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AI chatbot definition, use cases, and how to use

AI chatbots use natural language to understand questions and respond like a person. Learn how they work, where businesses use them, and how to build your own.
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What is an AI chatbot?

An AI chatbot is a software application designed to understand and naturally engage in human conversation using AI capabilities like natural language processing (NLP). These chatbots can be integrated within websites, apps, or messaging platforms to assist with tasks, answer queries, and engage customers around the clock.Unlike traditional chatbots that follow fixed scripts and menu options, an AI chatbot uses artificial intelligence to interpret what you mean, handle follow-up questions, and adjust its replies as the conversation goes on. Many now use generative AI and large language models, so they can write, summarize, and explain instead of only returning pre-written answers.

How AI chatbots work

AI chatbots use natural language processing (NLP) to understand human language, engage in conversations, and run simple, automated tasks. Plus, they use predictive intelligence and analytics to anticipate needs and provide relevant recommendations.

Input

A user enters a message into an AI chatbot via a channel such as an app, website, text message, or even by speaking on a phone call. This message can be a command or a question.

NLP and intent recognition

The AI chatbot receives the message content and captures related info such as the channel that it came in through. The chatbot then uses NLP to determine the purpose of the message and identify relevant intents.

Output

The AI model searches its training data or connected knowledge base to build a reply. The AI chatbot then determines an appropriate response and communicates that to the user via the same channel. As the conversation continues, so does the process—steps one through three repeat until a user's question has been answered, their problem has been solved, or the request is transferred to a live agent.

How to use an AI chatbot

Whether you're asking a chatbot for help or building one for your team, these three steps cover the basics.

Ask a clear question or give a specific task

Type your request the way you'd explain it to a coworker.

Add context

Say who the answer is for, what format you want, and any details the chatbot should work from, such as a tone, a word limit, or a pasted document.

Follow up and refine

A chatbot keeps track of the conversation, so you can ask it to shorten an answer, explain a term, or try a different angle. Always confirm important facts against a trusted source.

Types of AI chatbots

There are two main types of AI chatbots that businesses use: transactional chatbots and conversational chatbots. While they’re both capable of completing tasks, they differ in overall complexity and how they use AI.

Transactional chatbots

A transactional chatbot, also called a task-oriented or declarative chatbot, is a single-purpose chatbot that’s focused on performing or automating one function. This type of AI chatbot is the most commonly used and functions using a set of rules, NLP, and a very small amount of machine learning.

They are trained on structured data and designed to provide a fixed set of options for users to choose from, depending on their intent or the problem they want to solve. After a user makes their choice, the chatbot guides them through the process by providing more options until the question has been answered or the problem has been solved.

Transactional chatbots generate automated responses that are designed to be conversational. Interactions with transactional chatbots are very structured and specific, making them very helpful for businesses that know in advance what common actions or problems customers may need help with. For example, restaurants, delivery companies, and banks use transactional chatbots to handle common inquiries—such as questions about business hours—or to help customers with simple transactions that don’t involve many variables.

Conversational chatbots

A conversational chatbot is a more sophisticated and interactive option that enables personalized interactions. This type of chatbot uses conversational AI to understand the meaning of a user’s messages and respond in a way that’s humanlike.

Conversational chatbots use AI, NLP, knowledge databases, and relevant contextual information to detect nuances in a user’s questions and responses—and then provide relevant answers the way a human would. These AI chatbots are contextually aware and continuously use natural language understanding, natural language processing, and machine learning to become progressively smarter.

Conversational chatbots, which are often called virtual assistants or digital assistants, also use predictive intelligence and analytics for personalization based on each user’s profile and previous behavior. Over time, this type of AI chatbot can learn user preferences to anticipate needs and provide tailored recommendations. Conversational chatbots are used by e-commerce companies, online services, social platforms, businesses with advanced software as a service (SaaS) tools, and business-to-business (B2B) companies that provide enterprise solutions.
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AI chatbot use cases for businesses

AI chatbots are designed to help humans interact with technology and automate tasks. Improvements in AI, machine learning, data science, and natural language processing have enabled the proliferation of chatbots by making it easier to build conversational bots that benefit companies, customers, and employees. Whether used as part of a larger application or as a stand-alone solution, AI chatbots can be used in a variety of channels, such as messaging apps, mobile apps, websites, phone lines, and voice-enabled apps. They can be developed to handle just a few simple commands or to serve as complex digital assistants and interactive agents.

How companies use them

Many companies have AI chatbots act as virtual agents to handle customer service issues or support employees. In general, improved customer service combined with a reduction in customer service costs leads to a high return on investment (ROI) for companies that use chatbots for customer service.

Using AI chatbots also helps companies speed up their sales cycles, generate more leads, and improve customer loyalty. Companies implement chatbots and AI to build personalized user experiences that lead to higher conversion rates and happier, more engaged customers.

As organizations invest in more complicated technologies and build out multiple messaging interfaces, chatbots become a necessary bridge between customers and employees—and the massive amounts of information, systems, and applications they interact with.

How employees use them

AI chatbots can be used to automate simple tasks, empowering employees to save time and focus on high-value work. They can also be used within organizations to help employees navigate company policies, procedures, HR information, and other internal systems and documentation.

How customers use them

AI chatbots can offer assistance or customer service that is available on demand and without restriction. When customers interact with chatbots, they can get answers to their questions at any time. Chatbots also help ease sales experiences and enable customers to build stronger, more personal connections with the brands they interact with.

AI chatbot use cases by team

Customer service

AI chatbots can function as virtual service agents that are always available, leading to more satisfied customers. They can also file and acknowledge help desk requests or perform routine tasks for your customers.

Human resources

AI chatbots can streamline various HR tasks, such as helping employees manage their benefits, notifying employees of policy changes, and helping employees file for sick leave or paid time off.

Finance and accounting

AI chatbots can help employees update and keep track of vendor details, file expense reports, and open purchase order requests.

Marketing

AI chatbots can send targeted offers to loyal customers, track customer satisfaction, and help deliver personalized experiences that drive engagement.

Sales

AI chatbots can pre-qualify leads, provide quotes to potential customers, and start proactive conversations—freeing up time for salespeople to focus on closing deals.

IT

AI chatbots can answer common tech questions, walk employees through password resets, and log support tickets, freeing up IT teams to focus on bigger issues.

AI chatbot use cases

E-commerce and retail
Online stores use AI chatbots to process orders, manage returns, engage customers with personalized recommendations, and provide product information.
Financial services
Banks and credit unions use AI chatbots to provide account balances and statements, answer customer questions, handle basic transactions, and offer financial guidance.
Healthcare
Hospitals and clinics use AI chatbots to schedule appointments, provide medication information, and help patients find nearby office locations.
Education
Schools and universities use AI chatbots to help provide student feedback, assess teachers, and ease administrative duties.
Insurance
Insurance companies use AI chatbots to help file claims, provide status updates, and automate basic tasks.
Manufacturing
Manufacturers use AI chatbots to streamline vendor management and engagement, assist crews, simplify workplace maintenance, help manage product recalls, and ease human resources tasks.
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Frequently asked questions

  • Natural language processing (NLP) is a specific AI capability that chatbots use to make sense of substantial amounts of natural language data. It works by taking a text or voice input from a human, using AI to determine that input's meaning, and then generating and delivering an appropriate response. Natural language processing makes it possible for bots to communicate with human users in a way that emulates human conversation.NLP breaks down user inputs into utterances, intents, and entities. An utterance is any phrase that a user enters into a chatbot. When entered into an AI chatbot, the chatbot analyzes the utterance to determine the user's goal or intent. Finally, the chatbot recognizes entities within the utterance that help define details of the intent. Entities are typically things like dates, times, places, names, or locations that provide further specificity to a user's intent.
  • AI chatbots are used in a variety of ways to empower businesses, employees, and customers.
     
    • Businesses use them to automate time-consuming processes, nurture and convert more leads, and provide always available customer service. 
    • Employees use them to help manage their benefits, understand policy changes, and file for sick leave or paid time off. 
    • Customers use them to quickly find answers and get assistance at any time of the day.
  • Businesses use AI chatbots to enable various benefits, including:
     
    • Improved cost efficiency and operational efficiency.
    • Increased scalability.
    • Greater customer satisfaction.
    • Always available customer service.
    • Reduced human error.
    • Proactive, personalized customer engagement.
     
  • Traditional chatbots function using predefined scripts and rules, making them suitable for straightforward tasks. They follow a set of programmed responses to specific keywords or phrases and typically struggle with complex or unexpected queries.

    AI chatbots use natural language processing (NLP) and machine learning capabilities to understand human language, provide contextually relevant responses, and independently learn from interactions to improve over time.
  • An AI chatbot answers questions in a conversation, such as explaining a return policy or resetting a password, and then waits for your next message. An AI agent works toward a goal. It can plan the steps, use connected tools and data, and finish tasks with little oversight, like checking an order, issuing a refund, and emailing the customer.
  • To create an AI chatbot, businesses use a mix of advanced technologies and strategic planning. First, they define the purpose and scope of their ideal chatbot, ensuring it aligns with their goals and objectives. Then, they select a development platform for a framework to build their bots on. Lastly, businesses use data to train their bots before finally deploying them. A low-code tool like Microsoft Copilot Studio can help you build one without starting from scratch.
  • The best choice depends on what your customers ask most. Look for a chatbot that understands natural language, connects to your help content and customer data, hands off to a live agent when needed, and works on the channels your customers already use. Start with a few common questions, then expand as you see results.
  • Conversational AI is technology you can talk to in everyday language, by typing or speaking. It combines natural language processing, machine learning, and context from earlier messages, so replies feel like a conversation instead of a menu of options. AI chatbots and virtual assistants are common examples.
  • In Microsoft Copilot Studio, you train a chatbot by giving it your content and guidance: add knowledge sources such as your website, documents, or FAQs, set up topics for the questions it should handle, and test it with real examples. After you publish, review the conversations, fix wrong or missing answers, and update the sources as your information changes.
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