The Linux Foundation, the nonprofit organisation enabling mass innovation through open source, announced in early June the intent to launch the Tokenomics Foundation, a new foundation that will focus on establishing open industry standards, benchmarks, and best practices for the economics of AI infrastructure.
The Tokenomics Foundation will operate in close partnership with the FinOps Foundation, extending the discipline of variable technology spend into the era of token-based AI.
“As enterprises move generative and agentic AI workloads from pilot to production, tokens have become the new unit of technology spend,” said Jim Zemlin, CEO of the Linux Foundation.
“Measuring and benchmarking token efficiency across different models and vendors is critical to how organisations make business decisions, but until now, there was no neutral home to develop the standards needed to measure token economics transparently across the entire supply chain. The Tokenomics Foundation provides that neutral home, ensuring these standards remain open and community-driven.”
While per-token costs fell heavily during 2023-2025 they have levelled off – and new model token prices are rising, making AI the largest and fastest-growing line item on enterprise technology budgets. Research from Goldman Sachs shows global token usage is to multiply 24x between 2026 and 2030 to 120 quadrillion tokens per month.
Industry analysts now forecast more than US$1 T in AI infrastructure investment through 2027, the largest concentrated capital buildout in the history of computing, with the inference market alone projected to expand from approximately US$106 B in 2025 to US$255 B by 2030.
"Token costs and efficiency have become a CEO-level concern, not an engineering footnote," said JR Storment, Executive Director of the FinOps Foundation.
"But naming the problem isn't solving it. The Tokenomics Foundation gives the industry a neutral home to define the standards, the specifications, and the discipline that will determine how much companies benefit from the inference era. In the same way FinOps created a shared discipline for cloud spend, Tokenomics will do it specifically for AI and related token costs."
The Foundation will serve both sides of the AI economy: the buyer side, made up of enterprises operating at scale that need transparent, vendor-neutral standards for the economics of AI token consumption, and the supplier side, including frontier model providers, neoclouds, and the broader token factory supply chain.
The Tokenomics Foundation Governing Board will help set industry direction and deploy funds to support the project. A Technical Committee will develop open specifications, benchmarks, and frameworks, and the Foundation will jointly fund and support the FOCUS (focus.finops.org) specification’s expansion into token-based spending models. The FinOps Open Cost and Usage Specification (FOCUS) is an open technical specification for technology billing data that defines clear requirements for vendors to produce uniform billing datasets.
Organisations who have expressed initial support for the Tokenomics Foundation include Accenture, Booking.com, Flexera, Google Cloud, IBM, JPMorganChase, KPMG, Microsoft, Oracle, Salesforce, SAP and ServiceNow.
"We work with thousands of enterprises reinventing themselves around AI, and the hardest conversation is no longer whether to adopt it but how to prove the return. Token spend is climbing fast and the discipline to govern it has not kept pace," stressed Mike Eisenstein, MD, Accenture.
"When the bill arrives, companies face a tough choice between pouring more money in, or having to pull back and risk slowing innovation. Open, vendor-neutral standards for token economics give our clients a common language to manage that spend and quantify the investment and its returns. That is the gap the Tokenomics Foundation fills, and we are excited to help build it."
Noted Chris Reed, Senior Director IT Finance, Booking.com: "We serve travellers at enormous scale, and generative AI now touches everything from our Trip Planner to the agentic tools handling millions of customer and partner conversations. At that volume, the economics of every token matter, and small differences in efficiency compound into very large numbers.
"We need transparent, comparable ways to measure token cost and performance across models and providers so we can keep delivering value to travellers sustainably. The Tokenomics Foundation gives the industry the neutral standards to do that, and we are proud to support it."
“Our 2026 State of the Cloud research found cloud waste rising for the first time in five years, stemming in part by the surge of AI workloads. The real challenge for organisations is no longer just adoption, it’s understanding spend and controlling AI costs to make it sustainable to run at scale.
"While teams are getting better at cloud financial management, token-based pricing behaves differently, and most still lack the benchmarks to know whether they are paying a fair price for the value they receive. A neutral, community-built standard is essential to give buyers a true picture, and that is why Flexera supports the Tokenomics Foundation,” shared Jay Litkey, Senior VP of Cloud and FinOps, Flexera.
"As tokens become the common currency of AI, enterprises need better ways to measure and manage their value, efficiency and cost across an increasingly complex ecosystem of models and platforms. As buyers choose among a growing range of models and deployment options, they need open, trusted standards to compare cost and efficiency across all of them," observed Bill Lobig, VP of IBM Apptio, IBM.
"No single provider should define those benchmarks. That is why IBM supports the Tokenomics Foundation and the move toward a neutral, community-owned foundation for this work."
"The rate of change in AI consumption is unlike anything we have managed before, and the timing for this foundation is exactly right. Tokenomics is not just about cost. It’s about establishing a consistent framework to evaluate and optimise across model selection, use case patterns, architectural choices, and value outcomes. Getting that discipline in place early will be important to how effectively the industry scales AI and realises value,” commented Arvind Joshi, COO and CFO of Global Technology, JPMorganChase.
“For organisations to make the investments in AI that will drive business growth, they first need clear financial controls in place. The Tokenomics Foundation is designed to help organisations gain deeper insights into balancing their spend and return on investment in AI, which will help scale and drive success for their AI initiatives,” said Nathan Thomas, Senior VP of Product Management, Oracle.
"Token economics is fundamentally more abstract and more opaque than anything we've managed at this scale before. Input versus output tokens, cached versus non-cached, pricing structures that don't behave like compute or storage. It requires a different operational muscle than the one the industry built for cloud, and that muscle should evolve through broad experimentation across the industry, with the best ideas and practices contributed back so we can collectively establish durable standards around it," stated Nishant Gupta, Chief Availability Officer, Salesforce.
"Managing cost and performance is top of mind for every organisation scaling AI today. ServiceNow lives this from two angles: governing and controlling AI at scale while managing costs internally, and building solutions that solve this problem for our customers. That dual perspective makes clear why the Tokenomics Foundation matters. The industry needs a central place to develop the standards and framework that turn AI spend into a strategic, accountable investment.” shared Dinesh Sonawane, VP, Technology Business Management and FinOps, ServiceNow.
The announcement was followed by FinOps X, where the FinOps Foundation launched the FinOps Certified: Technology Value certification. The new certification covers the application of FinOps across key technology categories, like public cloud, software-as-a-service (SaaS), data cloud platforms, and data centres. To become a FinOps Professional, practitioners can now start with either FinOps Certified Practitioner or Engineer, and then become eligible for the Pro Certification by completing the FOCUS Analyst, AI Value, and Technology Value certifications.
The FOCUS Steering Committee ratified the FOCUS version 1.4 specification on June 4, 2026. This is the first FOCUS release that lets FinOps teams interface with accounts payable and finance work from the same billing facts, noted Shawn Alpay, Chair of the FOCUS working group at the FinOps Foundation, and Matt Cowsert, Principal Product Manager, at the FinOps Foundation in a blog post. The authors explained that the updated standard helps to "shorten the monthly close cycle and eliminate the manual stitching that previously sat between AP, finance, and FinOps tooling". AP stands for accounts payable.
"With the release of FOCUS 1.4, the specification evolves beyond basic cloud consumption, taking a major step forward in our ongoing journey to tell the broader technology value story. It builds a critical bridge to finance, introducing the Invoice Detail dataset so FinOps and accounts payable teams can tie usage directly to the physical bill. It exposes the anatomy of the deal by expanding the Contract Commitment dataset and adding eligibility tracking to reveal what was coverable.
"Crucially, 1.4 establishes rigorous standards of data integrity, wrapping the new Billing Period dataset with clear rules for corrections, data delivery, and completeness to build trust in FOCUS as a system of record. Together, these updates lay the vital groundwork for FOCUS 1.5, which will bring unit and token economics into view by introducing the Price Sheet and tracking inference value at the AI frontier."
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