Linux Foundation Launches the Tokenomics Foundation to Define the Economics and ROI of AI Value

New Foundation brings together 30 industry leaders to develop open frameworks, specifications and best practices for measuring the cost, value and return on AI spend

Summary

• The Linux Foundation has launched the Tokenomics Foundation to establish open, vendor-neutral industry standards, benchmarks and best practices for the economics of AI.
• Backed by 30 initial members, the foundation will address the challenges of tracking the ROI of AI, replacing fragmented vendor pricing with a standard way to measure the true total cost of ownership.
• The roadmap will aim to create shared language and measurement: defining tokenomics and the value metrics for AI ROI, creating AI Value Frameworks to measure business impact, vendor-neutral models for the full cost of AI, establishing standard methods for measuring cost to serve and the value AI actually returns, delivering token cost telemetry in the FOCUS specification and building the education and certification practitioners need.

SAN FRANCISCO, August 4, 2026 — The Linux Foundation, the nonprofit organization enabling mass innovation through open source, today launched the Tokenomics Foundation to focus on establishing open industry standards, benchmarks and best practices for the economics of AI. At the time of launch the founding member organizations include Accenture, BNY, Broadcom, Calero, Cast.ai, DoiT, Finout, Flexera, GoDaddy, Greenpixie, Hitachi, IBM, JPMorganChase, Kion, Lenovo, Nebius, North Cloud, Oracle, Pay-i, Pointfive, Revenium, SAP, ServiceNow, SHI, Stacklet, Vantage, WWT, XOsphere and Yarken.

The Tokenomics Foundation’s creation coincides with accelerating enterprise urgency around AI spend,with token consumption forecast to increase 24-fold by 2030, Goldman Sachs predicts. Organizations face a widening gap between what they spend on AI and their ability to measure, manage and monetize their AI investments.

The Tokenomics Foundation aims to help organizations better meet the challenge of AI value, right at the moment that the global 2000 are evaluating the ROI they are receiving from AI investments amidst historic investment into infrastructure and AI services.

AI Token Economics, or AI Tokenomics, is the emerging practice of managing the production, consumption and value of AI to generate business outcomes. It gives practitioners a map for answering two challenging questions: what does AI actually cost, and what is the value of intelligence?

Tokenomics looks at the entire supply chain of how energy and capital are used to create tokens and AI services at the hardware layer, the consumption of AI services (and adjacent AI costs) to drive intelligence and the outcomes and impacts to business models that the AI drives.

Tokenomics, as the industry is defining it, acknowledges that much of the cost of AI is not in the tokens themselves. There are a wide range of adjacent costs from compute to storage to database to cache and even, human labor in the form of engineers. But tokens are a consistent atomic unit of usage driving various costs. Tokens cover the entire spread of AI costs.

The inaugural Governing Board convened on July 30, and soon after will be the formation and meeting of the Technical Steering Committee, which aligns on key challenge areas for working groups to build best practice materials. The Tokenomics Foundation roadmap includes initial pieces like:

• Definitions. Publish what tokenomics is, and define token value/density, including input, output, reasoning, and cache.
• A reference model for the full cost of AI, not just tokens. Shared terms and the complete component picture, so the token line is understood as one part of the bill rather than the whole of it.
• Cost to serve. A standard method for measuring the whole bill of materials, expressed as cost per call rather than cost per token, so the number maps to work actually performed.
• Value measurement. A framework for relating AI spend to outcomes, starting with the share of work completed without human involvement, measured against what the process costs today.
• Education and certification. A foundational course and credential, so practitioners and the teams around them can apply all of the above.
• Projects like the Big-T Framework: provides a methodology for classifying the token and related AI cost complexity of workloads ahead of model routing activities between the most cost effective frontier or open source models.
• Token Cost Telemetry: improved AI cost reporting schemas in FOCUS v1.5 and beyond (FinOps Open Cost and Usage Specification) to better understand AI TCO
• AI Value Frameworks: the Foundation is laying out a roadmap for showing ROI from the TCO (Total Cost of Ownership) of AI, as well as how Tokenomics impacts business models, COGS and labor planning.

Linux Foundation Quotes

"Open source proved that shared foundations beat closed ones, and open weight models are now extending that lesson to AI itself," said Jim Zemlin, Executive Director of the Linux Foundation. "But an open AI ecosystem needs more than open models; it needs open economics. Tokens have become the commercial expression of the entire AI economy, yet there is no shared way to connect AI spending to value. The Tokenomics Foundation gives the consumers and suppliers of AI a common, vendor neutral place to build those standards in the open, the same way this community has done for software and for cloud economics."

"Businesses are reinventing how they deliver value with AI faster than they can measure it," said J.R. Storment, Executive Director of the Tokenomics Foundation. "Every model release changes the math on cost, consumption, and ROI, and tokens are only the visible tip. The real total cost of AI spans compute, storage, data, and the people who build with it. Every CEO is being asked to show returns on all of that without a shared way to count it. That is why this Foundation exists and is working together on pre-competitive frameworks, benchmarks, and specifications, built in the open, so the entire global economy can accelerate value from AI rather than just account for the spend."

How the Foundation Will Work

The Tokenomics Foundation will operate a dedicated Governing Board, Technical Steering Committee, and IP-managed member working groups to develop vendor-neutral specifications, benchmarks and best practices.

The Tokenomics Foundation operates as part of the technology value umbrella within the Linux Foundation, which serves a global community of more than 120,000. The technology value Foundations share community events such as Tokenomicon + FinOps X, San Diego June 7-10 2027, and operational resources while maintaining separate governance. They will also support FOCUS, the open billing data specification that provides the substrate for normalizing cost and usage data across providers.

Supporting Quotes

"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. 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."

— Mike Eisenstein, Managing Director, Accenture

“As organizations invest more heavily in AI, transparent and consistent approaches to measuring total cost of ownership and business value will become increasingly important. BNY looks forward to collaborating with the Tokenomics Foundation and other members to help advance standards, shared language, and practical benchmarks for AI economics.”

— Leigh-Ann Russell, CIO and Global Head of Engineering, BNY

"Every major technology wave has a similar pattern: many organizations spend aggressively on innovation with no clear mechanisms to capture value. With Agentic AI, the pattern repeats, albeit at an unprecedented speed and burn rate. The core issue isn't the technology alone; it’s that spending continues to be disconnected from business priorities. Misalignment here can be extremely costly, and it's that discipline Tokenomics is setting out to build. Broadcom is proud to help found an effort that brings the industry together to solve it — starting with Token Value, where we're eager to show how Broadcom’s ValueOps AI Tokenomics can help organizations define and measure their AI investments."

— Sreenivasan "Raj" Rajagopal, Head of ValueOps for AI & Infrastructure, Broadcom R&D Software

“Enterprises are under pressure to show ROI on tokens, but almost none can say what a token costs to produce. Our research puts enterprise GPU utilization at 5%, so most of a token's cost is idle hardware. The return shows up at the business outcome, and almost no one measures it. The industry is standardizing the meter in the middle and ignoring both ends. Cast AI joined the Tokenomics Foundation to help measure both.”

— Laurent Gil, Co-Founder and President, Cast AI

"Every organization running AI is now asking the same question they once asked about cloud: What is this actually costing me, and what am I getting for it? Tokenomics is the discipline that answers it. FinOps gave us a shared language for cloud spend, and the Tokenomics Foundation does the same for tokens, models, and GPU cycles. DoiT is proud to be a founding member, and I'm honored to help steer this work as a member of the Governing Board."
— Amit Kinha, Field CTO, DoiT

"Gartner forecasts worldwide AI spending will grow 47% this year alone — the fastest-moving line item in enterprise IT, and one most finance teams still can't reliably forecast. That's not a maturity problem, it's a measurement problem. Most technology spend has matured around stable, predictable units — a license, a seat, a compute-hour. Token-based AI pricing has no such stability, and no equivalent billing standard yet. That's the gap a neutral standard needs to close, and why Flexera supports the Tokenomics Foundation."

— Jay Litkey, Senior Vice President of Cloud and FinOps, Flexera

"Executives are scrambling for the productivity benefits of AI while struggling to reconcile the cost, energy and carbon implications. Tokenomics reconciles this and safeguards long-term growth with a sustainable AI strategy. The Tokenomics Foundation will play a hugely important role in establishing best practices and Greenpixie is ecstatic to apply its expertise to this new frontier.”

— John Ridd, CEO and Co-Founder, Greenpixie

"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. 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."

— Bill Lobig, Vice President of IBM Apptio, IBM

"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 optimize 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 realizes value.”

— Arvind Joshi, COO and CFO of Global Technology, JPMorganChase

“For organizations 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 organizations gain deeper insights into balancing their spend and return on investment in AI, which will help scale and drive success for their AI initiatives.”

— Nathan Thomas, Senior Vice President of Product Management, Oracle

"AI has moved from experiment to infrastructure, and the industry is only beginning to build the discipline to account for what it consumes. The Tokenomics Foundation gives us a shared, open place to define how token spend should be measured and managed, so that efficiency becomes a standard every organization can reach rather than an advantage held by a few. PointFive is proud to be a founding member, and to help build toward a world where no compute is wasted."

— Alon Arvatz, CEO and co-founder, PointFive

"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."

— Nishant Gupta, Chief Availability Officer, Salesforce

"For more than fifty years, SAP has helped enterprises manage the resources their business runs on. Tokens are the latest. With the Autonomous Enterprise, we are embedding hundreds of AI agents into the business processes that companies depend on every day. These agents need clear economic models so customers can understand, manage, and scale their use with confidence. That is why AI economics matters now. The industry needs a neutral forum where enterprises, model providers, and cloud companies can agree on how AI is measured, attributed, and valued. The Tokenomics Foundation provides that forum, and SAP is proud to join as a founding member, building on our contributions to the Linux Foundation and the FinOps Foundation.”

— Jonathan von Rueden, Chief AI Officer, SAP SE

"Managing cost and performance is top of mind for every organization 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.”

— Dinesh Sonawane, Vice President, Technology Business Management and FinOps, ServiceNow

"As organizations move from experimenting with AI to operating it at scale, the ability to understand how token consumption drives cost, efficiency, and business value is becoming critical. As an active board member, SHI is committed to helping shape the industry standards, frameworks, and best practices organizations need to manage technology and AI investments with confidence. Joining the Tokenomics Foundation strengthens our ability to help customers turn AI adoption into measurable business outcomes while contributing to the evolution of this rapidly emerging discipline."

— Shane Cronin, Head of FinOps & ITAM Services, SHI

About the Tokenomics Foundation

The Tokenomics Foundation is a vendor-neutral foundation hosted by the Linux Foundation, focused on establishing open industry standards, benchmarks, and best practices for the economics of AI. Operating in close partnership with the FinOps Foundation, it brings together large token consumers with the AI supply chain to build the primitives of tokenomics across token production, consumption, and monetization. The Foundation develops shared language, frameworks, benchmarks, and community-led guidance that help organizations move from experimental AI adoption to sustainable AI operations. Learn more at tokeneconomics.com.

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