Advances in AI capabilities to outpace cost savings
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Enterprise dependence on AI will keep overall costs increasing exponentially even as per-token prices fall, according to Gartner. AI tokens may be getting more cost effective for enterprises, but organizations' reliance on AI systems and how much they use the technology will keep driving up spending. Enterprises have worked to deploy agentic systems in 2026, with spending on AI-optimized infrastructure as a service - the compute that supports large language model training and operation - projected to nearly double through the end of 2026, reaching $42 billion, Gartner found earlier this month. Sommer told CIO Dive in a July interview that Gartner estimates global token consumption to be about 300 trillion tokens per day, an annualized growth rate of 500% to 600%. Hard-to-predict AI costs are forcing some enterprises to rethink their implementation plans. Nearly half of organizations reported that they've escalated AI spending surprises to the board, according to a July report by cost management software Mavvrik. Three main factors are shaping current token economics, Gartner's Monday report found. Foundational model costs are going down - a win for enterprises - but improved AI efficiency is unlocking more powerful, expensive models to chase higher-value AI applications. Those sophisticated AI workflows use far more tokens than earlier models' simple chatbot interactions...
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