Companies Scramble to Control AI Spending as Token Costs Explode 10x in a Year
14 Sources
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Token-maxing is an AI cost sink - how to use agents without busting your budget
Follow ZDNET: Add us as a preferred source on Google. 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,
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Artificial intelligence: Why firms are struggling to set prices
If you have used a free version of an ChatGPT or its AI rivals, then you are obviously getting a good deal. Firms like Microsoft, Google and Anthropic have invested hundreds of billions of dollars in developing Large Language Models (LLMs) the tech behind those services. So getting, ChatGPT,
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What Are Companies Getting for All That A.I. Spending?
Corporate America was enthusiastic about artificial intelligence. Until it got the bill. Whiplash around spending on "tokens," the units of computing power in which A.I. is sold, is hitting engineering teams and board rooms. First there was "tokenmaxxing," as executives encouraged as much A.I. use
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EY built an 'AI router' to stop its own AI bills from spiralling
The Big Four firm is steering tasks to cheaper models to control token costs, part of a wider corporate reckoning with the price of AI. EY has built what it calls an "AI router," a system that steers each task to the cheapest model that can handle it, in an effort to keep its own soaring AI bills
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AI tokens could become the kilowatt-hour of the AI age
Earlier this year, OpenAI CEO Sam Altman declared, "We see a future where intelligence is a utility, like electricity or water, and people buy it from us on a meter." Many other AI companies seem to be betting on a similar future. If that vision actually comes to be, then "AI tokens" may break out
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Atlassian puts its engineers on an AI budget as the cost of 'tokenmaxxing' bites
The software maker cut thousands of jobs in the name of AI. Now it is handing the engineers who remain capped 'AI wallets,' a sign the industry's token spending has become a line item to manage. Atlassian has started giving its engineers a fixed monthly allowance for artificial intelligence, a
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AI coding agents are blowing through budgets -- Replit, Kilo Code, and Symbotic explain how they're managing it
At Kilo Code, engineers are reading or writing code themselves only about 1% of the time now, according to co-founder Emilie Schario -- the rest is agents. That shift is forcing new questions onto dev teams: which systems are safe to hand over, who cleans up when models goof up, how to support
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Beyond Tokenmaxxing: the rising token tax on enterprise AI
During the first wave of AI adoption, much of that cost was effectively hidden from customers. AI came wrapped in subsidized pricing, generous allowances and a relentless focus on driving usage. The message was simple: use more AI. In some organizations, usage itself has become the goal. The rise
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Atlassian tightens tracking of staff AI use as other technology firms encourage 'tokenmaxxing'
Some companies reportedly using leaderboards for employees who used the most AI in their work Software firm Atlassian has sought to tighten tracking of its staff's AI spending by introducing "wallets" with monthly caps of up $2,000 for each employee, amid an explosion in costs at other tech
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BNY skipped the 'tokenmaxxing' craze. Here's what AI metrics it tracks instead | Fortune
Good morning. Tokenmaxxing quickly became one of the buzziest metrics in enterprise AI. Fortune's Jeremy Kahn reported that "tokenmaxxing" turned into a status symbol at some big tech companies, where engineers were urged to climb leaderboards by burning more AI tokens. He argues that the practice
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The AI 'tokenmaxxing' corporate fad is fading as workplaces look to cut costs
Tech executives cast high AI usage as a badge of honor Just a few months ago, Silicon Valley executives were promoting high token consumption as a signal of high-performing employees. The stereotypical tokenmaxxer was staying up late -- perhaps ignoring their significant other -- while
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A flex in corporate America, AI 'tokenmaxxing' fades as workplaces look to cut tech spending
A corporate fad of "tokenmaxxing" on artificial intelligence technology is hitting its limits as workplaces throwing AI at everything are seeing the costs rise without a similar spike in productivity. What started as tech industry-fueled springtime hype over squeezing as much AI-generated work as
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Workplaces Look for Cheaper AI as 'Tokenmaxxing' Fades as a Corporate Fad
A corporate fad of "tokenmaxxing" on artificial intelligence technology is hitting its limits as workplaces throwing AI at everything are seeing the costs rise without a similar spike in productivity. What started as tech industry-fueled springtime hype over squeezing as much AI-generated work as
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Finance Teams Are Done Flying Blind on AI Costs | PYMNTS.com
That approach worked while AI spending was small enough to absorb without much scrutiny. It no longer is. Enterprise software once ran on annual licenses and seat-based pricing that finance teams could forecast with reasonable accuracy, PYMNTS reported. AI, priced in tokens, compute cycles and
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Businesses are experiencing a dramatic shift from encouraging unlimited AI token usage to implementing strict controls as bills skyrocket. Major firms report 10x increases in AI spending, with some burning through annual budgets in months. Companies like EY are deploying AI routers to manage costs while the industry develops tokenomics frameworks.
The Token-Maxing Era Comes to an Abrupt End
Corporate America's enthusiasm for artificial intelligence hit a wall when the bills arrived. Companies that spent the past year encouraging employees to maximize AI token usage—a practice dubbed "token-maxing"—are now scrambling to control spiraling token costs as AI spending threatens to consume entire technology budgets
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. Steve Lucas, CEO at Boomi, reported personally spending 10 times more on Claude in one year compared to the previous year, calling the trajectory "not sustainable"1
. The shift from tokenmaxxing to what some now call "tokenminimizing" reflects a fundamental reckoning with AI token usage patterns across enterprises3
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Source: NYT
Agentic AI Systems Drive Unpredictable Cost Explosions
The rise of agentic AI systems has transformed token costs from predictable to chaotic. When businesses deploy multiple AI agents together to make decisions and automate processes, token consumption increases dramatically and unpredictably
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. Unlike simple chatbot interactions, agentic workflows can consume orders of magnitude more tokens as agents iterate through complex tasks. Microsoft reportedly reined in engineers' use of third-party coding tools, while Uber burned through its entire annual AI coding token budget in just months2
. Goldman Sachs forecasts that token consumption will increase 24 times between 2026 and 2030 to 120 quadrillion tokens monthly as companies shift to agentic AI adoption2
. The fundamental challenge lies in the non-deterministic nature of Large Language Models—subtle variations in prompts produce different answers, making cost prediction nearly impossible2
.EY Deploys AI Router to Control Billion-Dollar AI Investment
EY, which invests over $1 billion annually in AI and operates approximately 1,000 AI agents, built an "AI router" to steer tasks to the cheapest model capable of handling each request
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. The system represents sophisticated cost-conscious AI deployment, reserving expensive models for complex problems while routing simpler tasks to cheaper alternatives. This approach addresses a paradox in token economics: while the price per token has collapsed, enterprise AI spending has tripled because agentic tools running multi-step processes consume far more tokens than single chatbot prompts4
. EY's own research revealed that 82% of 534 senior US business leaders surveyed expressed concern about AI token usage costs, with 98% of those using token-based tools reconsidering their AI pricing strategy4
. Critically, only 64% of firms actively monitor token usage with budgetary guardrails, meaning a third are spending on AI without clear meters4
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Source: PYMNTS
Tokenomics Emerges as New Economic Discipline
The complexity of AI spending has spawned "tokenomics"—the practice of measuring, pricing, and managing token consumption as a distinct business activity
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. Howard Rubin, an economist advising companies on technology spending, described tokens as "a currency where you have no instinct to know what you're using, and the accounting practices aren't even there for it"3
. The Linux Foundation established the Tokenomics Foundation in June to create common parameters that AI providers agree to disclose, standardizing frameworks for organizational decision-making3
. Companies are turning to specialized service providers like Revenium to track whether token spending improves productivity enough to justify costs, mapping token consumption to specific outcomes like software features shipped3
.Related Stories
AI Tokens May Become the Kilowatt-Hour of the AI Age
OpenAI CEO Sam Altman envisions a future where "intelligence is a utility, like electricity or water, and people buy it from us on a meter"
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. If this vision materializes, AI tokens could become the defining measure of a new industrial age—the kilowatt-hour of the AI age for measuring and paying for AI adoption5
. Tokens represent the tiny chunks of text and data that AI models process, with more complex work typically requiring more tokens. While AI companies like OpenAI, Microsoft, and Google still offer flat-rate subscriptions to consumers, they increasingly charge businesses based on token usage5
. Researchers are already using token data to track AI's economic impact, with economists analyzing 380 trillion AI tokens to understand how AI consumption reshapes financial markets and creates an "AI premium" for certain stocks5
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Source: NPR
Balancing Innovation with Economic Reality
Despite mounting concerns about AI spending, business leaders emphasize the importance of giving staff room to explore AI agents within structured guidelines. Snowflake CEO Sridhar Ramaswamy acknowledged concerns about AI spending at Summit 2026 but insisted the investment creates opportunities to transform processes into products for customers
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. Matt Luizzi, VP of analytics at Whoop, described implementing guardrails and monitoring while enabling staff to take risks, stating "we're leaning in hard because we think there's an ROI to this"1
. The fundamental question facing enterprises, according to Lucas, is "Can I operate AI at a return?"1
. Companies are finding answers by cutting software licenses and outside services to fund AI spending, with some scrounging resources before making strategic reallocation decisions3
. As EY's global AI consulting leader Dan Diasio noted, "'AI saves time' is no longer sufficient when costs mount and remain unclear"4
, marking a decisive shift from adoption at any price to value at a known cost.References
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