There's plenty of upside to the broad artificial intelligence (AI) market for investors. For example, PwC estimates that AI will contribute $15.7 billion to the global GDP by 2030 and create a $126 billion market in the U.S. alone by 2025.

You'd be hardpressed to find any major technology company that's not doing something with AI right now, and Gartner predicts that nearly every new software product will have some form of artificial intelligence in it by 2020. 

Even with all of this AI growth, it can still be difficult to decide which companies are in the best position to benefit. But there are two companies that are leading the way in AI right now, and will likely continue to do so for a while: NVIDIA Corporation (NASDAQ:NVDA) and Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL).

But before we dive too deep into why these two companies are top AI picks, let's first briefly look at what we mean when we say AI, and what other aspects of artificial intelligence investors should know about.

First off, AI usually refers to software working together to complete a certain type of task very quickly, and better than humans can do it. NVIDIA says that when Facebook tags a photo of your friends automatically, it's a form of "narrow AI." When most people refer to AI, they're referring to specific AI functions like this.

White lines on a black background connecting together.

Image source: Getty Images.

The other terms you should be familiar with are "machine learning" and "deep learning." NVIDIA says machine learning is "the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world." In short, machine learning takes an algorithm and learns from the new data it finds in order to perform its task.

And finally, there's deep learning, which is when a computer is able to pull out bits of information about what it's seeing and then make observations based on that. This works in a similar way that our own brains work when we observe the world around us and make assumptions and decisions based on what we see. A deep learning system uses what's called a neural network to separate multiple layers of data for observation, and then puts them all back together to form a conclusion.

For example, when Google used its deep learning computer to find cats in videos, it could do so by analyzing several layers of information -- like cat shapes, colors, and pictures of cats -- before putting all of the data together to decide if what it was looking at is actually a cat.

It's important to know all of this because when we say "AI stocks," we're really talking about all three of these ideas, because many tech companies -- including NVIDIA and Google -- are pursuing all of these technologies.

Why is NVIDIA a top AI stock?

I need to get this out of the way first: NVIDIA doesn't make a significant amount of its revenue from AI right now. Its AI sales are spread across several of its key business segments -- like automotive and data centers -- and the vast majority of its top line is still dependent on sales of the company's graphics processors for gaming.

But NVIDIA has nearly unmatched potential in the AI hardware space. The company is taking its graphics processors that were originally designed for gaming systems and applying them to processing visual data for AI servers, deep learning computers, and machine learning tools. And the results have been phenomenal.

Graphic of a brain with one side being a circuit board.

Image source: Getty Images.

Microsoft, Google, Amazon, and others use the company's graphics processing units (GPUs) to help power some of the most advanced machine learning services for their cloud computing business. Without NVIDIA's GPUs, Facebook wouldn't be able to sift through all of its visual content on its platform, and Microsoft wouldn't be able to offer machine learning services for its growing Azure cloud business.

This is important for NVIDIA because cloud computing is both becoming more complex -- meaning developers need more sophisticated tools that GPUs are great at running -- and the market is expanding quickly. Gartner estimates that cloud computing will grow from $260 billion in 2017 to $440 billion 2020. 

Aside from powering AI in the cloud, NVIDIA is also a leading player in the driverless car technology market. Autonomous vehicles need to process lots of visual information very quickly, and the company is making processors and software that's purpose-built for those tasks.

NVIDIA has created its own computer, called Drive PX Pegasus, that's capable of processing all of the information required for a vehicle to drive all by itself, without any human input. This is the company's third version of its Drive PX system, and it's getting smarter and faster with every iteration. NVIDIA says more than 25 companies are already using its GPUs to build vehicles for ride-hailing and ride-sharing services that can completely drive themselves.

We could explore every aspect of NVIDIA's AI potential, but at some point, we need to move on to Google's AI opportunities. So, let's close out why NVIDIA deserves a top AI stock designation by taking a look at the company's massive potential across these five AI and deep learning markets:

Technology

NVIDIA Total Addressable Market

AI for high performance computing (HPC)

$4 billion by 2020

Deep Learning training

$11 billion by 2020

Deep Learning inference

$15 billion by 2020

Autonomous cars

$8 billion by 2025

AI for cities

$2 billion by 2021

Data source: NVIDIA.

Add all of this up, and NVIDIA is sitting on a $40 billion total addressable market in AI over the next seven years. And with the company's lead in both autonomous vehicle tech and powering AI cloud computing, it's likely NVIDIA will continue leading in the AI hardware space for the next few years.

Why is Google a top AI stock?

Google, of course, has its hands in nearly every type of technology, including AI. Many times when Google's AI potential is discussed, the conversation is about the company's self-driving cars. And while that's a serious opportunity for the company, I think it's better to focus in on two more important avenues: advertising and cloud computing.

I already mentioned how NVIDIA's GPUs are creating a big opportunity for NVIDIA in the cloud computing space, but Google's potential is huge, too.

Google is currently the third-largest public cloud player behind Amazon and Microsoft, but the company has big plans to grow its cloud business into a huge revenue generator. Back in 2015, Google's senior vice president of technical infrastructure, Urs Holzle, said the company's cloud revenue could surpass its advertising sales by 2020.

That was a really bold statement considering that Google's advertising revenue accounted for 89% of its top line at the time, and still made up 88% of Alphabet's sales in 2016.

But Google is looking to expand its own services quickly, and it's using its machine learning tools to helps fuel the growth. The company created its TensorFlow machine learning tool a few years ago and then made it available for free to developers. That may not seem like a big deal, but the company has been able to expand its cloud position by using TensorFlow as a way to draw developers in and get them to sign up for its cloud services.

TensorFlow works on Amazon's and Microsoft's clouds as well, but these two cloud leaders have been so concerned about what Google is doing that they recently teamed up to release their own machine learning tool as an answer to TensorFlow -- and as an attempt to convince developers to stick with their cloud computing services.

Aside from all of its AI potential in cloud computing, Google also uses its machine learning technology to serve up better search results and, most importantly, to automate its advertising.

eMarketer estimates that Google will take more than 80% of U.S. search ad revenue by 2019. Which means even if Google isn't able to build out its cloud services using its AI, the company will still be able to use its machine learning tech to expand its all-important ad revenue.

This could be a slow burn

It's important for investors to remember that all of the AI potential these companies have will likely be spread out over the coming years, not months. That means investors should understand the other aspects of Google and NVIDIA's businesses -- and know that the companies will lean on those other segments as their AI potential grows.

But for patient investors who see the AI opportunities as the massive potential that they are, NVIDIA and Google are two very strong stocks that will likely dominate AI over the next few years.

John Mackey, CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Teresa Kersten is an employee of LinkedIn and is a member of The Motley Fool's board of directors. LinkedIn is owned by Microsoft. Chris Neiger has no position in any of the stocks mentioned. The Motley Fool owns shares of and recommends Alphabet (A and C shares), Amazon, Facebook, and Nvidia. The Motley Fool recommends Gartner. The Motley Fool has a disclosure policy.