Every time you ask a chatbot a question, generate an AI image, or use a smart assistant at work, it kickstarts an expensive process behind the scenes.

Powerful computers process your request inside enormous data centers. Those facilities require specialized chips, electricity, cooling systems, buildings, and thousands of pieces of equipment. None of that comes cheap!

As companies race to build the infrastructure needed to support artificial intelligence, they’re spending hundreds of billions of dollars.

There’s just one problem: Increasingly, that expansion is being funded with borrowed money.

Some financial experts are beginning to question what happens if AI doesn’t generate enough revenue to repay it.

Why Does AI Need So Much Money?

Unlike traditional software, AI requires extraordinary amounts of computing power. Training advanced AI models can involve thousands of specialized processors working together. Once those models become available to the public, companies must continue paying to operate them.

Now multiply that demand across millions of users.

Companies need more data centers, more processors, more electricity, and more infrastructure to handle that amount of traffic. Building all of that also takes enormous amounts of money long before the facilities begin generating revenue. To do that, the companies need to start borrowing.

What Is Private Credit?

You’ve probably heard of companies borrowing money from banks or issuing bonds. Private credit works a little differently.

Instead of borrowing through traditional banks or public bond markets, companies obtain loans directly from investment firms, private funds, and other nonbank lenders. These arrangements can offer more flexibility for large, complicated projects.

They’re also becoming an increasingly important source of funding for AI infrastructure.

AI-related data center and project financing deals had surged to $125B in 2025, compared to $15B during the corresponding period in 2024. That’s an enormous increase in just one year.

Even Meta Needs to Borrow Billions

Consider Meta, the company behind Facebook, Instagram, and WhatsApp. They arranged a $29B financing package for a massive data center project in Louisiana.

The arrangement involved major investment firms and demonstrated how private financing was becoming central to AI expansion.

Meta isn’t alone, either. Companies throughout the AI industry are borrowing heavily to build infrastructure they expect will become increasingly valuable.

These companies assume that the demand for AI will keep growing, and their future revenue will justify today’s enormous investments.

So what happens if the demand stops, and the profits don’t justify the sunk costs?

What Happens if AI Doesn’t Pay Off?

Borrowing money isn’t automatically dangerous. In fact, businesses borrow to expand all the time.

The risk comes when the expected revenue doesn’t materialize. Companies are investing heavily based on expectations about future demand, subscription revenue, business adoption, and technological development. If those expectations prove overly optimistic, some could struggle to repay their debts.

There are also practical problems. A completed data center cannot generate its expected revenue if it doesn’t have enough electricity to operate. Power shortages and delays in connecting data centers to electrical grids could create additional financial risks for these lenders.

Why Should Ordinary AI Users Care?

You might be wondering what private credit has to do with your daily use of AI. Potentially, quite a lot.

If companies face pressure to recover their investments, they may need to rethink how they price and deliver AI services. That could eventually mean higher subscription prices, tighter usage limits, fewer free features, or changes to which products remain available.

There’s also a cybersecurity and data privacy angle. As organizations become increasingly dependent on AI platforms, financial instability at a provider could create business continuity concerns.

What happens if a service you rely on suddenly becomes unavailable?

What if a provider changes its terms, reduces support, or shuts down a product?

That’s why it’s important to avoid making any one single AI service indispensable.

Don’t Put All Your Eggs in One AI Basket

You don’t need to understand financial markets to protect yourself from potential disruptions.

A few simple habits can help:

  • Keep copies of important documents outside your AI platform.
  • Avoid using AI conversations as your only storage location for valuable information.
  • Review subscription costs and changes to service terms.
  • Use approved AI tools for workplace information.
  • Have an alternative process for important tasks if an AI service becomes unavailable.

Most importantly, remember that convenience doesn’t guarantee permanence. Just because an AI service is free, inexpensive, or widely available today, doesn’t mean it will always stay the same.

Conclusion

Artificial intelligence is advancing at an extraordinary pace. Unfortunately, the infrastructure supporting that progress has become extraordinarily expensive.

Private credit and other forms of borrowing are helping finance the expansion, allowing companies to build facilities they might otherwise struggle to fund.

That doesn’t mean the AI industry is destined for a financial crisis, but that the future of artificial intelligence depends on more than impressive new capabilities. Companies eventually need to earn enough money to support what they’re building.

For everyday users, the lesson is simple: AI may feel like an unlimited digital resource, but behind every prompt is a very real bill that somebody needs to pay.