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Mon, 03 Aug 2026

Mon, 03 Aug 2026 Tokenomics: Why making AI pay is tricky

Buyers of AI services are struggling to control costs and sellers are not sure how much to charge.
Big Tech Companies Struggle with AI Pricing As large language models (LLMs) become increasingly popular, companies are finding it difficult to set prices for their services. Firms like Microsoft and Google have invested heavily in developing LLMs, but setting a price for their paid-for versions is challenging. Token Economics Pose a Problem The issue lies in the economics of tokens, which are the building blocks of LLMs. Tokens are used to process prompts and generate responses, but the process is not entirely predictable. Subtle variations in prompts can produce different answers, making it difficult to estimate token usage. Unpredictable Costs As a result, companies are struggling to manage their AI costs. Some have been caught off guard by high bills for token consumption, including Microsoft, which reportedly reined back on external use of some third-party coding tools, and Uber, which burned through its AI coding token budget in just months. Industry Experts Weigh In Experts say that companies need to be more precise with their prompts and think carefully about what AI models to use. They also recommend considering the long-term costs of using AI agents, rather than just focusing on short-term savings. No Clear Solution Despite efforts to address the issue, there is no clear solution in sight. Companies are experimenting with different pricing models, including flat fees and pay-per-use, but these may not be sustainable in the long term. Industry Leaders Grapple with Pricing Strategies As companies grapple with pricing strategies, industry leaders are warning that the current system is unsustainable. "You get into variable pricing, and it's changing every couple of months," says Bill Peterson, senior director of product marketing at Sumo Logic. "Customers don't like that. That's not how anybody builds a budget."