2026 Wasabi Global Cloud Storage Index: Costs, AI Infrastructure Spending, and Cyber Resilience Trends

For the fourth year in a row, the Wasabi Global Cloud Storage Index has delivered a compelling picture on the state of the cloud storage market, offering unique insight into how cloud storage intersects with AI initiatives and cybersecurity risk. Commissioned by Wasabi Technologies and conducted by Vanson Bourne, the Cloud Storage Index sheds light on shifting budget priorities, persistent fee challenges, emerging risks, and where organizations truly stand on delivering value from their cloud investments.

This year, we surveyed 1,700 IT decision-makers worldwide. The findings reveal what’s top of mind for organizations as they navigate key cloud storage implementations and challenges in 2026. AI is dominating headlines, and this year we explored related market requirements in depth.

At the same time, a more complex story is unfolding across organizational budgets and growing concern around protecting vital data. Below are the most important takeaways that cloud strategists, infrastructure leaders, and CIOs should be aware of.

Cloud storage economics: Costs, budgets, and buying behavior

Before diving into popular topics like AI and cloud infrastructure, it's important to understand the foundational ways buyers are impacted in today’s market.

Fee complexity is still driving budget overruns

Even with years of cloud infrastructure experience, many organizations are still grappling with complex  fee structures that drastically increase their cloud storage costs. For example, the Cloud Storage Index found that roughly half of public cloud storage spending goes toward cloud storage fees, not the storage capacity itself. This trend has remained consistent over the previous three years of results.

It’s no surprise these fees affect budgets. Nearly half of survey respondents reported exceeding their cloud storage budgets over the past year, often citing common fee-triggering actions like API calls, retrievals, and other data operations. In fact, 91% of respondents cited at least one fee-related reason as a contributing factor to their budget excess.

Together, these findings suggest that fee complexity continues to undermine cloud storage cost predictability and budgeting. Cost overruns aren’t just about the volume of data stored, but also the behaviors and actions associated with that data.

The bottom line: fee complexity remains a persistent pain point for IT and finance teams trying to forecast and optimize their cloud storage spend.

AI budgets are rising and infrastructure is the priority

Despite this pressure from fees and budget overages, organizations aren’t slowing investments in AI or infrastructure improvements. The Cloud Storage Index reported that 60% of respondents plan to increase their AI infrastructure investment this year, with only 3% saying they will decrease spending.

We also learned where most of that budget is going. The majority is being allocated to data, compute, and storage. To be exact, the Cloud Storage Index revealed that 66% of AI budgets are currently allocated to data storage and infrastructure, with the remaining 33% going toward software or SaaS solutions.

This reinforces a key theme in today’s AI market adoption cycle: success isn’t only about deploying intelligent applications. It’s about enabling them with the foundations of storage, compute, and data infrastructure, which is why organizations are channeling most of their dollars to these areas.

AI ROI is lagging investment, for now

When it comes to ROI, it’s important to understand how organizations see their AI initiatives performing today and how they expect that trajectory to change over time. This year’s survey data shows a clear gap between spending and value realized.

While expectations for AI projects are high, only about 32% of organizations report a positive return on AI initiatives. This helps illustrate where many organizations are in the AI adoption cycle: heavy investment is underway, but measurable value is still catching up.

Despite this, organizations remain optimistic, with more than half expecting a positive ROI on their AI projects in the next 12 months. For that future to be realized, organizations will need to understand why the current gap between investment and return exists and what changes are required to close it.

Perhaps most importantly, AI decision makers should be asking how their cloud infrastructure provider(s) can help optimize data and storage-related costs and predictability.

The strategic consensus is clear: infrastructure spending to support AI is no longer optional. Storage and compute are the building blocks for successful AI deployment, but budgets aren’t unlimited, and fee complexity remains a constraint. Without an optimized foundation of storage and compute resources, organizations are unlikely to reach the ROI they expect with AI initiatives.

Hybrid is the default for AI workflows

This year we also asked respondents about how they’re deploying infrastructure to support AI. For many enterprises, cloud storage isn’t exclusively public, private, on-prem, or off-prem; it's a hybrid approach. According to the Cloud Storage Index, 64% of organizations are deploying hybrid storage architectures for AI workflows.

When it comes to AI workflows, respondents indicate that public cloud is most commonly used for data ingest and retrieval, as well as model archiving and retention. These deployment patterns reinforce a deliberate strategy: align each stage of the AI pipeline with the infrastructure and storage environments that best support performance, control, and cost.

Dark data: Cost without value

This year’s survey highlights persistent challenges around data quality and management for AI initiatives, particularly the cost of storage, data access, and migration. Those challenges connect to a commonly overlooked issue: dark data.

Dark data is information that enterprises collect or possess but never analyze to create value. It often sits in storage, unused for decision-making, customer value, or other strategic purposes.

This year, our survey found that 72% of organizations estimate that at least a quarter of their storage capacity is dark data. That statistic matters because dark data represents infrastructure and storage costs without any added business value. Organizations pay to retain, manage, and protect this data without any contribution to potential business outcomes.

Dark data can also become an AI performance issue. Unmanaged or inconsistent data can degrade model performance within the AI pipeline and undermine output, amplifying the ROI challenges many enterprises face.

Many organizations recognize this challenge. In fact, 91% of respondents state it’s a priority to better analyze and operationalize dark data. This is also why free and uncapped data access matters: when organizations face obstacles such as complex API and access fees, or service throttling limitations, it becomes harder to evaluate, rationalize, and put stored data to work.

The resilience gap: Security starts at the storage layer

Data security and compliance remain persistent challenges in public cloud environments. The Cloud Storage Index reminds us that organizations are in a constant battle with bad actors to prevent data loss and downtime.

Among the 1,700 respondents we surveyed this year, 44% reported experiencing a cyber attack that led to the loss of access to cloud data. In today’s market, loss of access doesn’t just disrupt IT operations; it halts overall business operations and revenue generation.

Given the prevalence of cyber attacks and the escalating costs of downtime, it’s notable that 41% of organizations believe their public cloud vendor does not provide sufficient tools to protect their data against cyber threats. One of the key findings from this year’s study is that organizations need stronger cloud data protection built into their storage systems.

Baseline features like replication, data durability, and immutability remain critical. This year, 63% of respondents also reported using the object lock feature as part of their security strategy.

At the same time, the Cloud Storage Index suggests many teams don’t think baseline controls are enough on their own. Modern threats increasingly require layered safeguards built into the storage environment; protections that reduce the chance a single compromised credential or workflow gap turns into a major outage.

That’s the principle behind capabilities like Wasabi’s Multi-User Authorization (MUA) and Covert Copy, which are intended to add safeguards beyond standard immutability and replication. Combined with predictable pricing, these features are built to help organizations strengthen resilience without introducing unnecessary complexity, or cost.

Key takeaways

The Cloud Storage Index highlights a widening gap between what organizations expect from cloud storage and what they’re currently experiencing. Fees continue to erode predictability. AI budgets are rising faster than realized returns. And the bar for cyber resilience keeps moving upward.

To close that gap, leaders should focus on three priorities:

• Simplify and forecast costs. Reduce exposure to usage-based fees that make storage spend hard to model.

• Operationalize data readiness. Treat dark data as a cost-and-risk multiplier, and invest in governance and usability, not just compute.

• Build resilience into the storage layer. Make immutability a baseline, then add safeguards that limit the impact of compromised access and protect recovery.

These global findings are just a starting point. We’ll continue analyzing the data to provide deeper insights into the cloud storage market by geography, industry, use case, and more.

Cloud is still the default destination for growth. But in 2026, the organizations that succeed will be the ones that build cloud foundations designed for predictability, performance, and recovery under pressure.