Over the past few years, Artificial Intelligence (AI) has gone from something in science fiction movies to a reality with tools such as ChatGPT and others.

Even if these AI tools aren’t true AI (yet), their popularity and incredible potential brought in a massive amount of funding from venture capitalists, major corporations, and others in order to fund research into this promising field.

While there is no doubt that AI has a huge amount of potential, many of the investors who have put up billions of dollars are starting to want to see a return on that investment.

Unfortunately for many companies, AI-powered products are not as lucrative as they had hoped. At least not yet.

Another challenge that AI startups are facing is that the major players are doing very well. OpenAI, which makes ChatGPT and Dall*E is backed by the deep pockets of Microsoft and has put out two of the most popular AI tools so far.

These tools are being used by both individuals and businesses, and the premium subscriptions are generating millions in revenue to help support further development.

The thousands of startup companies in this field aren’t having nearly that level of success.

When it comes to tech companies, there is a cycle that seems to happen with most major advancements.

First, there is a lot of buzz around a specific area, which brings in investors. These investors are willing to put up large sums of money in an attempt to bet on the right company that will change the industry.

Over time, a majority of the startups fail, but the few that are successful end up becoming household names.

In this cycle with AI, startups are facing some additional obstacles. The technology behind modern AI requires massive amounts of computational power and storage in order to operate properly.

This means that the companies need to purchase, or at least buy access to, very powerful servers and networking equipment.

Of course, this equipment does not come cheap.

Having to support and even modernize this type of infrastructure can quickly burn through even large cash reserves that a startup may have received from initial and ongoing investments.

Ali Ghodsi, the CEO of Databricks, summed the issue up well:

“You can already see the writing on the wall. It doesn’t matter how cool it is what you do – does it have business viability.”

Over the past three years, about $330 billion has been invested in 26,000 AI startups. As many of these companies fail, and others are unable to produce a viable product, investors will start to shy away from throwing more money into these companies.

This will add even more financial stress to the equation, undoubtedly resulting in a growing number of AI company bankruptcies.

It seems Artificial Intelligence isn’t smart enough to make a profit.

If you enjoyed that story, check out what happened when a guy gave ChatGPT $100 to make as money as possible, and it turned out exactly how you would expect.