What Is a Chatbot? Definition, Types, and Examples | Coursera

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Chatbots are computer programs that simulate human conversation. Learn more about the most common chatbot types and use cases.
Often built into social media platforms and websites, a chatbot is software that interacts with a person in spoken or written form, similar to having a back-and-forth conversation with another person.
The primary function of a chatbot that is declarative is to generate automated responses when you ask a question, whereas predictive chatbots provide more personalized responses.
Chatbots work by processing training data and applying artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and developer-defined rules to provide accurate or reliable responses to user queries.
A chatbot is typically used to facilitate customer service and provide personalized recommendations. Read on to discover more about chatbots, how they work, and their practical applications. Afterward, if you’re ready to learn how to write effective prompts, enroll in IBM’s Generative AI Fundamentals Specialization. Beginner-friendly, this program also covers the ethical concerns and considerations for the responsible use of generative AI.
Chatbots are computer programs that simulate human conversation, written or spoken. Modern-day chatbots integrate conversational AI, such as NLP, to understand questions even if they aren’t grammatically correct and then respond based on the data they have collected. You have most likely encountered chatbots in customer service when you need help accessing your bank account, returning a pair of shoes, booking an appointment, or troubleshooting software on your computer.
A chatbot may prompt you to ask a question or describe a problem, to which it will either clarify what you said or provide a response. Rule-based chatbots are simple, responding only to the question asked. In contrast, sophisticated AI-powered chatbots learn about you from collected data and evolve to better assist you over time.
Chatbots, AI chatbots, and virtual agents all mimic human conversation, but they differ in how they work and what they can do. Understanding these differences can help you pick the right tool for your specific use case.
Chatbots process collected data and are often trained on it using AI, machine learning, NLP, and rules defined by the developer. This allows the chatbot to provide accurate and efficient responses to all requests.
The two main types of chatbots are declarative and predictive. Declarative chatbots are more basic than predictive chatbots. Discover more about each type below:
Declarative chatbots perform one function. These chatbots use NLP, defined rules, and ML to generate automated responses when you ask a question. Declarative, or task-oriented, chatbots are most common in customer support and service and are best for answering frequently asked questions, such as store hours or which item you’re returning. This type of chatbot is common, but its capabilities are a little basic compared to predictive chatbots.
Predictive chatbots are more sophisticated and personalized than declarative chatbots. Often considered conversational chatbots, or virtual agents, these AI- and data-driven chatbots are much more interactive and aware. They utilize NLP and more complicated ML, along with natural language understanding (NLU), to continue learning about the user through predictive analytics and intelligence. Over time, they can predict recommendations and anticipate your needs.
Read more: NLU vs. NLP: What’s the Difference?
Modern chatbots such as OpenAI’s ChatGPT and Microsoft’s Copilot can handle a range of complex queries without the need for human intervention. Plus, thanks to generative AI, these advanced chatbots are not only able to have conversations with users but can also boost their productivity in the workplace.
Looking to leverage the benefits of chatbots in your job? Consider trying one of these common chatbot platforms for your business:
• Salesforce Agentforce
• HubSpot Chatbot Builder
Chatbot developers typically build chatbots, but not without a team of machine learning and AI engineers, as well as NLP experts. The following are a few careers involved in building chatbots.
Chatbot developer: These professionals build conversational experiences for users using AI, machine learning, and natural language processing.
AI engineer: AI engineers build models using machine learning algorithms and deep learning neural networks to support decision-making, such as in chatbot development.
NLP engineer: NLP engineers create programs that can understand human languages and respond accordingly, using a combination of computer science and AI.
Learn to create useful chatbots without writing any code in IBM's Building AI-Powered Chatbots Without Programming course. True to its promise of not requiring any code, the course is designed to help you learn how to visually create chatbots with watsonx Assistant and how to deploy them online through a handy WordPress plugin.
From streamlining routine tasks in mobile apps to providing around-the-clock customer support, chatbots are useful in a great variety of ways. Outlined below are some of the most common ways organizations and individuals use chatbots.
You might use a chatbot in a mobile app when you’re paying for an item or subscription. It might offer the option to make direct monthly payments from your bank account instead of paying manually each time. In a doctor’s office, you might fill out intake forms on your phone with the help of a chatbot.
It is common for customers to consult a chatbot when they’re having trouble logging into their account, or when they have an issue with a tool or system software and want to ask questions without calling customer service and speaking to human agents.
AI chatbots like Alexa are continuously learning from data they collect, so you may ask a chatbot whether it is raining outside, and it might offer person