Excessive cloud spending is a pervasive problem in enterprises
We’re burning cash in the cloud, and most companies know it. The data confirms it. VMware surveyed 1,800 senior IT decision-makers. Almost half say at least 25% of their cloud budget is going to waste. A full 31% say they’re wasting more than half.
This spending problem doesn’t stem from one decision. It’s the result of a hundred small ones, resources left running, contracts signed without oversight, teams working in isolation. The challenge is visibility. When departments manage cloud spending in silos, there’s no clear view into what’s actually being used or what should be shut down. Control disappears, and governance becomes fragmented.
There’s opportunity in fixing this. The waste tells us where the system broke. Cost optimization means saving money and increasing agility. When you remove unnecessary cloud services, you reduce technical debt. You open up more room to move faster without dragging inefficiency behind.
Right now, many organizations see the problem but underestimate the scale. The technology exists to control it. The barrier is often managerial will and process. That’s something leaders can change, starting at the top.
Inefficient IT and developer culture directly contributes to uncontrolled cloud spending
It’s not just about tools. It’s about people. More specifically, it’s about what people are rewarded for. Rob Tiffany from IDC put it bluntly, CIOs get applause for launching something new, not for hunting down unused virtual machines. So guess what gets prioritized.
Inside most engineering teams, nobody’s thinking about cloud costs day to day. Developers spin up environments and forget them. Reserve resources that don’t get used. Run test servers 24/7 that nobody touches at night. This isn’t malicious, it’s a lack of awareness and incentive.
Roman Rylko, CTO of Pynest, gave a great example: one of his clients had developer environments running around the clock that were only used during business hours. A simple startup and shutdown schedule saved the company a double-digit percentage. That kind of waste is common, and much of it goes unnoticed because developers aren’t trained to care, and they’re not held accountable.
Culture sets direction. When teams don’t see the financial impact of their actions, they don’t change behavior. If you’re a C-suite leader, that should be a red flag. FinOps tools help, sure. But tools don’t fix culture. Accountability and cost-awareness need to be built into engineering the same way security and performance are. Make teams responsible for what they use. Drive that principle from the top. You’ll see the savings, not just in dollars, but in execution focus.
Underutilization of FinOps tools hampers effective cloud cost management
Most companies already have the systems in place to control cloud spend. The problem is, they’re not using them right. FinOps platforms, designed to track cloud usage, identify waste, and optimize billing, are often deployed with limited access. That makes them weak by design.
Rob Tiffany from IDC made it clear: too many organizations buy FinOps tools, then block them from seeing what they need to see. APIs are restricted. Cloud accounts don’t get connected. The same tools that are supposed to help reduce waste end up working blind.
This is process failure, not a technology one. You can’t tackle cloud overspend if the monitoring layer can’t reach every account and service. And if the tool can’t talk to the platforms you’re using, whether it’s AWS, Azure, or Google Cloud, it won’t surface buried inefficiencies. Deployed correctly, these tools give you the data to act and the confidence to scale across clouds.
For executives, the takeaway should be simple: don’t mistake partial implementation for progress. FinOps must be integrated across the full scope of your cloud environment, including internal APIs, third-party services, and shadow IT layers. If you’re unwilling to expose this data, don’t expect meaningful cost optimization.
Vendor relationships and opaque contract terms exacerbate recurring and hidden cloud costs
Cloud vendors want long-term clients, and they’re good at early lock-in. That’s not a surprise. What is surprising is how many enterprises agree to complex, multi-year contracts without understanding the cost implications. And once it’s signed, the charges become recurring, difficult to track, and easy to overlook.
Matt Kimball from Moor Insights & Strategy pointed out the trap well. Companies sign SaaS deals, Salesforce, Oracle, others, and add modules they never use. These additions then show up as line items year after year. No one questions them. Nobody remembers authorizing them. And over time, those idle services grow into major expenses hidden in your budget.
Rob Tiffany took it further. He said companies often think, “If it’s Microsoft or AWS, it’s safe to sign and forget.” But that mindset creates dependency without control. These deals are optimized for cloud providers’ revenue, not your usage patterns.
C-suite leaders need a tougher stance on cloud contracts. Take a continuous approach. Review them regularly, renegotiate when possible, and audit against actual usage. Look into every detail, modules, user seats, storage tiers, network charges. Make sure you’re only paying for what creates value.
Agentic AI offers a promising solution to overcome resource limitations in cloud cost oversight
CIOs are stretched thin. Their teams are already handling modernization, migrations, cybersecurity, compliance, and more. Adding the burden of tracking every idle virtual machine or orphaned backend service hasn’t been practical, that’s been the excuse for years. But the excuse is losing ground.
Agentic AI changes that. These systems don’t wait for instructions, they act. They can monitor dashboards, scan for duplicated resources, identify unused services, and present cost-saving opportunities across multiple cloud environments. Not hypothetically. In real time.
Rob Tiffany from IDC is clear on this: AI agents can now take over the repetitive, time-consuming task of tracking hidden cloud waste, tasks that IT doesn’t have time or people for. Once those eyes and ears are in place, there’s no good reason not to act on the data, and executives can finally push operations teams to reduce inefficiencies without increasing headcount.
What matters here is how leadership responds. If you don’t adopt this tech, you’re choosing to stay blind to known sources of waste. And if you do adopt it but don’t update your processes or incentives, the AI insights won’t get implemented. This isn’t just automation, it’s an operational advantage. Decisions around budget allocation, hiring, and even contracting can now be based on deeper, faster intelligence.
Broader definitions of “cloud waste” reveal even greater inefficiencies than initially reported
Cloud waste isn’t just unused storage or idle compute. That’s the surface layer. Real inefficiency runs deeper, and it’s showing up in countless places leaders typically overlook.
Mark Troller, CIO at Tangoe, emphasized that most waste reports don’t capture the full picture. If you only count infrastructure sitting idle, 30% to 50% waste might feel exaggerated. But if you include duplicate SaaS tool subscriptions, shadow IT activity, and expensive workloads poorly structured for cloud architecture, that number is arguably low.
The actual problem is fragmented accountability. No one owns the total cost picture. Engineering teams aren’t checking licenses. Finance doesn’t see the performance drags from poor workload design. Procurement sometimes lacks visibility into usage beyond the initial contract. This creates a gap where inefficiencies thrive.
Executives need to rethink what they call “waste.” What’s indirect doesn’t mean it’s small. Network costs can balloon from one bad workload architecture. A single overprovisioned SaaS license can snowball into hundreds of unattended users. These costs get normalized when they should be questioned.
If you define cloud waste narrowly, you’ll miss most of it. A broader, data-driven, and continuous audit model uncovers more, and gives your organization the clarity to act decisively. Start there, and the path to optimization opens up.
Key highlights
- Cloud waste is systemic and underestimated: Nearly one-third of IT leaders report wasting over 50% of their cloud spend, largely due to organizational silos and lack of visibility. Executives should drive cross-functional governance to reduce this spend.
- Culture perpetuates overspending: CIOs and developers often aren’t incentivized to track cloud inefficiencies. Leadership should tie performance metrics to cost accountability to shift priorities toward sustainable usage.
- FinOps is underpowered without full integration: Many companies deploy FinOps tools but limit their access, weakening their effectiveness. Leaders should ensure these platforms have full visibility across all cloud services and APIs to unlock their value.
- Vendor lock-in and contract complacency inflate costs: Enterprises frequently overlook recurring charges in long-term cloud and SaaS contracts. Executives must adopt an ongoing contract review process to align actual usage with billing.
- Agentic AI enables scale without added headcount: AI agents can handle routine cloud monitoring tasks previously ignored due to staffing constraints. Leaders should deploy these tools to uncover waste and free up teams for higher-value work.
- Narrow waste definitions miss broader inefficiencies: Costs from duplicate licenses, shadow IT, and poor architecture often exceed idle infrastructure waste. Executives should define cloud waste holistically and implement continuous audits for full control.
