Analysis: Spending cuts impact OpenAI and Anthropic growth expectations; the AI industry shifts toward a cost-efficiency era

Odaily Planet Daily News As enterprises begin to reassess the return on AI investment, the industry is transitioning from a "tokenmaxxing" high-consumption model to an efficiency-first approach, putting new growth constraints on major AI model developers. Many companies have started to cut or optimize model call costs. For example, the CEO of AI startup Lindy stated that they have shifted 100% of their traffic from Anthropic's Claude model to the lower-cost DeepSeek, which is expected to save millions of dollars in expenses within a few months.

This shift reflects tightening enterprise AI budgets, with the previous "unlimited model resource usage" tokenmaxxing model gradually being replaced by cost control and ROI-oriented approaches. Some companies have even implemented tiered budgets for AI tool usage, such as Uber setting monthly caps on internal AI spending.

Analysts point out that as enterprises move from "expanding usage" to "refined deployment," the rapid growth model that OpenAI and Anthropic previously relied upon is facing challenges. Industry data still shows strong growth: Anthropic's annualized revenue is approximately $47 billion, while OpenAI's run rate is close to $25 billion. However, the market is beginning to focus on the sustainability of this growth.

Meanwhile, model calling methods are evolving, with technologies like "model routing" emerging, using lower-cost models to replace premium models for simple tasks to optimize overall computing costs. Industry competition is also intensifying, with Microsoft, Amazon, and Google all accelerating the launch of low-cost AI models and enterprise-grade tools, further compressing pricing space. Against the backdrop of increasingly rational enterprise AI spending, major model companies may face the dual pressures of "slowing growth expectations" and "IPO window pressure." (CNBC)