As enterprises increasingly invest in artificial intelligence, the complexities of AI token economics are leading to unprecedented challenges in billing accuracy and financial control. At the FinOps X 2026 conference in San Diego, the focus was on the FOCUS specification, which aims to provide a standardized framework for addressing these issues. Notably, about 68% of organizations spending over $100 million annually are now using FOCUS-formatted data, reflecting a shift toward a common billing language in the industry.
The FOCUS specification, developed by the FinOps Foundation, seeks to standardize data across various technology categories, including public cloud, AI, and SaaS. Shawn Alpay, director of data engineering at FinOps, emphasized the need for consistent data definitions across providers. “The data is not normalized across providers, across technology categories, public cloud, AI, SaaS, etc,” he stated in an interview at the conference. This lack of normalization complicates the financial storytelling necessary for effective budgeting and forecasting, especially as organizations expand their AI capabilities.
With the rollout of FOCUS 1.4, the specification is evolving to cover a broader range of datasets and user personas beyond its initial focus on public cloud environments. This expansion aims to include not just data engineers and FinOps practitioners but also finance, leadership, and procurement teams. Matt Cowsert, principal product manager at FinOps, noted, “FOCUS is also a language that you’re then able to use across your organization.” This widening of the user base highlights the growing recognition of the value FOCUS brings to various stakeholders within enterprises.
Integrating AI token economics into the FOCUS framework presents distinct challenges, particularly in measuring the cost of inference at granular levels, such as per user, per session, and per request. Alpay pointed out that the complexity of this data collection introduces significant data engineering challenges. “When it comes to AI and tokens in that realm, you’re starting to talk about per user, per session, per request, per operation — and the farther down this ladder you go, the larger the cardinality of the data and the harder it is to gather that information,” he explained. This complexity can lead to substantial costs attributed merely to data gathering and processing.
The working group is currently debating whether to develop a new observability dataset or to integrate with existing frameworks like OpenTelemetry. This decision could significantly impact how organizations manage and report their AI-related spending. Alpay acknowledged the need for careful consideration in delivering this information, suggesting that consumers may want the option to choose the granularity of the data they consume.
https://www.youtube.com/watch?v=SjIRu2K2_CI
As AI continues to reshape business operations and create new financial dynamics, the role of the FOCUS specification in establishing a consistent billing framework becomes increasingly critical. Ongoing discussions and developments within the FinOps community reflect a recognition of the complexities involved in AI token economics and the necessity for a unified approach to financial management across diverse technological landscapes.
With the rapid evolution of AI technologies and their financial implications, organizations must stay informed about advances like the FOCUS specification. Adapting to these changes will be essential for achieving effective financial oversight in AI-driven environments.
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