From complexity to clarity: How Flexera brings visibility to FinOps for AI
AI is scaling across every function, and with it comes messy, unpredictable cloud bills. Pricing is opaque, usage swings, and the CFO wants to know what value shows up on the other side. Gartner expects most enterprises to deploy industry-specific AI agents by 2030, which means spend will grow-and scrutiny will, too. FinOps needs better visibility now.
That's why Flexera One Cloud Cost Optimization (CCO) introduces FinOps for AI: practical capabilities that separate AI costs from everything else, clarify what's driving them, and help teams take action before budgets get blown.
The use case: Bring FinOps cost transparency to AI
AI spend is hard to predict and even harder to explain. The mechanics are different from traditional cloud, so the usual dashboards miss the signal.
- Bursty workloads: Training spikes during iterations; inference depends on users and application behavior. Demand can jump without warning.
- Token-based billing: GenAI services bill per token. Estimating input (prompts) and output (responses) at scale is tough.
- Visibility gaps: AI services get buried inside overall cloud spend. Without job-level tracking and metadata, teams and leaders can't see what's truly driving costs.
- Utilization and commitments: Dynamic usage makes long-term discounts tricky. GPUs may sit idle just to handle peak windows.
The result: growing AI use, surprise invoices, and pressure on FinOps to explain where the money went.
Meeting the need: Actionable visibility for AI cost optimization
FinOps for AI in CCO brings structure to AI spend and enables targeted optimization. The goal is simple: see clearly, decide fast, act with confidence.
- Linked services categorization: Group AI services by workload type (training, inference, processing) to pinpoint optimization opportunities.
- Direct ingestion of custom fields: Bring in your own fields (like AI service and workload type) so reporting reflects your business reality.
- Precision categorization: Separate "AI service" from "workload type" for granular analysis and better decisions.
- Streamlined control: Map services to custom fields through category mapping to simplify expense classification and target improvements.
- AI cost segregation: Isolate AI spend from overall cloud costs with a dedicated "AI Spend" view to track, forecast, and govern.
Business value: From cost control to competitive advantage
Boards and executives want efficiency, differentiation, and proof that AI investments pay off. FinOps leaders need data that connects usage to value-quickly.
- Increase transparency: Fine-grained categories and a clear AI view reveal what's driving cost and where to optimize.
- Clarify value: Separate AI from other cloud costs to enable sharper conversations about ROI and business outcomes.
- Prepare for scale: As AI use cases multiply, the model supports consistent tagging, reporting, and control.
With this foundation, FinOps becomes a trusted partner to product and engineering-funding what works and reducing what doesn't.
Proof in outcomes
Carlsberg: Using Flexera CCO to support digital transformation and rein in cloud growth, the team achieved application and resource-level visibility, multi-cloud cost control, and more than $400,000 in savings in the first year.
Bayer: With Flexera One and CCO, Bayer identified wasteful non-production resources and built processes that deliver $2M in annual savings across a complex hybrid estate.
Analyst and community alignment
Flexera is recognized as a Leader in the 2024 and 2025 Gartner Magic Quadrant for Cloud Financial Management Tools and noted in the Forrester Wave for flexible cost management and ITAM integration. Flexera is a FinOps Foundation Certified Platform and has adopted the FOCUS 1.0 specification-so cost data is normalized and easier to ingest, map, and analyze across cloud and AI.
Learn more about the FinOps Foundation's guidance for AI and the FOCUS standard here: FinOps for AI and FOCUS 1.0.
Why Flexera One stands out for AI-era FinOps
- Unified capabilities: FinOps for data clouds, FinOps for AI, multi-cloud commitment automation, and automated workload optimization for Kubernetes and VMs.
- Extended scope: Integrates IT asset management, SaaS, and sustainability for a broader, connected view of spend.
- Speed and efficiency: Reduce vendor sprawl and drive savings with automation that acts on insights.
Next steps
If AI spend is rising and visibility is lagging, now is the time to act. Bring AI costs into focus, show value to leadership, and fund the work that moves the needle.
Want your leadership team to sharpen AI literacy and ROI thinking in parallel? Explore curated training by role here: AI courses by job.
Ready to discuss how FinOps for AI in CCO can help your organization? Connect with your Flexera team and set up a working session to review your AI spend, categories, and quick-win opportunities.
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