Anthropic filed a registration statement for its initial public offering ahead of a planned November 2026 stock market debut, raising concerns among critics about the company's financial transparency and long-term viability.
The company's financial disclosures reveal nearly $900 billion in spending commitments, the vast majority stretching into the 2030s. With only $96 billion in cash reserves, Anthropic faces at least $582 billion in non-cancelable commitments to five major technology companies -- Amazon, AMD, Broadcom, Google, and Microsoft -- for the computational power required to train and run its generative AI models. These obligations, while not appearing on the balance sheet, are effectively debts in a legal and practical sense.
Compounding the financial pressure, Anthropic's 2026 results have not been subjected to formal auditing. Third-quarter 2026 figures suggest the company's revenue growth slowed significantly over the summer. The company will need to reverse this trend and sustain extraordinary revenue growth to meet its vast obligations.
Critics point to several industry-wide challenges that will make this task exceptionally difficult. Multiple studies, including from organizations noted for their bullishness on AI, suggest large language models are not accelerating productivity or generating positive returns on investment for most businesses. One study found the number of Americans using AI at work fell from 46 percent in the summer of 2025 to 33 percent in the summer of 2026. When Anthropic released its much-hyped Fable 5 frontier model this summer, its commercial reception was tepid.
The AI industry's frenzied competition further complicates Anthropic's outlook. With numerous well-heeled corporations offering generative AI models that are largely indistinguishable in quality, companies can rarely raise prices without prompting customers to switch to rivals. An ongoing price war, intensified by competition from Chinese firms offering open-weights models and locally run alternatives, applies downward pressure on pricing even as high costs persist.
Those costs are substantial. A one-gigawatt data center costs an estimated $31 billion to build. Anthropic has committed to 15 gigawatts of data center capacity and estimates it will ultimately need 20-25 gigawatts, explaining the company's half-trillion-plus dollars in spending commitments. Once operational, training AI models and processing user queries require massive amounts of energy and cooling infrastructure.
External factors add further uncertainty. The backlash to AI and data centers across the country has scuttled and delayed numerous projects. Rising costs related to geopolitical events and supply-chain challenges could drive operational costs higher still.
The SEC is being urged to intervene. The agency has the power to delay or stop companies from going public if it believes a registration statement is "on its face incomplete or inaccurate in any material respect." Critics argue the company's prospectus includes only unaudited financial results for the period where it claims the greatest revenue growth, while relegating its most significant future obligations to footnotes. The recommendation is for the SEC to block Anthropic's IPO until the company provides two consecutive quarters of audited financial statements with all material information about spending commitments disclosed.
The author warns that if Anthropic goes public, an ever-larger share of the fallout from a potentially devastating AI crash would fall on ordinary people. As a private company, Anthropic's shares are overwhelmingly owned by corporate insiders, tech giants, and venture capitalists. Once the company goes public and shares enter 401(k)s, retirement accounts, and index funds, workers and retirees would be increasingly left holding the bag when financial pressures bite.
Adding another huge, unprofitable tech giant to public exchanges could exacerbate risks to a stock market that is already historically overvalued and disproportionately concentrated in a handful of tightly interconnected mega-cap tech companies, the analysis suggests. That has already created a risk of a historically damaging stock market crash; never before has such a huge amount of wealth depended on the performance of so few companies whose fortunes are inextricably linked.
