3 Reasons Why Mark Cuban Is All-In on Artificial Intelligence

Billionaire Mark Cuban (@mcuban) believes the world’s first trillionaire will be an artificial intelligence entrepreneur. 

"I am telling you, the world's first trillionaires are going to come from somebody who masters AI and all its derivatives and applies it in ways we never thought of," Cuban said, reports CNBC.

Cuban has put his money where his mouth is, investing in AI and machine learning startups. He even invested in Twitter because they “finally got their act together on artificial intelligence.” 

While we don’t have a direct line to Cuban, we think we know why he’s so bullish on artificial intelligence based on our research of his comments and what we’ve seen after 5 years of experimenting with AI in marketing.

1. More Can—and Will—Be Automated by AI Than You Think

Cuban predicts that we “are going through the process where software will automate software, automation will automate automation,” reports Futurism. 

We’re already seeing this in marketing, one of the industries currently being disrupted and transformed by AI. 

Marketing automation software was the first phase, making it easier to perform repetitive and administrative marketing tasks. Yet the irony is that marketing automation is still largely manual. 

But as marketing automation software integrates AI technologies, the AI layer will be truly responsible for automating higher-level marketing functions like:

• Drafting social media updates.
• Writing data-driven blog posts.
• Personalizing emails and website copy.
• A/B testing landing pages.
• Building lead nurturing workflows.
• Developing advertising copy.
• Managing paid media spend.
• Conducting keyword research.
• Finding insights in analytics.
• And recommending strategies (to name a few).

In time, AI will free up marketers—and talent in other industries—to perform higher-level creative and strategic tasks. 

And this is just the beginning, which is why we think Cuban’s on the money: 

AI will move up the value chain accordingly as its capabilities increase, augmenting human tasks and giving organizations using AI a huge competitive advantage over those that don’t.

2. Advancements in AI Will Speed Up Future AI Advancements 

Cuban claims we’ll see “more technological advances in the next ten years than we have over the last 30,” reports Futurism.

That’s a bold claim, but likely true thanks to machine learning’s ability to learn in an unsupervised fashion.

In the beginning, humans coded algorithms to automate cognitive tasks. Today, those algorithms, to some degree, teach themselves. 

As the algorithms learn better and faster, they’ll in turn be able to learn better and faster, accelerating AI advancements. 

However, keep in mind, AI is a suite of related technologies at varying degrees of maturity.

Some areas will accelerate faster than others. Other areas may not mature indefinitely.

But in total, AI’s ability to teach itself is already massively accelerating certain technological developments, such as self-driving cars and medical image recognition.

3. AI Doesn’t Have to Be 100% Right to Be 100% Transformative

Artificial intelligence, machine learning, deep learning and related technologies use massive amounts of data to surface insights and make predictions.

AI may never be completely certain that an insight or prediction is correct. But it doesn’t have to be to make a huge difference in businesses. 

"With deep learning in particular, you process all that data and you look for not the 100 percent conclusion, but you look for the 51 percent, the 60 percent opportunities that could send you in a new direction. And I think that's why it's so big," Cuban told CNBC. 

Basically, AI doesn’t have to work all of the time. And that very fact means that as long as it works well enough in enough capacities, it will be widely adopted. 

Marketing is a great example of this concept.

AI marketing systems can’t predict with 100% accuracy which campaigns will work or completely automate content creation or fully plan marketing strategy. 

But they can do a good enough job that it makes economic sense to consider using these systems. And as they’re more widely used, they get better at what they do and make even more economic sense to continue using.

It’s a virtuous cycle—and one that Mark Cuban seems to understand better than most.