Ahead of its IPO, Anthropic’s Daniela Amodei shrugs off doubts about AI’s returns
Anthropic, an AI model maker, is pursuing an IPO after a massive oversubscribed private funding round, with co-founder Daniela Amodei emphasizing the need for capital to advance AI frontier. Despite some industry doubts about AI spending returns, Amodei remains confident in AI’s growing value across various sectors.
Anthropic, a rapidly growing AI model maker, is taking steps toward a public listing by confidentially filing for an IPO. This move follows an overwhelmingly successful private funding round, where the company secured $65 billion at a $965 billion valuation, significantly oversubscribed due to strong investor demand. Daniela Amodei, co-founder of Anthropic, stated that access to capital is crucial for training models and serving inference, making public markets well-suited to meet this need as the core companies advancing AI frontiers will increasingly require substantial investment.
The company has experienced breakneck growth, with annualized revenue soaring to $47 billion in May, a dramatic increase from $9 billion at the end of 2025. However, this growth trajectory faces scrutiny, as some companies, like Uber, have found that not all AI spending yields productive returns. This raises concerns that corporations might rein in AI budgets, potentially slowing sector-wide growth.
Amodei, however, remains unfazed. She believes businesses are still in the early stages of effectively deploying AI. She anticipates that current use cases, such as coding, financial services, legal, and healthcare, will continue to drive efficiency and creativity. As businesses become more familiar with AI tools, she expects greater integration into daily workflows, leading to significant realized value.
Regarding infrastructure, Anthropic is not building its own data centers, unlike rivals OpenAI and xAI. Amodei explained that their strategy has always been to plan for optimal outcomes without overextending by acquiring more compute capacity than they can productively use. She noted the difficulty in perfectly predicting compute needs, preferring to have slightly more demand than they can serve rather than the inverse. This perspective aligns with their recent partnership with xAI for compute capacity, a deal valued at $1.25 billion per month.
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