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IT Leaders Struggle to Demonstrate Cloud ROI

While the FinOps discipline is robust and proven, executives appear to be overconfident, according to Performance vs. Perception: The FinOps Execution Gap, a new report from CloudBolt Software

Many label their FinOps practices as mature and automated, which stands in stark contrast with the reality:

  • 78% of respondents admit difficulty in consistently demonstrating cloud ROI, which they defined primarily as revenue growth (43%), followed by operational efficiency/productivity (36%), and then cost savings (35%).
  • 98% agree that Kubernetes is becoming a major driver of cloud spend, but 91% remain unable to effectively optimize their Kubernetes clusters, signaling a critical blind spot as container adoption grows.
  • 66% report mostly to fully automated environments for cloud waste management and cloud spend optimization. Yet 58% of respondents say it takes weeks or months to detect and fully remediate cloud-cost waste opportunities. This calls into question the assertion of a truly automated approach for the majority of respondents.

"FinOps as a discipline is more sound than ever and continues to evolve effectively," says Kyle Campos, CTPO at CloudBolt. "But a good percentage of organizations may be taking a victory lap before even navigating the first turn. Through this research, it's evident that while a majority indicate they believe they've achieved FinOps maturity, the data shows they are still in the early stages of operationalizing and optimizing FinOps practices. Confidence in lieu of measurable progress obscures reality and hinders the improvement necessary for significant business impact."

The report details key barriers to stronger ROI on cloud investments, with:

  • 55% of respondents citing difficulty linking cloud spend directly to business outcomes.
  • 48% blaming organizational misalignment and operational silos.
  • 44% noting inefficient resource management, including poor tagging and inconsistent accountability.

Further, the report identifies private cloud/data centers as playing a key role in the ROI equation:

  • Hybrid multi-cloud management was identified as the top priority by 42% of respondents.
  • 39% say hybrid cloud management will be a "funded priority" for their organization over the next 6-12 months, only topped by AI/ML cloud-cost optimization (FinOps for AI) at 40%.

"Leaders believe they have visibility into their cloud spend. Yet without necessary governance, enforcement, and effective remediation, they are doing little to reduce the insight-to-action gap — the time it takes to go from 'we have a problem' to 'problem fixed and cost optimized.' This leads to persistent inefficiencies and inflated costs," Campos adds. "Kubernetes and AI-driven workloads especially highlight this disconnect — rapid adoption without proper operational control and automated actions (both retrospective and proactive) is dramatically affecting return on investment. If FinOps practices are not focusing on continuous optimization and employing the capabilities to execute on that, organizations will continue to struggle to effectively show cloud ROI."

Methodology: Conducted in collaboration with Wakefield Research, the study surveyed 350 senior IT leaders in the US across a wide range of industries to assess the current state of FinOps practices.

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IT Leaders Struggle to Demonstrate Cloud ROI

While the FinOps discipline is robust and proven, executives appear to be overconfident, according to Performance vs. Perception: The FinOps Execution Gap, a new report from CloudBolt Software

Many label their FinOps practices as mature and automated, which stands in stark contrast with the reality:

  • 78% of respondents admit difficulty in consistently demonstrating cloud ROI, which they defined primarily as revenue growth (43%), followed by operational efficiency/productivity (36%), and then cost savings (35%).
  • 98% agree that Kubernetes is becoming a major driver of cloud spend, but 91% remain unable to effectively optimize their Kubernetes clusters, signaling a critical blind spot as container adoption grows.
  • 66% report mostly to fully automated environments for cloud waste management and cloud spend optimization. Yet 58% of respondents say it takes weeks or months to detect and fully remediate cloud-cost waste opportunities. This calls into question the assertion of a truly automated approach for the majority of respondents.

"FinOps as a discipline is more sound than ever and continues to evolve effectively," says Kyle Campos, CTPO at CloudBolt. "But a good percentage of organizations may be taking a victory lap before even navigating the first turn. Through this research, it's evident that while a majority indicate they believe they've achieved FinOps maturity, the data shows they are still in the early stages of operationalizing and optimizing FinOps practices. Confidence in lieu of measurable progress obscures reality and hinders the improvement necessary for significant business impact."

The report details key barriers to stronger ROI on cloud investments, with:

  • 55% of respondents citing difficulty linking cloud spend directly to business outcomes.
  • 48% blaming organizational misalignment and operational silos.
  • 44% noting inefficient resource management, including poor tagging and inconsistent accountability.

Further, the report identifies private cloud/data centers as playing a key role in the ROI equation:

  • Hybrid multi-cloud management was identified as the top priority by 42% of respondents.
  • 39% say hybrid cloud management will be a "funded priority" for their organization over the next 6-12 months, only topped by AI/ML cloud-cost optimization (FinOps for AI) at 40%.

"Leaders believe they have visibility into their cloud spend. Yet without necessary governance, enforcement, and effective remediation, they are doing little to reduce the insight-to-action gap — the time it takes to go from 'we have a problem' to 'problem fixed and cost optimized.' This leads to persistent inefficiencies and inflated costs," Campos adds. "Kubernetes and AI-driven workloads especially highlight this disconnect — rapid adoption without proper operational control and automated actions (both retrospective and proactive) is dramatically affecting return on investment. If FinOps practices are not focusing on continuous optimization and employing the capabilities to execute on that, organizations will continue to struggle to effectively show cloud ROI."

Methodology: Conducted in collaboration with Wakefield Research, the study surveyed 350 senior IT leaders in the US across a wide range of industries to assess the current state of FinOps practices.

Hot Topics

The Latest

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...