According to a new survey of 300 CFOs and finance leaders, 56% of respondents are prioritizing AI and automation initiatives. To fund these initiatives and improve working capital efficiency, the survey reveals, these CFOs and finance leaders are looking for closer relationships with IT and engineering to identify waste in technology spending and seek more predictable cost structures. With cloud spend accounting for a significant portion of overall IT budgets, organizations are being forced to rethink how efficiently their applications consume cloud resources.
90% of CFOs report being concerned about their company’s level of cloud spend, with one-third of them reporting significant cloud spend increases.
AI Is Increasing Both Cloud Spend and Cloud Governance
AI adoption is increasingly consuming resources in unpredictable ways, complicating spend forecasting. 43% of surveyed organizations cited that AI adoption is adding workload complexity, while a separate “Flexera 2026 State of the Cloud Report” found that “cloud-based AI workloads are surging, causing an increase in wasted cloud spend (29%) for the first time in five years.”
The inherent conflict between the increasing reliance on AI development and productivity tools with increased competition for the very cloud resources (GPUs, data center space, and compute time) that power those tools has CFOs concerned about their organization’s cloud spend — 76% report being moderately, very, or extremely concerned and 69% believe that 10%-30% of their cloud spend is wasted.
AI cost models vary widely, including subscription, units of consumption, and compute time. Add in agentic AI tools that may be making their own API calls, and it becomes increasingly difficult for financial leaders to avoid unexpected charges.
With or without widespread AI adoption, a lack of visibility to cloud usage is a problem for 32% of CFOs. Yet, they are increasingly turning to AI-powered tools to improve cloud spend analysis and forecasting. These tools can help identify where you’re spending the most, but not necessarily how to address underlying technical levers driving inefficiencies.
Cloud Optimization: Lower Costs and Higher Innovation
As CFOs exhaust top-level budget and cultural factors driving increased cloud spend, they’re partnering with their engineering leadership to identify which technical levers are the most effective to unlock broader financial and strategic advantages. Working together, they can track whether cloud environments are overprovisioned, underutilized, or operating with other inefficiencies that reduce profitability. Re-platforming and application modernization efforts can improve efficiencies, but may involve lengthy projects that fail to realize benefits fast enough to keep up with spending.
One surprising answer? Swapping out the Java Virtual Machine (JVM) their development teams are using. This is a technical layer that even many development managers don’t immediately associate with cloud spend, but a high-performing JVM means code runs faster and warms up earlier, improving cloud elasticity and reducing the need to overprovision cloud compute to handle traffic spikes or peak events. Our high-performance Java platform, Azul Prime, minimizes JVM tuning efforts and reduces cloud spend in the first year, resulting in 129% ROI, according to a recent Forrester TEI Study.
Says one of the executives interviewed for the Forrester study:
“Through more efficient utilization of our Java applications, we’ve been able to reduce the number of physical and virtual servers in use, resulting in a 15% to 20% reduction in cloud costs.”
– VP of digital and data platforms at a financial services firm
Learn What CFOs Are Saying
In our new “Cloud Cost Optimization in 2026” survey and report, you’ll get further insights from CFOs and finance leaders on what they’re prioritizing for the next 12 months, which metrics they’re tracking, and which methods they’re using to address runaway cloud spend.
