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 takeawaysToken-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 leadersA 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. As my ZDNET colleague Steven Vaughan-Nichols discussed recently, it wasn't so long ago -- certainly during the rise of generative AI -- that everyone was excited about their token leaderboard, which showed who had the most token usage in an organization. Today, token leaderboards are obsolete because no one can afford to waste tokens. In the agentic era, token maxing is a sign of excess, and "tokenomics" -- the practice of measuring, pricing, and managing the consumption of tokens -- is a key business activity, even for a tech CEO like Lucas, who noted that tokens are being consumed at a much faster rate."A year ago, we weren't talking about tokenomics," he said. "But last year, I personally spent at Boomi 10 times the amount on Claude that I did the previous year -- 10 times; that's not sustainable. I can't do that every year."Also: The new enterprise AI expert every company needs - and whyThe onus now is on businesses and professionals to create their own enterprise-ready version of tokenomics. Agentic AI is set to transform how every business operates -- and creating a cost-effective technique for exploring agents is an urgent priority, suggested Lucas."What matters in the enterprise is ultimately the economics of AI," he said. "Most organizations will look to AI as the enterprise engine of the future. So, what matters now is, 'Can I operate AI at a return?' That is the fundamental question."Business leaders suggested the best way forward is clear: Rather than constraining how people can use agents, give them guidelines and the context to make cost-effective model decisions.Letting people shineSnowflake CEO Sridhar Ramaswamy recognized that token consumption is on the rise, even in his own organization. However, he also said it's critical to give staff the wriggle room to explore agents."Are we worried about how much we are spending on AI inference across our different internal teams? Absolutely," he said. "But do I see that spend as a reason not to use AI? Absolutely not." While token maxing is a concern, Ramaswamy said during a media session at his firm's recent Summit 2026 event in San Francisco that the creative use of AI can help unlock new business opportunities. Also: 40% of enterprises will scrap AI agents - 3 ways to ensure yours don't failAgents can help boost staff efficiency and productivity, with the potential to generate new services for his firm's clients faster and more effectively."We look at agentic AI as an opportunity to optimize not just what we do, but how we can turn a process into a product that our customers can use," he said.Like Ramaswamy, Matt Luizzi, VP of analytics at wearable technology specialist Whoop, said his company is investing in agentic explorations to find a competitive advantage."If we want people to push themselves out of their comfort zones, we're going to need to be OK with them taking risks and understanding that you can't break anything."Also: AI is causing cognitive fatigue. Here's how to work with more haste and less speedIn short, Luizzi said that he's OK with staff spending money on agents, but that doesn't mean token consumption gets out of hand. "We have guardrails in place, and monitoring and observability to let people know what they're spending," he said during a panel session at Summit 2026."But more likely than not, we just need to sit down and enable them on, 'How could you be doing this more efficiently and what are you trying to accomplish?'"Putting everything into contextThe key to agentic success, suggested Luizzi, is carefully managed enablement. Yes, let people push the boundaries with agents and tokens, but don't let them go overboard."At the end of the day, we're leaning in hard because we think there's an ROI to this. We are seeing people become more efficient. We are seeing work get done faster," he said.Also: How Workday and other software providers plan to survive AI"Those positive results mean we're not trying to be super keen on how many tokens people use but also understanding that this is something that needs to scale, so not enabling people to go crazy either."Sriram Sitaraman, CIO at technology specialist Synopsys, said in the same panel session at the Snowflake conference that people must be able to explore new avenues, including agents, to discover innovative solutions to business challenges: "You can't innovate with constraints; you can only go so far."Like Luizzi, Sitaraman said guidelines can help set tight boundaries for token consumption. He suggested that the right context for projects can help establish effective constraints."If you ask an agent, 'What should I do tomorrow?' it might consume a whole lot of data, a whole lot of tokens, and come back with something that isn't useful," he said. "If you set a context, such as creating a North America sales ops agent, giving the project specific objectives and data, then the consumption is going to be limited, and the value that it delivers to the user is higher."Also: How to beat the AI algorithm and get the job of your dreamsThat focus on business context was echoed by Francois-Xavier Pierrel, group chief data and ad tech officer at French TV network TF1, who told ZDNET that a common-sense approach is the best way for business and professional users to control token use.Pierrel compared the alternative approach to a sugar addiction. Once you begin adding sugar to your food, you get used to it and start to develop an unhealthy addiction. He said AI presents similar risks."Everything was cheap, very cheap, and we got all into it," he said, looking back at the early rush to use generative AI technologies. Now, agent obsession represents a more costly proposition."The number of tokens used can quickly become a big number. And at some point, if we look at all the companies investing crazy money into agentic AI, the bill will come back." Also: Forget productivity: Here are 5 strategic shifts that drive real AI valuePierrel said caution is the watchword in his organization, and he gave an example of how professionals are asked to consider their options when using large language models."For use cases that are very narrow or have strong boundaries, we say, 'Can we use a small model, something that will consume fewer tokens than expected or planned, and that will still do the same job?'" As companies look to deploy more agents as part of working processes, Pierrel suggested this kind of tokenomics strategy will be crucial to value creation. Also: AI agents are your new colleagues - how to get the best results"I think we are going to be more agile on this one, trying stuff, and then adapting to the use case to avoid having crazy bills," he said. "We're not shooting a rocket to the moon. So, let's be reasonable -- don't deploy a million agents if you can do it on a smaller scale and it will still work."