In the heart of midtown Manhattan, Ed Zitron, a former tech publicist turned AI critic, is challenging the financial narratives surrounding the AI industry. Known for his distinctive style and no-holds-barred approach, Zitron has been a frequent guest on financial news outlets, dissecting the economics of AI companies like OpenAI and Anthropic.
Zitron’s journey began with a personal struggle. ‘I started writing on the side because I was not doing well emotionally,’ he shares. ‘I was quite depressed for several years. I got way better. Tons of therapy. It’s awesome.’ This emotional journey led him to launch a newsletter, Where’s Your Ed At and a podcast, Better Offline which sees between 750,000 and 1 million downloads a month.
The Financial Reality of AI Companies
Zitron’s criticism centers around the financial realities of AI companies. He argues that while companies like OpenAI and Anthropic have massive valuations, they are far from profitable. ‘OpenAI burned $20.9 billion in 2025,’ Zitron states, highlighting the stark contrast between their expenditures and revenues.
The AI industry is structured in a pyramid, with companies like Nvidia at the top, producing GPUs for data centers. These data centers are then rented out to companies like OpenAI and Anthropic, which use them to process user prompts. This process, known as inference is measured in tokens. However, the cost of these tokens often outweighs the revenue generated from user subscriptions.
The Trillion-Dollar AI Buildout
The scale of the AI buildout is staggering. ‘Over $1 trillion now, easily,’ Zitron says, referring to the amount spent on the AI infrastructure. He predicts that hyperscalers will spend another trillion next year, raising questions about the sustainability of such massive investments.
Zitron’s concerns extend to the debt levels of these companies. ‘They’ve added $746 billion worth of PP&E—which is just properties, plants, and equipment—in the last four years,’ he notes, highlighting the financial strain on these firms.
The AI Bubble and Its Consequences
Zitron compares the current AI boom to past bubbles, such as the dot-com bubble and the crypto craze. He argues that the AI bubble is different because it involves a product, albeit one with questionable financial viability. ‘LLMs have an interesting underlying tech and can do some stuff, but every useful function that you see with an LLM comes from tens of billions of dollars of training expense and over $1 trillion worth of [capital expenditures] at this point,’ he explains.
The financial media’s role in this narrative is also a point of contention for Zitron. He criticizes the lack of scrutiny and the uncritical acceptance of the AI industry’s financial claims. ‘The media fails to hold the powerful accountable,’ he says, warning of the potential economic fallout for retail investors and the broader economy.
Zitron’s predictions about the AI bubble have been met with skepticism, but he remains steadfast in his analysis. ‘I’ve had to learn a great deal about economics and hardware and software,’ he says, emphasizing his commitment to publishing detailed, fact-based arguments.
As the AI industry continues to evolve, Zitron’s critical voice serves as a reminder of the financial realities that underpin the technological revolution. His insights offer a sobering counterpoint to the hype, urging a closer examination of the economics driving the AI boom.
