Barbara is a tech writer specializing in AI and emerging technologies. With a background as a systems librarian in software development, she brings a unique perspective to her reporting. Having lived in the USA and Ireland, Barbara now resides in Croatia. She covers the latest in artificial intelligence and tech innovations. Her work draws on years of experience in tech and other fields, blending technical know-how with a passion for how technology shapes our world.
Artificial intelligence chatbots are everywhere. Driven by the rise of ChatGPT, Gemini and Claude, the software mimics human conversation. You've probably chatted with a customer service bot while shopping online or asked a virtual assistant to set a reminder. They're embedded in apps, websites and smart devices, helping you complete tasks faster and more efficiently with 24/7 support for everything from online shopping to booking flights.
Around 35% of people in the USA have used AI chatbots to answer a question instead of a search engine, according to one survey in 2023, and another 35% have turned to it for explanations. A 2024 study showed a rise, with 56% of US teens and 55% of parents using AI-powered search engines, while half of teens and 38% of parents used chatbots. Another study found that 17% of respondents said chatbot-style results helped them find answers faster.
The growing stats back this up: businesses love them and users see why. ChatGPT is more popular than ever and logged 3.9 billion visits in November 2024, doubling its traffic from the year before. AI chatbots, with a 252% growth rate, is the second fastest-growing category in artificial intelligence, just behind AI image generators, according to some stats.
Perhaps we live in times when we got accustomed to outsourcing our intelligence to these machines a tad too much. Still, they are undeniably simplifying our routines and workflows like never before.
"Chatbot" is often used as an umbrella term to describe any software capable of simulating a conversation with humans. Early chatbots functioned like basic FAQ systems, offering pre-written answers to simple, expected questions. They couldn't handle natural language, forcing users to rely on specific keywords or phrases. Anything outside their programming, like complex or unexpected questions, would stump them.
Over time, chatbots evolved with improved algorithms. Conversational AI chatbots started using technologies like natural language processing and machine learning to engage in adaptive, context-aware dialogues.
Today, generative AI chatbots produce human-like responses, making interactions feel natural and intuitive. The biggest leap forward for AI chatbots has been their ability to "understand" context.
For example, if you type "What's the weather like?" in a rule-based chatbot, it might respond with "I don't understand." But an AI chatbot can understand your query, identify your location (if permissions allow) and provide the weather forecast. It can even suggest leaving early for an appointment you have if bad weather could cause traffic delays. This ability to interpret and respond contextually is what sets AI chatbots apart.
While these categories often overlap, their differences lie in complexity and the depth of interaction they provide.
AI chatbots rely on various algorithms, machine learning and lots of data to function. They are powered by large language models like OpenAI's GPT-4, Google's Gemini, Perplexity and Anthropic's Claude and can engage in longer, more complex discussions, provide personalized recommendations and even solve problems on the fly. These models are trained on massive amounts of data from books, articles and online conversations and use this training to generate coherent, contextually relevant responses.
When you type or speak to a chatbot, it is called a prompt. The quality of your prompt will result in the quality of output. The chatbot breaks down your input into smaller parts, analyzes the meaning and generates a response based on patterns learned during training.
LLMs allow chatbots to understand nuanced language, handle follow-up questions and even infer meaning from vague or incomplete prompts.
AI chatbots don't just follow a rigid set of instructions; they "learn" from patterns and user inputs. Instead of answering a single question, they can maintain the flow of a conversation, remember details from earlier conversations and adapt their tone or detail level based on your input.
Modern AI chatbots also use natural language understanding to grasp open-ended queries, overcoming typos, language issues and context.
AI chatbots have found a home in almost every industry. Businesses use them to streamline customer service, with some studies showing gen AI chatbots resolving 75% of customer interactions. They also reduce staff workloads and enhance user experience.
Retail companies rely on chatbots to help customers track orders, find products, answer FAQs and even personalize recommendations based on browsing behavior. Banks integrate them to answer questions about account balances or transaction histories. In healthcare, AI chatbots assist patients with appointment scheduling and symptom checks. In education, they're helping students with tutoring and homework assistance.
Beyond business, AI chatbots are becoming tools for personal productivity. Virtual assistants such as Siri and Alexa now use AI chatbot technology to offer smarter, more nuanced interactions. They can send messages, schedule appointments and even tell you a joke.
As these systems evolve, their potential applications will become even wider.
AI chatbots are undeniably useful. They save time, automate repetitive tasks and make accessing information more convenient. If you've ever resolved a billing issue late at night or gotten quick answers without waiting on hold, you've experienced their efficiency.
Still, they're far from perfect. While chatbots are getting better at understanding context, they still struggle with highly complex or emotionally sensitive situations. A chatbot might misinterpret a sarcastic comment or fail to provide the empathy a human would offer in a customer service scenario.
Privacy is another concern, since chatbots process and sometimes store user data. Though reputable companies have safeguards in place, you should always be cautious about sharing sensitive information due to the risk of data breaches.
Bias and hallucinations are other major issues AI chatbots face. Who can forget about the infamous Google's AI Overviews flop that suggested users put glue in pizza and eat rocks? Or when Google's Gemini depicted Nazis as people of color?
AI chatbots are evolving rapidly, and their capabilities are only expected to grow. Features like multimodal functionality, which lets chatbots process text, images and audio, are already making them more versatile. OpenAI, for example, has introduced voice interactions in ChatGPT, bringing it closer to a fully conversational assistant.
The technology behind them will continue to improve, bringing us closer to a future where talking to AI could feel as natural as chatting with a friend. Hopefully, humans won't go as far as developing romances akin to the one from the movie Her with Scarlett Johannson. (Interestingly enough, OpenAI has already gotten into hot water, and there is a potential legal battle over using a voice almost identical to Johannson's for its AI assistant.)
Here's where things get even more interesting: generative AI companies started leaning into a phenomenon called anthropomorphism (giving human-like traits to non-human things, like computers or animals). These companies are essentially giving chatbots personalities, branding them as "assistants" or "companions." One example is Meta AI partnering with celebrities to lend their voices to their AI assistant. The goal? Make them feel less artificial and more like helpful partners ready to assist you.
By combining speed, adaptability, and a growing understanding of human conversation, they offer a glimpse into the future of user-friendly tech. In the coming years, chatbots will likely become smarter, more personalized and more attuned to individual needs.
