<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=2006193252832260&amp;ev=PageView&amp;noscript=1">

4 Min Read

What Is AI? A Simple, Non-Technical Guide

Featured Image

Wondering how to get started with AI? Take our on-demand Piloting AI for Marketers Series.

Learn More

No matter your background or level of understanding, there is a simple, non-technical way to answer the question: “What is AI?”

Artificial intelligence is expected to have an impact worth trillions of dollars on the economy. Some companies are even already using AI to build massive competitive advantages.

Yet too many people still don’t know what AI is—and what it isn’t. There’s a reason for that…

Many explanations of what AI is are too technical, too vague, or too unclear to be useful.

Many explanations of artificial intelligence are too technical, too vague, or too unclear to be useful.

Because of this, many people get frustrated trying to understand AI and ignore it altogether. That’s a shame, because knowing what AI is can help you improve your life and career.

When you demystify AI, it becomes approachable and actionable, which means you can start benefiting from this powerful technology in your life and career.

This post is here to do just that. In it, we provide a simple, non-technical definition of AI and AI-powered technologies that anyone can understand.

What Is AI?

Artificial intelligence describes a range of smart technologies.

What Is AI?

In fact, “artificial intelligence” is an umbrella term. It encompasses a lot of different intelligent technologies across a range of use cases.

So what is AI?

AI is the “science of making machines smart,” according to AI expert Demis Hassabis, founder and CEO of the AI company DeepMind.

What that means is that AI is giving machines the ability to mimic human intelligence. AI is when we teach a machine to do things humans do like see, write, speak, move, and understand.

Different AI technologies do different intelligent things. But they all share this in common:

They can learn. True AI isn’t just automation, though it may include elements of automation. It doesn’t just repeat the same steps over and over again until it is programmed differently.

Instead, AI is trained to achieve an outcome by humans. That outcome could be anything from winning a board game to identifying skin cancer in photos.

Once an AI system learns well enough from a set of data, it can go achieve outcomes on other sets of data—without humans to guide it. It can even improve itself over time without our direct involvement.

Here’s an intentionally simplified example:

You could teach AI to play chess. You’d do this by giving it a million different chess matches to play against simulated opponents. Over time, your AI system would get great at chess.

Then, you could turn it loose on real opponents. When you do, the AI system uses what it learned to beat these opponents and learn from them. It doesn’t need you to tell it what to do or give it guidance.

At the end of the day, what you need to know about AI to start understanding and using it is simple:

AI is any technology that mimics human intelligence and can get smarter on its own over time. And while AI’s capabilities might be impressive, it isn’t science fiction or magic. It’s just very sophisticated math.

Types of AI

There are different types of AI that are also useful to know about.

Types of AI

Machine Learning

Machine learning is a subset of AI. It's a branch of computer science that enables machines to learn on their own. It’s also what gives most AI tools their power.

In machine learning, humans use a lot of data to train an AI system to achieve an outcome.

Once it's trained, the AI system can then use machine learning on new sets of data that it hasn't seen before. Using machine learning, the system can even learn to improve its outcomes over time.

The other types of AI below all use machine learning in different ways to produce different outcomes.

Deep Learning

Deep learning is an advanced form of machine learning.

Deep learning uses neural networks, which mimic the structure of the human brain, to do highly complex things that other types of AI can't do.

One example of deep learning in action:

Self-driving cars rely on super sophisticated deep learning to detect and avoid objects.

Natural Language Processing

Natural language processing (NLP) is AI that understands written or spoken language.

AI systems like Amazon’s Alexa use advanced NLP to understand what you’re saying, then formulate a correct response.

Gmail’s predictive text features also use NLP to understand what you’re writing, then complete your sentences.

Natural Language Generation

Natural language generation (NLG) is AI that generates natural-sounding human language in written or spoken formats.

NLG goes hand-in-hand with NLP. AI systems use NLP to understand what you’re writing or saying. Then, they use NLG to actually write or say the response.

NLG is one area of AI that has progressed very rapidly in the last few years. Today, NLG systems can actually generate paragraphs of human-sounding words on their own.

Computer Vision

Computer vision is AI that sees the world around it. It processes images and objects in order to make conclusions about them.

In some cases, computer vision might be used for facial recognition that identifies people walking through a busy city center.

In others, computer vision might tell the rest of the AI in a self-driving car that there is an object ahead, and it needs to steer to avoid it.

Narrow AI

Narrow AI is a term you sometimes hear that refers to AI that performs a narrow task or a narrow set of tasks.

Today, all AI is narrow AI. All AI is designed by humans to perform specific and narrow tasks, no matter how complex those tasks are.

Strong AI

Strong AI is general AI that is indistinguishable from humans and can do everything humans do. This type of AI is only hypothesized; it doesn’t actually exist.

It’s not impossible that someday we’ll develop strong AI. Such a development would have worldwide implications for humanity. But experts strongly disagree if such AI is even possible to develop.

Examples of AI in Your Everyday Life and Work

AI is all around you—and you probably use it every day.

Examples of AI in Your Everyday Life and Work

To wrap up your understanding of AI, it helps to look at how it’s used in your everyday life and work.

AI in Your iPhone

If you own an iPhone, you use AI dozens of times every day. Many features on your iPhone rely on AI to work. When your phone unlocks by scanning your face, that’s AI. When your camera automatically improves your picture quality, that’s AI. Anytime your phone makes suggestions or recommendations, it’s using AI.

Most of the consumer apps you use, especially social networks, also rely on AI to suggest content and tailor app experiences to your behavior.

AI in Your Shopping Cart

If you shop with Amazon, you’re encountering AI.

Amazon’s AI learns from your shopping habits (and the habits of millions of others) to recommend other products you might like. In fact, most brands that recommend products to you use some form of AI to do so.

Whether you know it or not, you might even receive custom discounts or coupons thanks to AI systems that understand your purchasing behaviors and likelihood to buy.

AI in Your Living Room

There’s a pretty solid chance your leisure time at home is infused with AI.

Anytime you get a content recommendation from Netflix or Disney+, there’s AI at work. If you use Alexa or a Google voice assistant, AI is integral to getting you the answers and responses that make sense.

Related Posts

Defining Machine Learning and Deep Learning to Understand AI

Mark Kilens | May 25, 2020

You can have marketing conversations with leads at scale thanks to AI chatbots. But first, you need to understand the AI tech that makes it all possible.

The Very Best Books on AI in 2022

Mike Kaput | March 23, 2022

What are the best books on AI available today? This post has the answer.

What Is Deep Learning?

Mike Kaput | April 29, 2021

What is deep learning? This post offers a clear, easy-to-understand definition for non-engineers looking to use AI in business and marketing.