With all the talk about generative AI, it's easy to miss the AI you already use every day.

Conversational AI is behind the voice assistant on your phone, the smart speaker in your kitchen, and the chat window on the websites you visit most. You're probably using it more often than you think.

Common examples of conversational AI

• Mobile assistants: Siri, Google Assistant, and Bixby on smartphones
• Smart home devices: Amazon Alexa, Google Nest, and Google Home
• AI agents for customer service: chat on Retail, Travel, and banking websites
• Voice AI agents in contact centers: automated phone conversations instead of menu trees
• In-app help: messaging inside ride-hailing, delivery, and on-demand apps

How conversational AI works

Conversational AI combines NLP and machine learning to understand what people say or type. NLP breaks down human language to identify intent and meaning. Machine learning is what lets it handle phrasing it hasn't seen before, and the teams running it can keep improving it by reviewing past conversations. Together, they let AI hold flexible, context-aware conversations instead of following pre-programmed scripts.

Conversational AI vs. rule-based chatbots

• Language understanding: conversational AI uses NLP to interpret intent and context. Rule-based chatbots rely on keyword matching.
• Improvement: teams improve conversational AI by reviewing real conversations. With rule-based chatbots, every new path has to be scripted by hand.
• Response flexibility: conversational AI handles varied phrasing and follow-up questions. Rule-based chatbots are limited to predefined scripts.
• Conversation flow: conversational AI is dynamic and natural. Rule-based chatbots follow rigid decision trees.
• Complex requests: conversational AI can handle nuanced requests. Rule-based chatbots struggle with unexpected inputs.

Here's where you'll find conversational AI in day-to-day life.

Conversational AI on your phone

Whether you're an Apple fan or an Android-for-lifer, your phone likely has a voice assistant that uses conversational AI to understand and respond to what you say.

You can ask it questions, like "Hey Siri, what's the weather today?" Siri might answer, "Today in Radiator Springs it will be clear and sunny with a high of 92 and a low of 64." Or ask, "Hey Google, where's the closest coffee shop?" and your phone will give you directions.

You can also give it instructions. Say "Hey Google, set an alarm for 7:30 a.m." and your phone will understand, act, and confirm: "Okay, setting an alarm for 7:30 a.m."

Mobile assistants use voice recognition to understand questions and commands. You start one by saying "Hey Siri" or "Hey Google," or by holding a button on the side of your phone, which prompts the assistant to ask what it can help with.

An open-ended question like that needs NLP to understand the meaning, or intent, behind your words. A basic rule-based conversation flow relies on specific questions and answers instead.

Conversational AI in your home

Smart home devices like Amazon Alexa, Google Nest, and Google Home are voice assistants that use conversational AI every day. You can use them to play music, podcasts, or the news, check the traffic before you leave for work, plan your day, set reminders, or control your thermostat. You can also ask for facts, sports scores, or a translation.

Some smart home assistants can also shop for you. Alexa, for example, connects to your Amazon account, so "reorder dog food" is enough to place an order.

Because they understand more complex requests, these assistants make everyday tasks easier to manage. Used well, it's almost like having your own personal assistant.

Conversational AI on your TV

If you own an Apple TV, Amazon Fire TV Stick, or Google TV, you can use the same kind of voice assistant to find something to watch without typing one letter at a time. Press the button on the remote and say the name of a series, movie, genre, or channel, and the device shows you what you're looking for. You can also use your voice to control volume, language, and closed captions.

Conversational AI for customer service

When you need help

One of the most common places you'll meet conversational AI is the chat window on a company's website, the one that pops up in the bottom right corner of your screen.

They don't all work the same way. A chat window built on rule-based flows makes you phrase things its way. An AI agent built on conversational AI lets you use regular, everyday language, which saves you effort and frustration.

Retail and Ecommerce

Retailers use conversational AI to give customers personalized, on-brand help on their websites and in their apps, so you can get a fast answer without waiting for a person.

Travel and hospitality

Travel brands use conversational AI so travelers can get answers to common questions, make or change bookings, check flight status, and add extras like seats or bags to a reservation.

Banking and FinTech

Banks use conversational AI on their websites and apps so customers can find answers to common questions, report a fraudulent charge or a lost card, or open a new account. When routine questions are handled through self-service, the bank's team has more time for the issues that need a person.

When you need to reach a person

Conversational AI can act as the first point of contact and collect information to pass along to a human agent. That includes basic details like your name, account number, and the reason you're reaching out, and more detailed information like your insurance policy number and claim details.

That saves you from repeating what you've already said. The agent can jump right in, so you get what you need and get on with your day.

Conversational AI for contact centers

Remember the voice recognition from earlier? Contact centers use it too, and we don't mean the old menu trees you used to press your way through to reach a person.

Modern phone systems use voice AI agents that let you say what you need instead of pressing through a menu.

Because they use NLP and machine learning, voice AI agents can understand what you mean even when you phrase things casually or use slang. The conversation feels more natural as a result.

Conversational AI for in-app help

Many services now run almost entirely through an app, from ride-hailing to food delivery to booking help around the house.

Conversational AI powers automated conversations inside those apps and on popular messaging channels, so you can get help right on your phone screen, in the middle of whatever you were doing.

Summary

Everyday examples of conversational AI include mobile voice assistants like Siri and Google Assistant, smart home devices like Amazon Alexa and Google Nest, AI agents for customer service on Retail, Travel, and banking websites, voice AI agents in contact centers, and in-app help inside ride-hailing and delivery apps. These tools use natural language processing to understand speech and text, so people can say what they need in their own words.

Frequently asked questions

What is conversational AI?

Conversational AI is technology that uses natural language processing and machine learning to help computers understand, process, and respond to human language in natural, human-like conversations.

How does conversational AI work?

It uses NLP to interpret the meaning and intent behind what a person says or types, while machine learning lets it handle phrasing it hasn't seen before. Teams keep improving it by reviewing real conversations.

What industries use conversational AI?

Retail, Travel, banking and FinTech, healthcare, telecommunications, and on-demand services like ride-hailing and food delivery all use conversational AI.

What's the difference between conversational AI and a chatbot?

A chatbot is an interface. Basic chatbots rely on pre-programmed scripts and keyword matching, so they can only handle what they were built to expect. Conversational AI uses NLP and machine learning to understand context and respond flexibly.

What are common examples of conversational AI?

Siri, Google Assistant, Amazon Alexa, AI agents for customer service, voice AI agents in contact centers, and in-app messaging.

Next: Chatbots vs. conversational AI: what's the difference?