What is a chatbot? Types, examples, and use cases

A chatbot is an AI text generator that can simulate human conversation and respond to user input in real time.

Artificial intelligence chat tools are becoming increasingly popular as online customer service solutions. From small businesses to major government agencies, organizations at all levels now rely on chatbot technology to at least partially facilitate user support. Instead of relying on human-staffed customer contact centers to answer phones and emails, administrators can set up AI chatbots to resolve complaints or provide help.

Chatbots aren’t just used to automate customer care, of course. Any piece of software that can “talk” to a user and respond to varied inputs in a conversational manner could be considered a chatbot.

To really define a chatbot, it’s important to understand how this technology actually works.

Chatbots work in a variety of ways, depending on how complex their software is. The simplest form of chatbot is really just a basic word-recognition system. These are the bots behind the “live chat” widgets you probably notice in the corner of many websites these days.

These basic bots may try to pass themselves off as intelligent, but they’re really just scanning your messages for keywords. If you want to pay an internet bill and can’t find the right page on your provider’s website, you might explain this to its chatbot. Thanks to its primitive preprograming, the bot notices that you’ve used the words “pay” and “bill” and suggests a page that you can visit to pay your bill. It’s useful, but it’s hardly advanced technology.

At the other end of the spectrum, we have genuine AI chatbots. These systems use machine learning to constantly improve their neural networks, allowing them to become ever more sophisticated in how they process conversational data and make associations between words and concepts. The most notable recent example of this technology is ChatGPT, OpenAI’s latest chatbot.

Chatbots like ChatGPT convincingly simulate conversation, can present well-constructed arguments and ideas, and may produce passages of text that are practically indistinguishable from those written by human beings. Thanks to their natural language processing systems and deep learning algorithms, these chatbots are extremely articulate and responsive to the person they’re talking to. You can find our article on what ChatGPT is for better understanding.

Many programs can be described loosely as chatbots, and these usually fall into three broad categories.

Button chatbots

Button chatbots (also known as menu chatbots) are the simplest form of bots. They present the user with buttons or menus and, depending on the user responses, direct them to a solution for their problem. These button-based bots are popular with booking systems, where the user can, for example, select time slots for a dinner reservation. The bot is then able to communicate their responses to a booking system. These bots work great for repetitive tasks, like taking bookings, carrying out surveys, or processing simple help requests.

Linguistic chatbots

Linguistic or rule-based chatbots are more complex than button bots, though they fall short of the nuanced and relevant responses that AI bots provide. Linguistic models are based on preprogrammed rulesets. For example, a rule could be that when a bot receives a certain number of keywords related to a specific topic, it provides the user with a link to a webpage that may help to resolve their query. Like button or keyword-based bots, they still rely on static, preset rules, but the user experience is more flexible.

Deep learning AI chatbots

The most advanced form of chatbot is the deep learning model. These systems continually improve with interaction – the more people use them, the more data they collect about how to talk like a human, make natural word associations, and avoid past mistakes. The speed at which deep learning systems are advancing is remarkable, with today’s chatbots able to engage in convincing, long-form dialogue, create complex and well-constructed essays, and even write simple code.

Millions of chatbots are active on the internet today, but here are a few notable examples.

• ELIZA. Considered by many to be the first chatbot, a computer program known as ELIZA was developed by MIT in the early 1990s. ELIZA used keywords, as many bots still do today. The bot could recognize words and respond with relevant phrases or open-ended questions. While this system was a far cry from our modern AI chatbots, it was still a key step towards where we are now.
• Jabberwacky. In the mid-2000s, a British programer called Rollo Carpenter developed an early AI-driven chatbot. This bot used machine learning to improve its performance over time, and was one of the first chatbots to become popular online as a source of entertainment for the general public. The Jabberwacky framework was the basis for Clevertbot, an even more popular conversational bot. These systems did a great deal to popularize chatbots in the public conscience.
• ChatGPT. In 2022, OpenAI released ChatGPT, a powerful AI chatbot. The program uses advanced deep learning techniques to simulate realistic human interactions and engage in long conversations. ChatGPT has fuelled widespread awareness of AI’s potential because it can also write coherent essays and code and troubleshoot software. AI systems like these have enormous potential, and can even improve cybersecurity by finding bugs and vulnerabilities in coding. However, industry experts have raised concerns about ChatGPT security due to its privacy gaps and close interaction with humans.

Chatbots have many use cases, from answering customer questions to debugging code. Here are some ways in which they can be employed effectively.

• Customer services. One of the most widespread use cases for website chatbots is in customer care and support. At one time, any questions or complaints had to be handled by customer service teams, but now at least some of these processes can be automated with simple chatbots. While many customers expect better service from humans than robots, chatbots can actually resolve a significant number of simple queries. This may result in a better customer experience for those who do need human assistance, since (in theory) those humans will have more time to focus on their cases.
• Automated messages. Chatbots are increasingly being used to contact people through messaging apps or by SMS. Companies carry out simple surveys using bots, while online businesses can set up Facebook Messenger bots to automatically reply to queries. Bots working through messaging applications can even communicate with other systems, updating databases and booking applications with message data.
• AI assistants. Chatbot technology can also enhance the functionality and versatility of virtual assistants. Not only do chatbots make the user experience better, but they can also operate more effectively on the user’s behalf. Some chatbot assistants can even simulate human voices, making phone calls on your behalf to arrange reservations and appointments.

Chatbots have some obvious advantages and disadvantages which need to be weighed up before we can decide whether this technology is a net benefit or not.

Even without the capacity to engage in meaningful conversations, advanced AI bots could allow businesses to scale content production, build new software applications, and troubleshoot technical difficulties, all while cutting back on expenditure. These bots also improve customer service experiences, allowing for rapid responses and query resolution.

At the same time, chatbots can be used for malicious purposes. A hacker could set up a Facebook chatbot to target people in social engineering attacks, without having to engage with victims directly. A political operative could spread misinformation and fake news with a Twitter chatbot. AI-driven scams are already a problem thanks to deepfake video technology, and chatbots will only heighten these threats.

Regardless of the negatives, however, chatbots are clearly here to stay, so what does the future hold for this technology?

Chatbots are only going to become more dynamic and advanced in the future. As their operational efficiency improves, these programs will be able to carry out complex tasks at speeds simply impossible for humans to attain.

Chatbots will almost certainly become the main system for customer support, with companies relying on human intervention only in very specific cases where a bot is unable to resolve an issue fully. While current chatbots may lack the agility of a human customer care expert, this is just a temporary issue. The technology may soon reach a point at which customers can no longer distinguish between humans and chatbots.

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