Merriam-Webster picked “slop” as its word of the year for 2025. It describes low-quality digital content created by AI. This choice highlights a growing concern. As companies lean into AI for savings, they also face new risks.
Ed Zitron, an AI critic, argues that the business model isn’t working. He believes AI companies are pouring money into tech without earning enough back. While AI revenues are increasing, they aren’t enough to cover the $400 billion investments expected in 2025.
Cory Doctorow, another vocal critic, claims that many AI firms rely on outside funding and that this isn’t a sustainable model. Often, new tech businesses run at a loss for several years, but they usually find a way to profit as expenses drop. However, every new version of AI tends to be more costly, using up more resources and expertise.
Building the massive data centers required for AI is incredibly expensive. A Bloomberg analysis showed that in 2025, there were nearly $178.5 billion in credit deals for these facilities. Many new players are trying to cash in, leading to a kind of financial frenzy. Yet, the chips that power these centers can quickly become outdated, raising concerns about long-term investment.
This financial strategy echoes past corporate failures and may signal another bubble. Relying on AI to turn profits by telling grand stories of transformation feels risky. AI isn’t just a tool for handling data; opinions like OpenAI’s Sam Altman and Meta’s Mark Zuckerberg suggest it might surpass human intelligence or even replace human connections.
But the impact on jobs is real. Brian Merchant, who wrote Blood in the Machine, shares stories from those fired in favor of AI. These individuals highlight the mediocre quality of AI-generated work and the potential dangers of removing human oversight.
Recent incidents illustrate this risk. In the UK, the high court cautioned lawyers about using AI in cases where fake legal precedents were cited. In Utah, police learned the hard way that relying entirely on AI could lead to absurd outcomes, like an officer being reported as turning into a frog during a transcription error.
Merchant calls the low-quality AI content “slop,” complicating our ability to discern real from fake information. Doctorow warns that AI is not on the verge of superintelligence—it is simply a collection of useful tools that work best when people control their use.
Despite the many productivity benefits AI may offer, it might not justify the high valuations and massive investment levels. If sentiments shift, financial markets could shake. According to the Bank for International Settlements, the top tech stocks now make up 35% of the S&P 500, up from 20% three years ago. If their prices correct, the ripple effects could impact investors worldwide.
In the UK, the Office for Budget Responsibility estimated a stock market drop could reduce the GDP by 0.6% and result in a significant public finance hit. While this may not match the severity of the 2008 financial crisis, it would still be a tough blow for an economy already struggling.
So as we navigate this AI-driven landscape, it’s vital to remember the broader implications. Major tech companies and their influential leaders may face challenges, but their struggles will resonate far beyond their immediate circles, affecting all of us.
