Chatbots vs conversational AI: Knowing the difference

14 min read

Last edited:  

Chatbots vs conversational AI: Knowing the difference

Today, chatbots and conversational AI promptly address the historical challenge of prolonged customer support by offering instant assistance. But chatbots and conversational AI are often used synonymously. Are they truly synonymous, or do they have distinct differences?

In this blog post, we will break down and differentiate between chatbots and conversational AI.

Chatbots vs conversational AI

Chatbots are computer programs that can stimulate and automate conversations with users whereas conversational AI is the broader technology that enables computers to understand, process, and respond to users in a more natural way.

While chatbots interact with users specifically on chat, conversational AI systems are more interactive with advanced technologies like natural language processing (NLP), machine learning (ML), and deep learning. These systems can recognize speech and text inputs, expanding their scope to text and voice assistants.

Let’s have a detailed look at the difference between chatbots and conversational AI:

What is a chatbot?

Technically, a chatbot is a computer program designed to chat with customers and users, answer their queries, help with tasks, and guide them around your website or app. These chatbots are available 24/7 to guide customers and users toward a solution to their queries.

Types of chatbots

Based on their functionalities and capabilities, chatbots are categorized into two types:

1️⃣ Traditional Chatbots: These are rule-based chatbots that operate on predefined patterns, rules, and decision trees. They follow specific instructions set by their developers to respond to certain keywords or phrases. Rule-based chatbots have limited flexibility and cannot handle queries outside their programmed scope.

For instance, in customer support, traditional chatbots can be trained to answer only a specific set of questions, mostly FAQs. Since they can’t comprehend context beyond the scope of the set rules, they transfer most of the queries to a human agent. This neither eases the burden on your human agents nor provides customers with the instant resolutions they seek, nullifying the primary objective of deploying a bot.

2️⃣ AI chatbots: Unlike traditional chatbots, AI-powered chatbots use artificial intelligence, particularly natural language processing (NLP) and machine learning to engage in human-like conversations with customers and provide relevant answers to customer queries. According to Forbes Advisor, more than 60% of business owners believe that AI will enhance customer relationships. AI-powered chatbots are capable of handling more complex conversations and tasks compared to rule-based chatbots.

Example of a Chatbot

DevRev’s Autonomous AI Agent for Instant and Reliable Customer Support:

DevRev’s AI agents serve as the first line of defense for your customer support, automating self-service and swiftly resolving queries. While most AI chatbots scrape information from a knowledge base to answer common questions, DevRev’s AI agents go much further with AI-powered semantic search. These AI agents are adept at handling customer interactions, providing step-by-step guidance through troubleshooting processes, and managing interactions across various platforms. Customers or users who land on your website or app looking for answers can:

  • Navigate to the PLuG widget
  • Search for information using AI search agents
  • Get answers instantly

The AI agent pulls information from a variety of sources, including knowledge base articles, past conversation history, and support tickets, to provide the most accurate response.

“Dom” by Domino’s for order fulfillment: Domino’s has created a unique and interactive chatbot named “Dom.” It can be integrated into various messaging platforms, allowing users to place new orders, track current orders, or seek instant customer service. Dom assists customers in placing their orders and handles payment processes seamlessly. This chatbot not only enhances customer convenience but also showcases how chat assistants can streamline and personalize the food ordering experience.

What is conversational AI?

Conversational AI broadens the scope of chatbots, embracing a more sophisticated approach to communication. Conversational AI technology users the power of machine learning, natural language processing (NLP), etc. creating more natural conversations by understanding human language, context, and emotions.

This has prompted businesses to use conversational AI applications in numerous customer-facing use cases such as customer service, sales assistance, etc. These AI-driven computer programs do not just respond but comprehend, learn, and adapt dynamically to customer interactions.

Types of conversational AI

1️⃣ Conversational AI chatbots: While AI-powered chatbots can engage in human-like conversations with customers and interpret the meaning behind their queries, conversational AI chatbots go a step further by understanding human language and sentiments. This means they can recognize and respond to speech and text inputs, understand user intent, and engage in natural and interactive conversations. They also continuously learn from interactions over time. A conversational AI chatbot can deliver natural, engaging user experiences and excel in deriving context from past interactions, allowing for personalized responses.

2️⃣ Virtual assistants: Broadening the scope of sophistication, virtual assistants offer a more comprehensive set of functionalities, being intelligent personal assistants. They integrate multiple capabilities, often combining elements of natural language understanding, task execution, and contextual awareness. Employing a virtual assistant can reduce a company’s expenses by up to 78%. Virtual assistants aim to assist users in a broader range of tasks and contexts, providing a more holistic and personalized experience.

3️⃣ Voice assistants: Voice assistants operate predominantly through voice interactions, leveraging speech recognition and synthesis technologies. They cater to user queries and commands through spoken language. Voice assistants, often embedded in devices like smart speakers or mobile phones, bring about a hands-free, voice-driven experience, enabling you to interact naturally without the need for textual input. Forecasts indicate that by 2024, the count of digital voice assistants will surpass 8.4 billion units, exceeding the global population.

Examples of conversational AI

1️⃣ DevRev’s AI Agents: DevRev is an AI-native platform with artificial intelligence built into its foundation, rather than bolted on. By integrating AI agents alongside human intelligence, DevRev’s AI agents help automate labor-intensive tasks and offer self-service support without compromising customer experience. Here’s how:

➡️ AI agents that ally with your support team: In addition to providing your customers and users with an engaging experience, your human support agents can interact with conversational AI agents using natural language. They can work side-by-side to boost productivity by:

  • Surfacing relevant knowledge-base articles
  • Suggesting the next best course of action for a query
  • Summarizing conversations so support agents don’t have to go through lengthy conversations
  • Quickly rephrasing replies to a formal language that will better suit your brand voice

And more! This enables your human support agents to focus on complex cases that require technical knowledge and creative thinking.

➡️ Sentiment analysis: As soon as a customer conversation is resolved, DevRev’s AI starts evaluating the conversation and categories the customer sentiment into: frustrated, unhappy, neutral, happy, or delighted.

It also provides a concise justification for its analysis, enabling the customer service team to understand if customers are happy with the product or are at-risk.This empowers support agents to tailor their interactions, giving more (or instant) attention to at-risk customers.

➡️ Continuous learning for better deflection: When a customer query is passed to a human agent, DevRev’s AI analyzes the conversation in the background to understand how the human agent solves it. In parallel, it generates a comprehensive knowledge base article for the query to ensure similar queries are deflected successfully in the future. Once created, the article is shared with the customer service team and administrators for approval and publishing.

This process ensures that DevRev’s AI agents continuously self-learn and respond to similar questions that arise in the future, thereby boosting your deflection rate.

2️⃣ Google Assistant: Google Assistant stands as a prime example of a versatile virtual assistant. Integrated into various devices, it offers a wide range of functionalities, from providing weather updates to managing schedules and controlling smart home devices. Its contextual awareness allows for natural language interactions and adaptive responses, providing users with personalized assistance across multiple tasks and contexts.

3️⃣ Amazon’s Alexa: Alexa, Amazon’s voice assistant, operates through voice interactions and serves as the centerpiece of various smart devices. It facilitates tasks such as setting reminders, playing music, and controlling smart home devices. With its natural language processing capabilities and integration into smart home ecosystems, Alexa provides a seamless voice-driven experience, illustrating the power of voice assistants in daily life.

Chatbots vs Conversational AI: Which one should you choose?

Choosing between chatbots and conversational AI depends on your specific needs, goals, and budget.

When to choose a chatbot:

If your primary need is to handle straightforward, repetitive tasks such as FAQs, basic customer inquiries, or simple bookings, a chatbot is suitable. Traditional and basic chatbots are generally cheaper and faster to deploy and maintain, especially if you need them for a specific function or department that does not involve complex interaction requirements. For instance, this could be answering customer queries outside of office hours, sharing ticket status, or helping customers with basic product information.

When to choose conversational AI:

If you need to handle more sophisticated conversations that require understanding context and nuances in human language, such as providing tech support, troubleshooting, or personalized customer recommendations, conversational AI solutions are highly recommended.

Conversational AI also helps businesses in highly competitive industries stand out by providing exceptional customer experiences. It offers more natural, human-like interactions across various channels (web, mobile, social media) and evolves over time to improve responses. This makes it ideal for businesses experiencing rapid growth.

In short:

Traditional or basic chatbots are best for simple, cost-effective, and quick-to-deploy solutions for basic tasks, while conversational AI can handle complex, scalable, and highly interactive situations, offering a superior customer experience.

Benefits of conversational AI

Adaptability and learning: Unlike traditional chatbots, conversational AI can evolve and learn from previous interactions, continuously improving its responses and understanding of customer queries. This enables you to deliver more personalized and contextually relevant answers to your customers.

Contextual understanding: Since conversational AI can comprehend nuances and context in conversations, it can drive more meaningful and relevant conversations, leading to exceptional customer experiences.

Lower customer service cost: As with traditional chatbots, conversational AI can automate repetitive tasks like order status or password resets, reducing the need for human agents. The difference lies in the experience it provides to customers during these interactions. When customers are satisfied with the personalized attention they receive, it lowers the agent workload, decreases response times, and saves overall customer service costs.

Increased customer satisfaction: Using conversational AI improves customer satisfaction by providing seamless, personalized experiences and faster resolutions. AI learns from data to offer better support and smooth handoffs, boosting customer satisfaction rates significantly. This leads to happier customers and better business outcomes.

Increased agent productivity: With conversational AI handling repetitive queries while providing good customer experience, agents get to focus on more complex tasks, enhancing their productivity. Faster service and efficient agents lead to improved support metrics.

Better data collection: Conversational AI tools that are available today enhances data collection by learning from interactions and improving support based on insights. It analyzes customer queries to understand needs better and refine responses. This continuous learning leads to better data utilization and informed business decisions.

Scalability: As a result of streamlined processes, improved self-service rates, and reduced wait times, and better agent productivity, you can scale your support efficiently as you grow. Scalable AI solutions ensure that expanding companies maintain high-quality customer support.

The future of Chatbots vs. Conversational AI

The future of chatbots and conversational AI is undoubtedly promising. These technologies have evolved significantly and continue to progress, unlocking tremendous opportunities and substantial benefits. Let’s explore some of the exciting possibilities that will certainly play a significant role in reshaping how we interact with our customers.

Integration of emotional intelligence: The future holds the promise of AI-driven assistants possessing emotional intelligence, enabling them to understand and respond to human emotions. This advancement will elevate user experiences by providing empathetic interactions.

Advancements in natural language understanding: The future will see further advancements in natural language understanding, enabling AI assistants to comprehend and respond to diverse languages and dialects more accurately.

Ethical and transparent AI: There will be a greater emphasis on ethical AI practices, ensuring transparency, fairness, and accountability in AI-driven interactions. Building trust with users will be pivotal for widespread adoption.

Deciphering the future of customer engagement

Chatbots and conversational AI continually redefine how businesses engage with their audience. As technology evolves, the quest for automating human-like interactions while maintaining personalized customer engagement remains crucial. Artificial Intelligence (AI) and conversational interfaces empower you to bridge this gap, offering personalized, streamlined, and engaging interactions.

To navigate this AI-driven landscape and offer a seamless customer service experience, integrating a chatbot on your website might seem daunting. Embracing solutions like DevRev, equipped with AI at it’s foundation, signifies the integration of innovative technology to foster deeper connections with your audience, naturally enhancing customer satisfaction and driving business growth.

Frequently Asked Questions

Conversational AI provides more natural, context-aware interactions and improves over time with machine learning. It handles complex queries efficiently, offering a superior user experience compared to traditional chatbots.

Challenges may include initial setup costs, ensuring the accuracy and relevancy of AI responses, handling unexpected user queries, and maintaining a balance between automation and human intervention.

The price of conversational AI typically depends on various factors such as complexity of the features, accuracy of the AI, any customizations required, number of accounts needed, etc. While there are AI tools that have free plans, the basic conversational AI tools might start at a few thousand dollars, while more advanced solutions can range from $10,000 to $100,000 depending on your requirements.

DevRev chatbot seamlessly integrates into business processes, offering personalized and efficient interactions to enhance customer engagement without sacrificing the human touch.

Conversational AI chatbot analyzes user data, preferences, and behaviors to tailor responses, recommendations, and interactions, thus contributing significantly to personalized customer experiences.

Akshaya Seshadri
Akshaya SeshadriMember of Marketing Staff

Akshaya Seshadri is a seasoned content marketer who possesses more than five years of expertise in the product industry.