What is a chatbot?

A chatbot is a program or application that users can converse with through voice or text. Chatbots were first developed in the 1960s, and the technology powering them has changed over time. Chatbots traditionally use predefined rules to converse with users and provide scripted answers. Contemporary chatbots use natural language processing (NLP) to understand users, and they can respond to complex questions with great depth and accuracy. Your organization can use chatbots to scale, personalize, and improve communication in everything from customer service workflows to DevOps management.

What are the benefits of chatbots?

Chatbots can search and retrieve information from any internal or external knowledge base and provide answers through human-like conversation.

Efficiency through automation

Chatbots save time and effort for an organization. They combine the steps of complex processes to automate repetitive tasks through a few simple voice or text requests. You can address common issues automatically and scale operations as needed.


You can build chatbots that respond to either voice or text in users' native languages. You can embed customized chatbots in everyday workflows to engage with your employee workforce or consumer engagements. They can respond to customer queries on social media channels, websites, and messaging applications. Similarly, you can set them up to respond to employee queries on any internal application.

Broader customer engagement

A good customer experience can help your organization stand out. Customer service that relies exclusively on human interaction has limited capacity and lacks flexibility. With chatbots, your organization can personalize interactions with customers at scale. You can reach them in familiar environments, respond to their requests faster, and meet their expectations. You can be proactive and customize your outreach.

What are use cases for chatbots?

Organizations across industries use chatbots to streamline the customer experience, increase operational efficiency, and reduce costs. 

Enterprise productivity

You can integrate chatbots with enterprise backend systems such as customer relationship management (CRM), inventory management programs, or human resources (HR) systems. They can check sales numbers or inventory status, generate marketing reports, or assist with employee orientation.

Read about how Infor uses AI in its enterprise

Personal assistants

Chatbots can simplify and expedite everyday personal activities. For example, customers can order new shoes or groceries, book medical appointments, or make travel reservations from their mobile devices, browsers, or favorite chat platforms.

Read about Kelley Blue Book's chatbot for car owners

Call center applications

In a call center application, chatbots can help solve customer requests and decrease the workload for employees. For example, customers could converse with a chatbot to change passwords, request a balance on an account, or schedule an appointment. Chatbots can maintain context and manage the dialogue. Chatbots can also dynamically change their responses based on the conversation.

Learn about Amazon Lex chatbots in Amazon Connect call centers

What are the types of chatbots?

To replicate human-style conversation, chatbots extract speech elements and provide instant responses. Over time, the technology powering chatbots has evolved.

Rule-based chatbots

Rules-based chatbot technology is the simplest version of chatbot software. It provides users with buttons or menus to seek specific information. Users go through a series of steps and predetermined questions to solve their problems. They cannot type a question but only click on one from a predetermined question set. The chatbot has a built-in dictionary that maps a specific response to every question. It gives the same response to all users who ask a specific question.

Rule-based chatbots aren't good options for scenarios that involve multiple unknown factors. They're also difficult to scale and can take longer than desired to answer the user's requests.

Keyword-based chatbots

Keyword-based or declarative chatbots extract specific keywords from conversations and provide corresponding responses. They use keyword recognition techniques to extract the intent, subject, and sentiment from the questions and respond using scripted replies in predetermined ways.

For example, if you enter "How do I activate my account?," the chatbot detects activate and account as the keywords and responds with a step-by-step guide.

Keyword-based chatbots are still limited in their responses and operate only within the scope of topics that have been preprogrammed.

AI-powered chatbots

Recent artificial intelligence (AI) technologies have expanded what a chatbot can do.

For example, instead of scripted replies, contemporary chatbots can provide dynamic responses to customers. To achieve this, chatbots use natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG).

Generative AI has also made chatbots more capable. A chatbot can be powered by a large language model (LLM), which is pretrained on large volumes of human language data. These models help chatbots simulate natural conversation.

Generative-AI-powered chatbots can also handle complex questions and accurately detect sarcasm, sentiment, and subtle variations in conversations. For example, a customer could ask, “I know it's peak hour, but how soon can I get my food?" The chatbot would then give a natural, precise response. Chatbots powered by generative AI can switch seamlessly between topics and respond sensitively or with humor.

There are many technologies related to chatbots that have distinct meanings.

Virtual agent 

A virtual agent, or virtual assistant, is an intelligent computer program that converses with customers naturally and helps them resolve problems. Virtual assistants can understand emotional nuances, intent, and contextual relevance in conversations. Any AI-powered chatbot can be a virtual assistant if required, but rule-based chatbots can't be.

Conversational AI

Conversational AI is an umbrella term that refers to any AI that communicates with users through text or audio. For example, both Amazon Ask, a chat-based assistant, and Amazon Alexa, a voice assistant, are forms of conversational AI. Many chatbots use conversational AI.


A voicebot, or voice assistant, is a chatbot that listens to voice commands, performs specific actions, or replies to users in natural speech. For example, Alexa is a voice assistant that performs various tasks, such as controlling smart home devices, reporting weather, and playing music.

Voice assistants use automatic speech recognition (ASR) along with other AI technologies used by chatbots. With ASR, voice assistants can analyze complex speech patterns and provide seamless, voice-enabled user experiences.

How does AWS help with building chatbots?

Amazon Web Services (AWS) offers many options to help you build chatbots or other conversational AI.

AWS Trainium is the machine learning (ML) chip that AWS purpose-built for training your own LLM. Each Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instance deploys up to 16 Trainium accelerators. This delivers a high-performance, low-cost solution for LLM training in the cloud.

Amazon Bedrock is a fully managed service that offers a choice of LLMs to customize along with a broad set of capabilities to build generative AI applications. Using Amazon Bedrock, you can easily experiment with and evaluate top LLMs for your use case. You can privately customize them with your data using RAG and build the AI chatbots you need.

Amazon Lex is a fully managed service that builds conversational interfaces using voice and text. Powered by the same conversational engine as Alexa, Amazon Lex provides high-quality speech recognition and language understanding capabilities. With Amazon Lex, you can add sophisticated conversational AI to new and existing applications.

Get started with chatbots and conversational AI on AWS by creating an account today.

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