that generate many tickets but don’t really require a human agent to solve:

• Answering FAQs: Many chatbots already use a multiple-choice system with common queries to keep conversations on track. So, customers can either type the question directly or choose the appropriate FAQ from a pre-determined list. The chatbot can provide a link to the documentation for further reading along with the answer.
• Handling basic transactional requests: Websites like eCommerce stores or booking sites have core customer interactions that are repeated over and over again. While there are typically pages dedicated to actions like order tracking, finding products, or scheduling bookings, many find it more convenient for a chatbot to guide them through the process.
• Providing navigational aid: Similarly, it’s easy to picture a user asking a chatbot where to find a specific piece of information or feature on a website or app. The chatbot can provide a direct link or simple step-by-step instructions on how to get there.
• Collecting initial customer information: Visitors typically find filling in forms tedious and off-putting. Chatbots can quickly gather basic details for signups or support interactions. In the latter case, it can forward this info to a support rep to skip the initial steps and get straight to solving the actual user issue.
• Automating simple workflows: Other basic admin tasks, like password resets, can also be fully automated via chatbots, too. A customer can simply type in something like “I forgot my password,” and the chatbot can guide them through the process without any human intervention.

Conversational AI Use Cases

Conversational AI, on the other hand, goes beyond being a glorified decision-tree, having the potential to practically act as a virtual assistant for both customers and internal support staff:

• Resolving complex inquiries with contextual understanding: Unlike simple chatbot workflows, AI customer service chatbots can handle complex, multi-step support requests, such as troubleshooting technical issues, asking follow-up questions, and tailoring instructions based on what worked/didn’t work in previous steps.

• Delivering personalized recommendations and upselling: By analyzing various customer data points, like past purchases, browsing history, market trends, and recent behaviors, conversational AI can make bespoke product recommendations. It can even offer tailored pricing strategies or offers based on the stage of the customer journey.
• Conducting sentiment analysis: Conversational AI can analyze user sentiment in real-time and adjust its responses accordingly. For example, it can detect certain levels of user intent or frustration, either transferring the ticket to sales or offering more empathetic responses. This can help prevent a loss of sales or customer churn due to critical issues.
• Handling multi-language or multi-channel interactions: AI virtual agents can instantly switch between different languages to offer localized support on the fly. It can also seamlessly transition between different channels or mediums, such as chat or voice.
• Handing over conversations smoothly: When conversational AI finds itself out of its depth, it can elegantly escalate the issue to an agent. Not only can it pick the best agent based on the context and customer priority, but it can provide an easy-to-digest summary to avoid any friction.

Chatbots or Conversational AI Chatbots: which is the best?

We are not saying that chatbots are a thing of the past, but for our money, conversational AI is the way of the future. 

Chatbots can help you score some quick wins by automating your most frequent queries. But you’ll run into limitations all too soon once you try to use it to truly level up your customer service experiences. 

Conventional chatbots simply can’t keep up with delivering the level of personalization today’s customer demands and continuing to support your agents as your business grows.

Investing in conversational AI, however, allows you to completely transform your user journeys from end-to-end. 

Plus, as a neat bonus, the same generative and conversational technologies that enable automated AI-powered interactions can also be used to quickly create other high-quality help resources, like in-depth how-to guides or articles. 

Want to see it in action? 🚀 Book a demo or try it for free with Customerly today!