Back in 2000, the cost of storing one terabyte of data was about $17,000. Today the cost is $3. This is a function of an exponential environment. When people think about an exponential curve, they always think about how it goes up, which it does. But the inverse of that, the cost of any one capability, goes down. It gets cheaper and cheaper. That’s why the internet of things has come to pass. It’s cheaper and cheaper to accumulate, store and process data.

There are currently about 50 billion devices connected through the internet of things. That’s where the term “big data” comes from. One of the early winners in the big data space was predictive maintenance, where people started to realize that you could put sensors for heat and vibration, for example, on a machine and anticipate when that machine might break. So, there was profitable return on investment.

We saw this technology in the manufacturing sector. We saw the same thing in the mining sector, where today they have sensors on drill bits. But the data is also affecting countless other industries, including retail.

The “Amazon effect” means we have all become used to the level of convenience and quick delivery that we get from a platform like Amazon. Now we naturally expect those same levels of service from other industries. It’s inevitable that we are seeing this affect the financial services industries as well. They call it FinTech, financial technology. This is all being driven by user interfaces, which are more intuitive. Robinhood, Betterment and Wealthfront are great examples, but there are so many others that are taking advantage of the technology and giving new options to consumers in the financial space.

The bottom line is that we are in this exponential environment. One of the areas that we’ve heard the most about in recent years is machine learning, or artificial intelligence, which is used on retail platforms, where you buy one thing and it says, “Hey, you might like these other things.” It learns about your preferences from other things you have done.

Where else is artificial intelligence showing its potential? One is image recognition. We’ve seen applications, for example, in advanced manufacturing, where machines can look for defects.

What is the No. 1 ingredient for machine learning? Data. Tesla has 2 billion miles of data, which gives it an advantage. Uber and Lyft are accumulating a lot of data too.

Now let’s talk about the learning process if you want to understand artificial intelligence and the reason why it’s so powerful. When Tesla introduced its autopilot feature in 2015, there were tens of thousands of Teslas already on the road that had the hardware already. There were people who could literally use the autopilot as they drove home that same night. And one guy did. There’s a very sharp, hairpin corner on the way to his house. As he was driving home that first day, he took his hands off the wheel, and was like, “Let’s see if the car can do it.” The car slammed on the brakes, and there was a warning light that came on that said, “You have to retake control of the vehicle.” So, it was essentially a fail. But the next day he did it again and again and again, and over the course of two weeks, the car learned how to take that corner. Now, it wasn’t just his car that learned how to take that corner. It was every Tesla. All the data from the users on the network gets uploaded to the cloud. The cloud is an enabling technology because then you can upload all of that, fix the problems and then deploy those fixes across the whole network.

That’s the power. That’s why it is accelerating. That’s why the number of people you have on your network is so important. Because the more people you have, the faster it can learn. They call this “fleet learning.” That is where the progress can accelerate.

There are two types of innovation: incremental and disruptive. Incremental innovation is very powerful. It’s changing our world, but it’s not disruptive innovation. Disruptive innovation invalidates existing business models. That’s why it’s so scary for business executives. How do you anticipate disruptive innovation?

People think to themselves, Who’s going to come and eat our lunch? That’s the wrong approach. What they should be thinking is Who’s lunch can we eat? This is a time to stay on offense. If other companies are going to flounder potentially, and even fail ― and some of them will ― there are opportunities for other companies to take their place.

Apple disrupted the music business. It disrupted the phone business. Google did as well with its Android operating systems. So, disruptive innovation comes from what I refer to as “adjacent markets.” If you have different industries that overlap in small places, the disruptive innovation quite often comes from those overlaps. The easiest way to understand what an adjacent market is, is to ask yourself, Who are our biggest suppliers? Who else do they sell to?

Or you can think down the supply chain and ask yourself, Who are my biggest customers? Who else do they buy from? In 20 minutes, you could have a list of a dozen different adjacent markets. Then ask yourself, Which of those adjacent markets is doing poorly? Can I expand to include that business?

Always think on offense. How can you play a larger role in the lives of your customers? LinkedIn disrupted the recruiting business. Amazon disrupted the book business with its Kindle E-reader. These are adjacent markets. Right now, Apple, Google, Tesla are getting into the automobile industry.

Always think, How can I expand? Don’t be afraid to see who’s at the fringe ― what’s selling, what’s working? Disruptive innovation tends to cater to the least profitable market segment first. These are the customers who are a pain in the neck. A lot of businesses avoid these customers altogether.

Every industry caters to the most profitable market segment, which makes sense. That’s where you make money. Who gets left behind? The people at the bottom. So, what happens? What are they looking for? They’re looking for a simpler, less expensive solution. That’s where disruptive innovation comes from. Who’s catering to that market segment?

This is a framework to think strategically about your business: Look up. Look down. Look side to side.

So, look up. Those premium products ― that’s where you make money. You need that profit because disruptive innovation requires a budget for failure. Selling the premium products to your most profitable market segment is a good strategy.

But, at the same time, look down, because that’s where disruptive innovation comes from. It’s those people at the bottom who want a simpler, less expensive solution. That’s the place where some of these innovations can come in and sweep through the entire industry.

Also look side to side. Those are your adjacent markets. Those are your new revenue opportunities. Don’t ask, “Who’s going to eat our lunch?” Ask, “Who’s lunch can we eat?” This is a time of change.

The whole idea of disruptive innovation is that a lot of people get scared by it. They get into a defensive posture and protect what they have currently. But, the bottom line is, you have frameworks that you can use to think more strategically about how to stay on offense, how to build your business, how to grow your revenue. This is a time to think bigger about your opportunity in business and the role you play in your company, even if you are self-employed. This is a time to look out into our changing world and ask yourself, How can I play a bigger role in the lives of my customers?

Patrick Schwerdtfeger is a business futurist specializing in technology trends including big data, artificial intelligence, fintech and blockchain. He’s the author of “Anarchy, Inc.: Profiting in a Decentralized World with Artificial Intelligence and Blockchain” as well as four other books, and has lectured at numerous academic institutions including Purdue and Stanford universities. He is also founder of Trend Mastery Inc., and host of the Strategic Business Insights video blog. Schwerdtfeger has spoken about business trends, technology and digital marketing at hundreds of conferences all around the world.