Chatbots vs. conversational AI: Key differences explained

Rachna Shah

October 19, 202311 min read

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Chatbots and conversational AI.

Imagine basic chatbots as helpful aides handling routine tasks, armed with predefined answers. Yet, they do have their limits – stray beyond their knowledge and you might get a vague "I don't understand."

However, conversational AI, a more intricate counterpart, delves deeper into understanding human language nuances, enabling more sophisticated interactions.

Simply put, chatbots follow rules like assistants with a script, while conversational AI engages in genuine conversations, grasping language nuances for a more interactive and natural experience.

For customer service leaders, distinguishing the true impact of these technologies on customers and business outcomes can be challenging. By grasping the functional differences between chatbots and conversational AI, you can make informed decisions to enhance operations and elevate customer experiences.

Before we delve into the differences between chatbots and conversational AI, let's briefly understand their definitions.

Table of Contents

What is a chatbot?

A chatbot is a software application designed to mimic human conversation and assist with customer inquiries. After you've spent some time on a website, you might have noticed a chat or voice messaging prompt appearing on the screen – that's a chatbot in action.

Think of a chatbot as a friendly assistant helping you with simple tasks like setting an appointment, finding your order status or requesting a refund.

For instance, if a user types "schedule appointment," the chatbot identifies the keyword "schedule" and understands that the user wants to set up an appointment. This keyword-based approach enables chatbots to understand user intent and provide appropriate assistance.

Example of a classic chatbot conversation flow

They follow a predetermined conversation path, matching queries with responses in their database using specific keywords.

What is conversational AI?

Conversational AI, in contrast, is the broader term that covers chatbots and virtual agents (like Alexa and Siri) that use natural language processing (NLP) and machine learning algorithms to engage in contextually rich conversations with users.

Sprinklr’s Conversational AI engages user in a conversation through chatbots

Conversational AI uses text and voice inputs, comprehends the meaning of each query and provides responses that are more contextualized. This results in more genuine and dynamic interactions.

Think of conversational AI as a skilled partner capable of having detailed discussions, guiding you through tasks such as offering tailored investment recommendations, proposing ideal travel plans or assisting in troubleshooting intricate technical problems.

Core differences between chatbots and conversational AI

Chatbots and conversational AI have a common goal of automating customer interactions.

However, conversational AI goes a step further by using advanced natural language processing (NLP), machine learning and contextual awareness. While chatbots are suitable for basic tasks and quick replies, conversational AI provides a more interactive, personalized and human-like experience.

Here are some ways in which chatbots and conversational AI differ from each other.



Conversational AI

Interaction style

Predefined responses based on keywords

Contextually rich, personalized conversations

Understanding intent

Limited understanding of user intent

Advanced NLP to grasp user intent and context

Learning abilities

Rule-based, limited learning capabilities

Machine learning for continuous improvement

Channel support

Limited to a single-channel

Supports multiple channels for interaction

Use cases

Basic customer support, FAQs

Advanced customer service, sales and support


Limited language support

Capable of handling multiple languages

Integrated processes/workflows

Does not integrate with processes

Integrates with processes and workflows

Voice and conversational IVR

Does not support such inputs

Supports these inputs

User authentication

Does not support

Enables user authentication

Now that we know the difference between the two, let's try and understand what they have in common.

How are chatbots and conversational AI related?

Although chatbots and conversational AI differ, they are closely related technologies, with chatbots being a subset of conversational AI.

Let's delve into the details of how they are connected.

1. Evolutionary relationship

The relationship between chatbots and conversational AI can be seen as an evolutionary one.

Chatbots have a history dating back to the 1960s, but their early designs focused on simple linear conversations, moving users from one point to another without truly understanding their intentions.

Early chatbots also emphasized friendly interactions, responding to a 'hi' with a 'hello' was considered a significant achievement.

Over time, with the rise of AI, chatbots underwent substantial changes. AI-driven advancements enabled these virtual agents to comprehend natural language and offer tailored responses. Presently, AI-powered virtual agents engage in complex conversations, learning from previous interactions to enhance future interactions.

2. Shared technologies

Both chatbots and conversational AI utilize similar foundational technologies like natural language processing, machine learning and sentiment analysis.

These technologies empower both solutions to comprehend user inputs, identify patterns and generate suitable responses.

However, conversational AI elevates these shared technologies by integrating more advanced algorithms and models that enable a deeper understanding and retention of context throughout conversations.

3. Similar use cases

There are several common scenarios where chatbots and conversational AI are used to enhance customer interactions and streamline business processes.

Here are a couple of examples:

a) Customer support: Chatbots and conversational AI play a crucial role in addressing customer inquiries promptly. Chatbots can provide predefined answers based on specific keywords, while conversational AI goes a step further by analyzing the conversation's context to offer more personalized assistance.

b) Task automation: Both solutions aid agents with tasks such as setting reminders, writing case notes or finding relevant information. By automating routine tasks, they allow support teams to focus on more cognitive tasks that require human touch.

4. Opportunities for integration

Companies have the chance to bring together chatbots and conversational AI to develop well-rounded strategies for engaging with customers.

By combining these two technologies, businesses can find a sweet spot between efficiency and personalized customer engagement, resulting in a smooth experience for customers at various touchpoints.

Chatbots vs. conversational AI: Examples from customer service

Let's look at some popular chatbots and conversational AI examples with varied applications, benefits and outcomes.

Chatbot examples


Poncho (although now defunct) was a well-known chatbot designed to deliver personalized weather updates and forecasts to users. Operating primarily through messaging platforms, Poncho engaged in friendly conversations to provide users with location-specific weather information and alerts.

Users could subscribe to Poncho's services and receive daily weather updates that cater to their preferences and needs.

A chat window with Poncho, an early chatbot system

Unlike advanced AI chatbots, Poncho's responses were often generated based on predefined rules and patterns, making it a reliable source for quick and accessible weather information. Its user-friendly interface and conversational interactions made it a popular choice for individuals seeking easy-to-understand weather forecasts and updates.

Dominos Pizza's Dom

Domino's Pizza has incorporated a chatbot into its website and mobile app to improve the customer ordering experience.

This chatbot, called "Dom", serves as a helpful guide for users, assisting with menu navigation, pizza customization and order placement.

Domino’s Pizza’s chatbot, Dom, engages the user in a conversation

Dom is designed to understand specific keywords and commands, streamlining the ordering process and making it more convenient for customers. Additionally, users can easily inquire about special offers or delivery estimates and even track the progress of their orders through the chatbot's conversational interface.

Also read: 15 best chatbot examples from groundbreaking brands

Conversational AI examples

Google Duplex

Google Duplex is a remarkable demonstration of conversational AI. It's an AI system built to assist users by making phone calls for them and handling tasks such as appointment bookings or reservations.

Image shows Google’s conversational AI called Google Duplex

The impressive part is that it can engage in natural-sounding conversations with human operators, showcasing its contextual understanding and dynamic interaction skills. This technology demonstrates how conversational AI seamlessly integrates into real-life situations, making tasks easier for users and improving productivity overall.

Sprinklr Conversational AI

Sprinklr Conversational AI is a prime example of how advanced conversational AI can completely transform how businesses engage with their customers.

For instance, Sprinklr conversational AI can be implemented to handle customer inquiries. Customers have the option to interact with the AI-powered system through messaging platforms or social media channels.

Sprinklr’s Conversational AI detects intent and context switch in real time

The AI comprehends the intent behind customer queries and provides contextually relevant information or redirects complex issues to human agents for further support.

This level of personalization and dynamic interaction greatly enhances the customer experience, resulting in heightened customer loyalty and advocates for the brand.

Chatbots vs. conversational AI: How to choose the right solution for your business

When choosing the appropriate AI-powered solution, such as a chatbot or conversational AI, businesses need to weigh their options carefully.

To make an informed choice, it's essential to consider the following factors:

1. Nature of interactions

If your business deals with straightforward and repetitive customer queries, a chatbot might be suitable.

Imagine you run an online store. A chatbot can help customers quickly check their order status, track shipments and answer common questions like return policies. It's like having a virtual assistant that handles routine tasks efficiently.

If your business requires more complex and personalized interactions with customers, conversational AI is the way to go.

Let's say you manage a travel agency. When customers inquire about vacation packages, conversational AI can understand the details they're looking for. It can even provide personalized recommendations based on their preferences, dates and past trips, creating a more engaging and tailored experience.

2. Scalability

Consider the volume of customer interactions your business handles. Conversational AI and bots can drive substantial operational savings by reducing service costs and improving productivity.

Chatbots can handle a significant number of interactions, but their scalability might be limited by the predefined rules and responses they rely on.

For example, retail banks employ chatbots to assist customers with account balance inquiries and transaction history. As these queries are common and can surge during peak times, chatbots efficiently handle the influx of interactions, ensuring customers receive prompt and accurate responses.

If you anticipate a high volume of interactions, conversational AI's ability to learn and improve over time through machine learning makes it a more scalable and efficient solution.

For example, e-commerce platforms utilize conversational AI to manage customer interactions during major sales events. With a significant increase in customer queries about products, discounts and shipping, a conversational AI bot's ability to understand context and provide personalized recommendations helps manage the high volume of interactions effectively.

3. Personalization

When it comes to personalizing customer experiences, both chatbots and conversational AI play crucial roles. They enhance engagement by tailoring interactions to individual preferences, needs and behaviors.

Chatbots contribute to personalization by quickly retrieving customer data to provide relevant information. For instance, an airline chatbot can retrieve a traveler's upcoming flights and offer real-time updates on departure gates or delays, making the experience more convenient and personalized.

Conversational AI takes personalization to the next level through advanced machine learning. By analyzing past interactions and understanding the context in real time, conversational AI can offer tailored recommendations.

Watch now: How personalized experiences can drive business growth

4. Budget considerations

Choosing between chatbots and conversational AI based on your budget depends on your business's unique needs and growth goals. While chatbots may offer a cost-efficient entry point, investing in conversational AI can lead to substantial returns through enhanced customer experiences and increased efficiency.

For businesses aiming to optimize their budget, chatbots present an efficient option. A restaurant, for instance, might implement a chatbot to handle reservations, inquiries and menu-related questions. This cost-effective approach streamlines customer interactions, freeing up staff to focus on enhancing the dining experience.

Conversational AI, while potentially involving higher initial costs, holds exciting possibilities for substantial returns.

For example, in a customer service center, conversational AI can be utilized to monitor customer support calls, assess customer interactions and feedback and perform various tasks. Furthermore, this AI technology is capable of managing a larger volume of calls compared to human agents, contributing to increased company revenue.

5. Use case and industry

Consider the specific use case and industry your business operates in.

Chatbots may be more suitable for industries where interactions are more standardized and require quick responses, like customer support, manufacturing and retail.

For instance, in the hospitality industry, hotels use chatbots to handle guest inquiries, room reservations and concierge services. Chatbots efficiently manage routine tasks, ensuring seamless guest interactions and freeing up staff for more personalized services. Other industries benefiting from chatbots include e-commerce and banking.

Conversational AI finds its place in healthcare, where it assists in appointment scheduling, symptom assessment and providing medical information. The advanced capabilities of conversational AI allow for an in-depth understanding of patient needs, contributing to improved patient engagement and healthcare delivery. Other industries benefiting from conversational AI include education, customer service, media and travel and many more.

Humanize your customer interactions with Sprinklr's conversational AI

The old-fashioned ways of interacting with customers just aren't cutting it anymore.

Conversational AI is a game-changer for customer engagement, introducing a sophisticated way of interaction.

As conversational AI becomes more adept at human-like interactions, its potential continues to grow. From healthcare and human resources to the food industry, every sector can harness the capabilities of conversational AI for substantial growth.

Dive into the future by embracing AI-driven solutions like Sprinklr Conversational AI. Witness the transformation that leads to sustained success, ensuring your business is always at the forefront of exceptional customer engagement.

Book a demo call today and let's explore the possibilities together!

Frequently Asked Questions

Yes, chatbots can be programmed to support multiple languages. By integrating language processing capabilities, chatbots can understand and respond to queries in different languages, enabling businesses to engage with a diverse customer base.

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