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The business case for FinOps to control cloud spending
59% of enterprises have built FinOps teams to advise on, manage or execute cloud cost optimization strategies. So, the question is, what are you waiting for?
Cloud spending continues to grow, and enterprises must optimize their cost management strategy -- especially with the wide adoption of AI initiatives.
According to Flexera's 2025 State of the Cloud report, 83% of respondents said managing cloud spend is a top cloud challenge. FinOps is one of the most effective ways to meet this challenge. It is so effective that 59% of Flexera's survey respondents have built FinOps teams to advise on, manage or execute cloud cost optimization strategies.
FinOps provides a collaborative framework for optimizing cloud spending, aligning costs with business value, and addressing the unique challenges of AI and hybrid environments.
The cloud spending problem
Cloud services were initially touted as a massive cost-saving tool, promising organizations that they could eliminate expensive Capex and replace it with lower Opex. Reductions in IT staff sizes and skills were also predicted.
Today's reality looks far different, with shortages of skilled cloud administrators and increasingly complex environments. Many organizations have opted to repatriate data and services to on-premises data centers to meet performance, security and cost requirements.
Most organizations continue to rely on extensive cloud service and app deployments, and the risks involved with poor governance of these environments are high. Some challenges your organization may face if you fail to implement an effective cost management strategy include:
- Budget overruns affect profitability.
- Uncontrolled cloud sprawl leads to cost, security, and compliance issues.
- Inefficient resource usage impedes innovation.
- Lack of financial accountability across teams.
These are clearly significant concerns that lead to measurable financial and resource waste.
The business case for FinOps
FinOps is a framework and set of practices designed to maximize business value by optimizing cloud spending. It relies on collaboration between finance, engineering and business teams to promote financial accountability for cloud costs. It emphasizes data-driven decisions around cloud service speed, price and quality.
The goals of most FinOps deployments include:
- Accelerating innovation.
- Improved visibility and forecasting.
- Aligning spend with business value.
- Optimize cloud services and eliminate waste.
- Financial accountability to mitigate budget overruns.
FinOps is ideal for those organizations looking to maximize operational efficiency between departments while improving cloud services and managing costs. Existing commercial and open source FinOps tools and services are mature, support multi-cloud environments and are designed with cost management in mind.
Use standard ROI formulas to calculate cost optimization; however, plan for a phased approach to savings, as it will take time for FinOps to have an impact. Be sure to measure success and value in both quantitative and qualitative terms.
Manage AI spend with FinOps
AI is now the fastest-growing segment of cloud spend, and poorly managed GPU workloads and overprovisioning exacerbate wasted resources and their associated costs. Only 51% of organizations can confidently evaluate AI ROI, according to "The State of AI Costs In 2025" by CloudZero.
AI workloads are extremely expensive, with the average monthly spend on AI at $85,521, according to CloudZero. They also incur costs for storage and data movement. These workloads are substantially more costly than standard cloud app resource consumption, so optimization is essential.
FinOps provides control mechanisms for AI at scale, ensuring it delivers actual business value. AI's unique requirements necessitate the following FinOps practices:
- Determine a governance mechanism that supports the unique issues surrounding AI and machine learning deployments.
- Optimize AI workloads and training costs by identifying underutilized GPUs and consolidating workloads.
- Optimize scheduling and orchestration to maximize investment and minimize idle GPU time.
- Create GPU budgets, alerts and cost reporting to manage AI spend.
Relating resource costs, model performance and business value is critical to managing AI-related costs. AI exemplifies the importance of FinOps principles.
FinOps for hybrid and multi-cloud
Hybrid cloud and multi-cloud deployments present their own unique challenges. Your organization will need to find ways of normalizing monitoring and metrics data across different providers. Governance tools must also support multi-cloud environments with competing services.
Plenty of continuous improvement opportunities for your FinOps platform exist, including:
- Improving KPIs around visibility, optimization and governance.
- Educating cloud administrators and engineers on the importance of cost-aware behaviors and practices.
Damon Garn owns Cogspinner Coaction and provides freelance IT writing and editing services. He has written multiple CompTIA study guides, including the Linux+, Cloud Essentials+ and Server+ guides, and contributes extensively to Informa TechTarget, The New Stack and CompTIA Blogs.
