Dear CFOs: Don’t Stop the Employees Consuming the Most AI Budget

Many companies are currently making the same mistake. As soon as an employee suddenly consumes €1,000 or more per month in AI tokens, a discussion about cost control immediately arises. Finance looks at dashboards, sees rising usage, and thinks: this needs to be more efficient. But that is exactly where it goes wrong. Because the employees using the most AI budget are often not the ones wasting it. They are precisely the people building entirely new ways of working within your organization.

These are the employees running multi-agent workflows while they sleep. People deploying multiple AI systems simultaneously to conduct research, generate reports, produce content, write code, perform customer analyses, and automate processes. Where previously three departments were needed, a single AI-native operator now emerges, managing entire chains through prompts and smart workflows.

Many CFOs still view AI as if it were a traditional software license-a fixed cost that must be kept as low as possible. But AI does not work the way SaaS used to. AI is not a tool you pay for per seat; AI is variable output. The more strategically an employee deploys AI, the greater the output they can generate.

This also means that high token costs are not automatically a bad thing. In fact, the opposite is often true. The employee spending €1,500 per month on AI but accelerating the work of five people in the process is likely not your biggest cost center. They are potentially your most valuable employee.

Many organizations still focus too much on cost reduction instead of output expansion. They see an AI invoice increase by €500 and immediately try to implement limits. But that same €500 might be responsible for tens of thousands of Euros in additional productivity, faster execution, fewer operational delays, and higher margins.

The danger is that companies start braking their most innovative employees at the exact moment they begin to build a lead. The heaviest AI users are often the first people within an organization to understand how work is fundamentally changing. They don’t use AI as a chatbot, but as infrastructure. They build systems in which AI agents collaborate, tasks are automatically distributed, and output continues continuously without human intervention.

This is where a new form of leverage within companies emerges. No longer just through headcount or management layers, but through employees who use technology to exponentially increase their capacity. Today, one person can deliver output that previously required an entire team. Not because that person works harder, but because AI fundamentally multiplies production capacity.

That is why it might be time to look at AI budgets differently. Software budgets are likely no longer the right model. AI is much more like variable production capacity. The smarter you support the right people, the greater the output generated by your organization.

The question for CFOs should therefore not be: “How do we get those token costs down?”

The real question is: “Which employees are creating 10x more value thanks to AI and how do we ensure they can build even faster?”

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// About the author

Job van den Berg

Mede-oprichter, AI Keynote Spreker & Techondernemer

Tech-ondernemer (1989) met een achtergrond als socioloog (Research Master (MSc) in statistiek en sociologie) en een van de meest gevraagde keynote sprekers over AI en data in Nederland. Als mede-oprichter van Ai.nl, The Automation Group en Proxies leidt hij engineers die agentic AI van prototype naar productie brengen binnen enterprises. Op het podium vertaalt Job die hands-on praktijk naar concrete strategieën. Eerder was Job Chief Data bij o.a. DPG Media en Kantar. Hij is co-auteur van 5 boeken over AI waaronder 'AI Agents' en 'Handboek AI Strategie' en een veelgevraagd expert in de landelijke media.

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