Cloud Waste: The $22B Problem Nobody Wants to Talk About

Cloud has transformed businesses—accelerating innovation, enabling scale, and unlocking agility across operations. But with all those benefits comes a pricey downside that many avoid discussing: waste. As organizations pour more workloads into the cloud, a substantial fraction of spend is going toward resources that deliver little to no value. If not addressed, cloud waste silently erodes margins, causes unpredictable budgets, and turns cloud TCO into a liability rather than an asset.

You may have seen the headline figure: “$22B wasted.” While exact numbers vary, recent surveys suggest that a large portion of cloud spend—often 20% to 50%—is wasted annually due to inefficiencies, misconfigurations, and idle or underused resources. For example, a 2024 survey by Stacklet found that 78% of organizations estimate between 21% and 50% of their cloud expenditure is wasted. Source These insights show that the cloud waste problem is real, material, and growing—especially with new pressures like AI, multi-cloud complexity, and increasing scale.

Why “$22B” Might Be Conservative—and What It Signals

Trying to attribute a dollar figure like $22B to cloud waste involves a lot of estimation—and many businesses are likely underestimating the true loss. One survey from Stacklet reveals more than half of respondents believe over 40% of cloud spend is waste — meaning the bill for waste across all enterprises is potentially much higher.Source Another report from Harness projects that enterprises alone will waste roughly $44.5 billion in cloud infrastructure costs in 2025 due to underutilized resources and misaligned spending.Source The figure “$22B” might refer to a subset (e.g., infrastructure only, or cloud waste in particular sectors), but even as a midpoint estimate it should serve as a wake-up call: waste is real, and it isn’t going away.

What this signals for businesses is that cloud spend management cannot be an afterthought. As cloud consumption grows and AI usage ramps up, inefficiencies balloon. Features like resource autoscaling, spot/preemptible instances, serverless execution, and shift scheduling become powerful cost levers—but only if actively managed. The fact that so many companies still report losses of tens of thousands of dollars per month due to mistakes like over-provisioning, log/data retention, and mismatched services shows how many opportunities for savings are being overlooked.

The Main Sources of Cloud Waste

To combat waste, you first need to know where it comes from. Based on recent surveys and case studies, these are the common culprits:

• Overprovisioned compute: Instances sized for peak load that rarely ever reach it. Managed VMs, container clusters, or dev/test environments can stay overpowered for long.
  
• Idle or underutilized resources: Storage volumes, databases, or compute nodes that remain active but barely used. Dead snapshots, unattached storage, test environments left running during off-hours.
  
• Poorly optimized configurations: Inefficient database queries, logging configurations that are too verbose, non-optimal VM types, or not using newer, cheaper instance families.
  
• Redundant services: Multiple backups, overlapping workloads, or duplicated SaaS subscriptions. Also, architecture designs that replicate across regions unnecessarily.
  
• Lack of governance & visibility: No clear tagging, lack of budget alerts, or missing dashboards that can show waste. Many orgs report that cost monitoring is reactive rather than proactive.
  

In the Stacklet survey, the most often cited causes included incorrect resource sizing or type (around 49%), outdated instance types, misconfigured networking, and over-retained logs or data.

How AI, Scale & Multi-Cloud Make It Worse

AI workloads are accelerating cloud costs in ways many didn’t anticipate. Training models, especially large ones, consume vast compute and GPU resources. Experimentation environments for AI tend to generate many unused assets—data, storage, temporary compute, etc. Many companies admit they don’t optimize AI-related cloud usage nearly enough. 

Scale amplifies inefficiencies. What costs $500/month wasted in a small environment become millions when scaled across dozens of projects or regions. Multi-cloud and hybrid setups introduce additional cost friction—data transfers between clouds, inconsistent pricing models, and duplicated services. These environments make tracking spend harder and increase the risk that inefficiencies go unnoticed for longer. With cloud spend globally expected to approach or exceed $800 billion in 2024, even a 25% waste rate translates into hundreds of billions of dollars lost annually.Gartner

The Real Cost: Not Just Money, but Opportunity & Risk

Cloud waste isn’t just about paying too much. It has knock-on effects:

• Forecasting and budget overruns: When budgets are based on ideal assumptions rather than actual usage, leadership is often surprised by spikes.
  
• Resource constraints: Spend wasted on non-critical stuff means less budget for innovation—new features, R&D, or scaling services.
  
• Operational complexity: More unused or misused cloud services means more complexity—harder to maintain, harder to secure, more to monitor.
  
• Security & compliance risk: Idle resources, open/unsecured storage, or duplicated data across regions can create security exposures.
  

So while the headline cost ($22B or more) is shocking, the hidden costs—slower product iteration, higher risk, lower margins—may be more damaging in the long-term.

Strategies to Reduce Cloud Waste

Reducing cloud waste isn’t about harsh cuts—it’s about ongoing refinement. Here are proven strategies:

First, establish cost visibility. Use native tools (AWS Cost Explorer, Azure Cost Management + Billing, GCP Billing Reports) and/or third-party FinOps platforms to track real usage, idle resources, and over-provisioning. Include tagging policies to map spend to teams or workloads.

Second, rightsizing compute and storage resources. Switch off dev/test environments out-of-hours, consolidate storage volumes, choose the right instance types, leverage cheaper instance families, or use spot/preemptible instances for non-critical workloads.

Third, optimize configurations and clean up. Remove outdated snapshots, manage log retention, refactor inefficient queries, deprecate legacy services, and apply best practices for network configuration.

Fourth, establish governance and financial accountability. Incorporate FinOps practices, define cost ownership by team or project, set up budget alerts and anomaly detection, and assign cost-saving targets.

Finally, keep monitoring and iterating. Cloud environments evolve: new service releases, pricing changes, usage patterns change. What worked last year may be wasteful now. Institutions that revisit their cloud usage every quarter and adjust based on real data tend to reduce waste significantly over time.

What “$22B” Teaches Us – A Call to Action

The “$22B wasted” stat, even if approximate, serves as a powerful signal: cloud waste is not fringe—it’s wide, expensive, and avoidable. For any organization using cloud infrastructure or platform services, ignoring this problem is no longer viable. The risk isn’t just in overspending—it’s in losing competitive advantage, delaying innovation, and missing financial predictability.

If you haven’t done a cloud waste audit lately, now is the time. Calculate what percentage of your cloud spend is underutilized, what services are overprovisioned, and what configurations or legacy components are costing without delivering value. Set cross-functional goals (engineering + finance + operations) to reduce that waste. With disciplined cloud spend optimization, you can reclaim a big portion of your budget.

Conclusion

Cloud enables businesses to move fast—but speed without control leads to waste. As cloud usage, AI, and multi-cloud environments become more common, the risk (and cost) of waste rises. When you face down the myths and inefficiencies, build systems for visibility, governance, rightsizing, and continuous optimization, cloud can become less of a gamble and more of a strategic lever.

At Transcloud, we help companies identify waste, build FinOps practices, and turn cloud spending into predictable, valuable investment—not just bills you hope you can pay. Let’s debug the $22B problem together.