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Token-maxing is an AI cost sink - how to use agents without busting your budget

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Why This Matters

Token-maxing in AI applications is leading to unsustainable costs for businesses, highlighting the need for strategic token management and responsible exploration of agentic AI. As token consumption accelerates, companies must develop effective tokenomics to avoid budget overruns and ensure long-term viability of AI initiatives. This shift underscores the importance of balancing innovation with cost control in the evolving AI landscape.

Key Takeaways

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ZDNET's key takeaways

Token-maxing to support agentic AI is unsustainable.

Business leaders must create a strategy for token use.

Give people room to explore agents within guidelines.

Twelve months in AI is an eternity. Steve Lucas, CEO at integration technology specialist Boomi, was concerned last year that CIOs were rushing into gen AI initiatives without a clear sense of direction. Now, a year later, he's concerned that IT professionals are taking a similarly rushed approach with agentic technology, and the scale of token usage is only going one way: upward.

"Whether you work inside or outside a company, it feels like your core hustle is to use AI and you token max the heck out of that technology for your own job," he said to ZDNET.

Also: The 3 types of people who will excel in the AI agent era, according to tech leaders

A token is the fundamental unit of information processed by an AI model, and research points to the soaring and unpredictable costs of agents as the technology consumes orders of magnitude more tokens.

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