The explosive growth of AI adoption across enterprises is transforming how organizations operate, innovate and compete. But with the AI revolution comes unprecedented cost-management complexity. AI workloads—whether predictive, generative or operational—can mean expense surprises, opaque pricing, and other challenges for FinOps leaders. Since Gartner predicts, by 2030, more than 80% of enterprises will deploy industry-specific AI agents to support critical business objectives, the need for AI-related FinOps has never been greater.
The FinOps Foundation acknowledges this new AI-driven complexity. Their articles on FinOps for AI show how and why new usage metrics like cost-per-token, volatile costs and GPU scarcity require new approaches. We’re ready to help, with a new capability for Flexera One Cloud Cost Optimization (CCO)—FinOps for AI—engineered to help FinOps and cloud teams meet these challenges.
The use case: Bring FinOps cost transparency to AI
Why is visualizing and optimizing AI spend so difficult? AI introduces hurdles that go beyond traditional cloud cost management:
- Bursty workloads: AI training workloads may be highly variable during iterative training; AI inference workloads are tied to user interaction and application requirements. All this means demand can spike unpredictably and lead to unplanned costs if not managed proactively.
- Token-based usage billing: Commonly, GenAI services bill based on tokens—text-processing units. Estimating costs for input tokens (prompts) and generated tokens (responses) can be a considerable challenge.
- Visibility challenges: It’s hard to distinguish AI service spend from overall cloud spend, so opportunities to optimize compute costs and eliminate waste are often missed. Without job-level tracking and custom metadata, linking AI-related spending to specific teams or making it visible on actionable dashboards is difficult.
- Utilization and commitment planning difficulty: Dynamic usage makes it difficult to cover workloads effectively with long-term commitment discounts like reserved instances. GPU resources may be overprovisioned to handle peak demand but sit idle much of the time.
The result: Growing AI adoption can lead to cloud cost sticker shock for FinOps leaders and business stakeholders.
Meeting the need: Actionable visibility for AI cost optimization
The new CCO capability is designed to bring FinOps teams new transparency and control for AI costs. Now they can gain more visibility into AI-related spending through:
- Linked services categorization: Categorizing AI services and linking them to workload types (such as training, inference and processing) make it easier to analyze and optimize costs for specific AI activities.
- Support for custom field name direct ingestion: Now users can ingest custom field names (like AI service and workload type) directly into the CCO pipeline, ensuring accurate and relevant financial reporting.
- Precision categorization: “AI service” and “workload type” are now distinct categories to provide granular visibility and support more fine-grained cost management.
- Streamlined control: Mapping services to custom fields through category mapping, streamlining expense categorization and enabling targeted optimization make management easier for FinOps teams.
- AI cost segregation: Segregating AI-specific costs from overall cloud spend and displaying them in a dedicated “AI Spend” section helps users easily identify, track and control AI expenses.
Business value: From cost control to competitive advantage
Boards of directors and C-suite executives are pushing their organizations for more AI-driven efficiency and differentiation, while at the same time raising questions with their teams about increased cloud spending and value received. The new FinOps for AI capability in CCO gives FinOps leaders the transparency needed to help address executives’ concerns while managing AI-related cloud costs.
- Increase transparency: Fine-grained categorization and cost segregation make it easier to see and manage AI-related costs.
- Provide insights into cloud value: By enabling FinOps teams to segregate AI from other cloud costs, insights are clearer and can better inform value discussions.
- Prepare for new AI use cases: With AI adoption accelerating and use cases proliferating, these capabilities lay a solid foundation for FinOps teams’ need for scale.
With these new capabilities, FinOps teams become trusted partners in AI initiatives, helping business stakeholders and technical leaders prove cloud and AI value while generating savings to fund competitive advantage.
Why Flexera: Proven value, analyst-recognized leadership, FinOps Foundation alignment
Organizations and partners using CCO are seeing significant value—and with new visibility into AI cloud costs, they’re better equipped for the demands of AI-driven innovation.
- Carlsberg, a global leader in the beverage industry, implemented Flexera CCO to speed their digital transformation and rein in rapid cloud spend. Outcomes to date: New application and resource-level visibility, multi-cloud cost control, and over $400,000 in savings within the first year.
- Bayer, a global enterprise with core competencies in life sciences, turned to Flexera One and CCO to optimize costs across a complex hybrid cloud estate. Outcomes to date: Processes to identify wasteful non-production resources are delivering $2M in annual savings.
Flexera’s expertise in cloud cost management and optimization is consistently recognized by leading analysts. In 2024 and 2025, Flexera was named a Leader in the Gartner® Magic Quadrant™ for Cloud Financial Management Tools, and the Forrester Wave™ for Cloud Cost Management and Optimization Solutions spotlighted Flexera’s flexible platform and integration of IT asset management (ITAM) with FinOps.
Flexera is a FinOps Foundation Certified Platform, and Flexera has adopted the FOCUS 1.0 specification. This ensures that cost data is normalized, making it easier for organizations to ingest, map and analyze commitment dimensions across their cloud and AI investments.
Flexera is unique in how the Flexera One platform brings FinOps for data clouds, FinOps for AI, multi‑cloud commitment automation and automated workload optimization for K8s and virtual machines together. The Flexera One platform also supports optimization for extended FinOps Scopes, including ITAM, SaaS and sustainability. This speeds time‑to‑value, reduces vendor sprawl and directly optimizes spending via automation.
Ready to take the next step?
Discover how Flexera CCO and our broader FinOps platform can help you overcome your cloud cost management challenges. Connect with our experts to learn more.
