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VOOZH | about |
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VOOZH | about |
Tokenomics: AI Value with FinOps for AI
AI has become a mainstream technology investment as 98% of FinOps teams now manage AI spend, up from 31% just two years ago. However, managing AI cost is only the beginning—the real question is whether AI investments are creating measurable business value. FinOps helps organizations answer that question by connecting AI spending to strategic outcomes, quantifying returns, and ensuring every AI initiative earns its place in the portfolio.
AI value spans employee productivity, revenue growth, cost efficiency, customer experience, operational resilience, and competitive advantage. Organizations that define clear business drivers, measure progress incrementally from concept through product, and track long-term impact will build sustainable AI value.
The FinOps Framework provides the cross-functional collaboration, data-driven visibility, and governance needed to do this at scale. Community-generated Working Group resources teach FinOps practitioners to evaluate AI investments and govern AI spend.
June 26, 2026
Day 2 of FinOps X 2026 opened with a reminder that while AI won’t replace FinOps, practitioners who master AI will succeed throughout the intelligence era.
June 26, 2026
Day 1 of FinOps X 2026 covered token economics and the rise of AI spend management, and the role FinOps and Tokenomics play in it.
May 7, 2026
Practical AI for FinOps use cases and prompts mapped to Framework capabilities and designed for cost optimization, reporting, budgeting, and policy workflows.
April 23, 2026
A FinOps practitioner's guide to understanding AI tooling costs across the full lifecycle, from training and tuning to inference, orchestration, and operations.
February 4, 2026
Use this Paper to better understand GenAI capacity models (AWS, GCP, Azure) and their impact on FinOps strategies, covering traffic shapes, spillover logic, and hidden costs.
May 7, 2026
Practical AI for FinOps use cases and prompts mapped to Framework capabilities and designed for cost optimization, reporting, budgeting, and policy workflows.
April 23, 2026
A FinOps practitioner's guide to understanding AI tooling costs across the full lifecycle, from training and tuning to inference, orchestration, and operations.
February 4, 2026
Use this Paper to better understand GenAI capacity models (AWS, GCP, Azure) and their impact on FinOps strategies, covering traffic shapes, spillover logic, and hidden costs.
October 3, 2025
This paper explores how to optimize for value and achieve “elastic and efficient” when running AI/ML on Kubernetes. We begin by unpacking what makes these workloads unique, then examine the main scaling challenges through a FinOps lens and finally outline proven patterns and tooling that keep GPU clusters fast without breaking the budget.
August 1, 2025
This Paper dissects how token pricing really works, revealing the hidden costs that can catch even seasoned FinOps professionals by surprise.
June 26, 2026
Day 2 of FinOps X 2026 opened with a reminder that while AI won’t replace FinOps, practitioners who master AI will succeed throughout the intelligence era.
June 26, 2026
Day 1 of FinOps X 2026 covered token economics and the rise of AI spend management, and the role FinOps and Tokenomics play in it.
July 3, 2025
Taiwo Ojetayo and Mike Moone of Workday demonstrate what Workday has learned as it continues to utilize AI services, how it applies FinOps practices to AI-related consumption data, and how this affects unit metrics to inform better business decision making.
July 3, 2025
Paul Guarino and Barghav Tumu of Fidelity Investments dive into the key automation and optimization techniques that make efficient ML possible, including lifecycle shutdown automation, rightsizing strategies, instance type optimizations, and intelligent workload scheduling. A key focus will be on tackling the high costs of services like SageMaker, where compute-heavy workloads can quickly drive up expenses.
July 3, 2025
Rob Martin and Mike Fuller of the FinOps Foundation walk through what FinOps for AI means for practitioners and recommend how to build an AI-focused Scope for your own practice.
FinOps applied to a range of technologies, from public cloud and SaaS to AI, data platforms, and data centers.
Designing modern solutions with value, cost, and performance built in from the start.
Using AI tools to improve FinOps team productivity, automate repetitive tasks, and accelerate decision-making.
Segments of technology-related spending aligned to business constructs–such as products or cost centers
Maximize value from technology investments by enabling informed, timely decisions.
Build a FinOps practice that maximizes technology value, through centralized enablement, distributed execution, and executive alignment.
Technology value is a board-level conversation, connecting technology spend, usage, and adoption to business strategy.
Where and how FinOps intersects with ITFM, ITAM/SAM, ITSM, Platform Engineering, Sustainability, and other disciplines.
FOCUS is the unifying language for technology value and an open specification that normalizes cost and usage data.
