AI startup Anthropic is taking a different approach to the AI infrastructure competition by prioritizing algorithmic efficiency and high-quality data rather than expanding compute capacity like rivals such as OpenAI. CNBC reported that Daniela Amodei, Anthropic's president and co-founder, stated that although the Scaling Law governing compute and model size remains valid, it is not the only route to success in AI development. Amodei emphasized that sustainable economic models will determine long-term leadership in the sector.
Operating with significantly less compute power and capital than competitors, Anthropic claims to deliver leading AI model performance through smarter resource use. Daniela Amodei pointed out that the distinction between the "technology curve" of AI advancement and the "economic curve" of market adoption is often blurred. While technology improves rapidly, real-world adoption depends on organizational readiness and human factors, slowing economic gains. She warned that excessive early investments in compute might lead to unsustainable fixed costs.
To retain operational flexibility, Anthropic employs a multi-cloud deployment strategy instead of relying heavily on a single cloud provider. Dario Amodei, another co-founder, highlighted at the New York Times DealBook Summit in December 2025 that the economic benefits of AI growth remain uncertain. He cautioned against overly aggressive, risky AI investment approaches, which media outlets have speculated may target OpenAI's strategy.
Supporting this caution, a previous MIT study found that only 5% of internal AI projects achieve millions of US dollars, with most failures attributed to poor integration rather than the AI models themselves. When questioned about Anthropic's focus on the enterprise market, Daniela Amodei explained that businesses seek efficiency and are willing to invest in AI tools that deliver predictable value and frequent usage. Enterprise adoption involves complex workflows, procurement, IT integration, and training, which create high switching costs and customer retention—factors less present in consumer markets, which are often driven by novelty and easier product switching.
The Wall Street Journal has reported, citing internal financial data, that Anthropic's business-to-business-focused strategy positions it to reach profitability by 2028—two years ahead of OpenAI. This approach contrasts with the compute-heavy investments made by other players in the AI technology race.
Article edited by Jerry Chen
