Chatbots vs. Conversational AI: What's the Difference?

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Chatbots vs. Conversational AI: What's the Difference?
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Have you ever chatted with a support service online and been impressed by how well it understood you? The technology behind the scenes could be either a chatbot or conversational AI. Although both are used to automate conversations in tech services, they work in very different ways.

Chatbots are the first step into automated customer service. They're programmed with a set list of responses to specific questions. You'll get a quick answer if your question matches what they’ve been trained on. However, a chatbot may not be able to answer your question if it is new or complex.

Conversational AI, on the other hand, uses more advanced technology like machine learning (ML) to understand and respond to questions. It gets better over time by learning from each conversation. By 2025, it's expected that nearly 95% of chats with tech services will be powered by this smart tech. 

For IT service managers, choosing the right chat support enables efficiency. In this blog post, we will discuss chatbots vs. conversational AI. 

Chatbot vs Conversational AI: Major Differences

Chatbots handle simple, rule-based queries. Conversational AI uses advanced tech to understand and learn from interactions, making for smarter, more adaptable conversations.

So, while both make your digital experience smoother, the approach is different.

FeatureChatbotConversational AI
TechnologyRule-based; operates on pre-set commands and pathsEmploys advanced AI technologies such as NLP, ML, and sometimes deep learning to understand and generate responses
Error handlingCannot handle inputs that do not match predefined patterns, leading to generic fallback responsesBetter at handling ambiguous or unexpected inputs, often asking clarifying questions or using context to infer meaning
Response generationLimited to pre-scripted responses based on user input matchingGenerates responses in real-time, often uniquely crafted to the user's specific query
Conversational abilityLacks the ability to conduct continuous, multi-turn conversations without losing contextExcellently manages continuous, multi-turn conversations, keeping track of the discussion flow
Integration capabilitiesBasic integration with databases and APIs, primarily for information retrievalAdvanced integration capabilities, including seamless connections with various data sources, APIs, and enterprise systems for real-time data access and actions

8 Use Cases of Conversational AI in ITSM

Accenture predicts that AI technology could boost worker productivity by up to 40% by 2035, underscoring the significant impact of conversational AI. Here are eight transformative use cases of conversational AI in ITSM:

1. Automated ticketing system

Conversational AI systems use advanced NLP techniques to interpret and process user queries submitted via text. By understanding the context and urgency of requests, these systems can automatically generate tickets, classify them into the correct category (like hardware issues, software glitches, or access rights), and route them to the relevant IT team. This process reduces manual sorting and prioritization, speeds up response times, and ensures that IT staff can focus on solving problems rather than just managing tickets.

2. 24/7 customer support

Conversational AI platforms respond immediately to users' questions at any hour, reducing downtime and frustration. These systems are trained on common IT inquiries, enabling them to understand and solve basic issues or provide guidance on the next steps. This capability is crucial for global organizations where users work across different time zones, ensuring that support is always available.

3. Self-service portals

By integrating conversational AI into self-service portals, users can interact with an intuitive interface that understands natural language. Whether resetting a password, requesting access to applications, or troubleshooting common issues, the AI guides users through the process, reducing the need for direct IT support. This allows IT staff to allocate their time to more complex tasks.

4. Knowledge management

Conversational AI enhances knowledge management by dynamically searching and retrieving information from an organization's documentation, FAQs, and resolved tickets. It applies ML to understand the context of user queries, offering the most relevant solutions based on previous interactions and user feedback. This personalized assistance helps users find accurate information quickly, reducing the need for direct IT support and continuously improving the knowledge base's effectiveness.

5. Incident management and resolution

Conversational AI systems can automatically diagnose reported incidents, prioritize them based on impact and urgency, and suggest solutions by referencing a database of similar, previously resolved issues. If an incident requires human intervention, the system can escalate it to the appropriate IT personnel, providing them with a detailed analysis and history of the issue, thereby reducing resolution time and improving the accuracy of solutions.

6. Change requests

Conversational AI streamlines the change request process by automating form filling, initiating approval workflows, and notifying stakeholders of the request status. Understanding the user's natural language inputs can accurately capture the details of the request, ensure it meets policy requirements, and update users on progress without manual intervention. This reduces bottlenecks in the change management process and ensures a smoother implementation of IT changes.

7. Asset management 

Conversational AI tools automate inventory tracking, license management, and allocating hardware and software resources in asset management. By processing user requests in natural language, these systems can update asset records, initiate procurement processes, and ensure compliance with usage policies. This automation reduces errors associated with manual entry, optimizes resource allocation, and provides real-time visibility into asset utilization.

8. User feedback collection and analysis

Conversational AI systems can solicit user feedback about their experience after resolving an IT issue. This feedback is then analyzed using sentiment analysis and ML to identify trends, user satisfaction levels, and areas for improvement. By continuously learning from user interactions, these systems help IT departments adapt their strategies, refine their services, and enhance overall user satisfaction.

6 Use Cases of Chatbots in ITSM

Companies can make use of chatbots in ITSM for different purposes. These include:

1. Switching to a live agent

Imagine the printer isn't working, and the usual quick fixes aren't helping. The chatbot, which understands human language, realizes this problem requires human help. The employee can click a button and start talking to the right expert without explaining everything again because the chatbot shares the chat history with the agent.

2. Keeping track of tools and meeting service standards

With so many apps and tools being used, it's tough for IT teams to keep everything running smoothly all the time. Setting up a system that works alongside your chatbot can help keep an eye on all your digital tools. This way, you can ensure you have the right tools available.

3. Categorization of tickets

Chatbots sort tickets by urgency and type, directing complex issues to the right service desk agents. This streamlined process boosts the service desk's efficiency, enabling support agents to focus on more complex tasks.

4. Finding solutions quicker

Your IT help chatbot gets smarter with every question it asks, building its own bank of answers. If something out of the ordinary pops up, especially when no one is around to help immediately, the chatbot can offer solutions based on what it learned from past problems. This is super helpful for getting things fixed faster, even outside of regular work hours.

5. Keeping cybersecurity threats at bay

Keeping software up to date is essential to avoid cyber attacks. You might miss important updates without a system to monitor your software and hardware, leaving you open to security risks. Chatbots can help by setting up alerts that let you know when to update your tools. This way, you're always protected from potential digital dangers.

6. Real-time alerts

Chatbots inform employees of instant updates on their service requests, system outages, or security notices. This constant flow of information helps streamline the support experience, making employees feel more satisfied by keeping them in the loop and reducing uncertainty. GenAI Sidekick for ITSM

Chatbots are simple programs that help with chatting or customer service through written messages. On the other hand, conversational AI is a more intelligent technology that talks or chats with people in a way that feels more like talking to a human.

After COVID-19 started, a study by PwC showed that 52% of companies began using more of this smart chat technology, which is becoming more popular.

As businesses seek to make customer interactions more personal and efficient, platforms like are in charge of leveraging conversational AI technology. 

With, companies can transform their customer service experience by:

  • Providing AI-driven support that understands and resolves queries in a human-like manner.
  • Analyzing conversational data to offer insights into customer preferences and improve service delivery.

To learn more, you can book your free demo with us!


1. What's the difference between chatbot and conversational AI?

Chatbots answer simple questions like the beginner AI you might see on a website. But conversational AI is more sophisticated, including voice assistants and smarter chatbots that understand and respond to human language, making it feel like a real conversation. Conversational AI aims to mimic human interaction, learning and improving with each conversation for a more natural experience.

2. Why does the chatbot vs conversational AI comparison matter?

A chatbot helps if you aim to automate simple Q&As or streamline customer service processes. However, you need conversational AI if you desire a more engaging, personalized customer experience miming human interaction. Such platforms offer the sophistication and adaptability to understand and respond to customers' needs more intuitively.

3. What about the cost of chatbot vs conversational AI?

Some chatbots are available for free or at a relatively low cost, especially if they're open-source or have simple functionality. Conversational AI solutions, however, might charge per interaction or require a subscription, reflecting their greater complexity and the more personalized experience they offer. The cost differs based on the depth of interaction and learning capabilities you need.

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