The State of the Cloud 2026: How Organizations are Driving Real Value in Today's Dynamic Landscape

Jay Litkey
Flexera

The cloud landscape has undergone a drastic change in the last year with AI adoption shifting from being experimental into core business operations. As this shift continues, organizations are redefining how they measure success. It is measured less by infrastructure decisions or cost savings alone and more by the overarching business value and outcomes that cloud and AI investments deliver. Amidst the ever-changing environment, the data shows cloud strategies are directly influencing a company's competitiveness.

The 2026 Flexera State of the Cloud report highlights leaders' growing focus on fine tuning their cloud initiatives. To wrangle spend and governance, the report found that more and more organizations are applying mature FinOps practices, with 63% having established FinOps teams and 71% now operating a Cloud Center of Excellence (CCOE). As cloud adoption matures, organizations are moving beyond cost control to delivering measurable, governed business value.

Here's how forward-thinking leaders are upleveling their cloud strategies to meet that challenge:

1. Rethinking Measurement

Cost savings have long been a common metric as part of evaluating the business impact of cloud. However, this year's report found that more organizations are beginning to broaden how they measure progress. When asked which metrics respondents use to assess progress against cloud goals, value delivered to business units increased 12 percentage points year over year to 64%, while reliance on cost efficiency and savings declined by 6 points as a primary success metric.

This signals a broader shift in how decisions are made. Organizations are beginning to prioritize business outcomes and long-term value over cost alone. FinOps is evolving into a key role that connects spend to outcomes in a consistent and measurable way (and no longer just for cloud but across the broader technology estate).

2. Building AI-Focused Governance

As AI adoption accelerates, it drives both increased consumption and new kinds of cost unpredictability. Challenges that were surfaced by the technical and executive leaders surveyed include: the security, data quality, and cost volatility tied to dynamic AI workloads. In part, over half (53%) of the surveyed respondents say security and compliance risks associated with cloud-based AI are a leading challenge.

Organizations are responding to this risk by increasingly establishing dedicated AI governance teams or senior leadership that oversees AI investments and risk management. This governance-first mindset aligns directly with what FinOps maturity delivers: more trust in the data driving AI and more clarity into AI's cost trajectory, leading to responsible scaling.

Growing AI workloads require robust governance since they can rapidly increase cloud spending as organizations race to adopt the latest innovations.

3. Dialing In on Spend

Over the past year, AI projects and increased developer usage have pushed cloud bills beyond expectations for many organizations. Public cloud budgets are currently exceeding planned limits by 17%, and a portion of tech leaders (27%) expect to increase spending in the next 12 months.

At the same time, wasted cloud spend has reached 29%, and is rising for the first time in five years. Even well-governed organizations can lose efficiency if spend isn't continuously monitored and optimized.

The cost pressure is compounded by how AI-related costs are quickly adding up. By the time they are fully visible, demand and spend has already shifted. Even in mature environments, controlling spend requires continuous attention. Leaders that are most effective in this area are treating cloud and AI as strategic business investments. They are leveraging FinOps practices to not just manage the existing technology estate but also the accelerating consumption of AI.

As cloud enters its next phase, competitive leaders are moving beyond traditional cost management, leveraging FinOps practices to treat technology as a strategic business asset. This looks like prioritizing measurable value and ensuring that investments align with tangible business outcomes. The rise in centralized governance structures, such as FinOps teams and CCOEs, are now essential in order to manage and optimize technology value.

How Leaders Should Respond to the 2026 Cloud Era

With the rise of AI-driven investments and technologies, companies that combine robust governance and proactive waste management will better manage their ability to control costs but also unlock ROI that keeps pace with the rapidly evolving technology landscape. Overall, success in the 2026 cloud era hinges on the clarity, confidence and value organizations derive from every technology investment. 

Jay Litkey is SVP of Cloud and FinOps at Flexera

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The State of the Cloud 2026: How Organizations are Driving Real Value in Today's Dynamic Landscape

Jay Litkey
Flexera

The cloud landscape has undergone a drastic change in the last year with AI adoption shifting from being experimental into core business operations. As this shift continues, organizations are redefining how they measure success. It is measured less by infrastructure decisions or cost savings alone and more by the overarching business value and outcomes that cloud and AI investments deliver. Amidst the ever-changing environment, the data shows cloud strategies are directly influencing a company's competitiveness.

The 2026 Flexera State of the Cloud report highlights leaders' growing focus on fine tuning their cloud initiatives. To wrangle spend and governance, the report found that more and more organizations are applying mature FinOps practices, with 63% having established FinOps teams and 71% now operating a Cloud Center of Excellence (CCOE). As cloud adoption matures, organizations are moving beyond cost control to delivering measurable, governed business value.

Here's how forward-thinking leaders are upleveling their cloud strategies to meet that challenge:

1. Rethinking Measurement

Cost savings have long been a common metric as part of evaluating the business impact of cloud. However, this year's report found that more organizations are beginning to broaden how they measure progress. When asked which metrics respondents use to assess progress against cloud goals, value delivered to business units increased 12 percentage points year over year to 64%, while reliance on cost efficiency and savings declined by 6 points as a primary success metric.

This signals a broader shift in how decisions are made. Organizations are beginning to prioritize business outcomes and long-term value over cost alone. FinOps is evolving into a key role that connects spend to outcomes in a consistent and measurable way (and no longer just for cloud but across the broader technology estate).

2. Building AI-Focused Governance

As AI adoption accelerates, it drives both increased consumption and new kinds of cost unpredictability. Challenges that were surfaced by the technical and executive leaders surveyed include: the security, data quality, and cost volatility tied to dynamic AI workloads. In part, over half (53%) of the surveyed respondents say security and compliance risks associated with cloud-based AI are a leading challenge.

Organizations are responding to this risk by increasingly establishing dedicated AI governance teams or senior leadership that oversees AI investments and risk management. This governance-first mindset aligns directly with what FinOps maturity delivers: more trust in the data driving AI and more clarity into AI's cost trajectory, leading to responsible scaling.

Growing AI workloads require robust governance since they can rapidly increase cloud spending as organizations race to adopt the latest innovations.

3. Dialing In on Spend

Over the past year, AI projects and increased developer usage have pushed cloud bills beyond expectations for many organizations. Public cloud budgets are currently exceeding planned limits by 17%, and a portion of tech leaders (27%) expect to increase spending in the next 12 months.

At the same time, wasted cloud spend has reached 29%, and is rising for the first time in five years. Even well-governed organizations can lose efficiency if spend isn't continuously monitored and optimized.

The cost pressure is compounded by how AI-related costs are quickly adding up. By the time they are fully visible, demand and spend has already shifted. Even in mature environments, controlling spend requires continuous attention. Leaders that are most effective in this area are treating cloud and AI as strategic business investments. They are leveraging FinOps practices to not just manage the existing technology estate but also the accelerating consumption of AI.

As cloud enters its next phase, competitive leaders are moving beyond traditional cost management, leveraging FinOps practices to treat technology as a strategic business asset. This looks like prioritizing measurable value and ensuring that investments align with tangible business outcomes. The rise in centralized governance structures, such as FinOps teams and CCOEs, are now essential in order to manage and optimize technology value.

How Leaders Should Respond to the 2026 Cloud Era

With the rise of AI-driven investments and technologies, companies that combine robust governance and proactive waste management will better manage their ability to control costs but also unlock ROI that keeps pace with the rapidly evolving technology landscape. Overall, success in the 2026 cloud era hinges on the clarity, confidence and value organizations derive from every technology investment. 

Jay Litkey is SVP of Cloud and FinOps at Flexera

Related Links

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While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

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As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

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Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

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Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

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