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The Share of Enterprise Workloads Run in On-Premise Data Centers Falls Below 50% for First Time

As more organizations opt for a hybrid approach to IT, the share of enterprise workloads that are run in corporate, on-premises facilities has fallen to below half for the first time and is expected to shrink further, according to the Uptime Institute Global Data Center Survey 2023.

"Our data shows operators grappling with several issues," said Andy Lawrence, Executive Director, Uptime Intelligence. "In 2023, the lingering effects of the COVID-19 pandemic have receded, but other challenges have emerged. Digital infrastructure managers are now most concerned with improving energy performance and dealing with staffing shortfalls, while Government regulations aimed at improving data center sustainability and visibility are beginning to require attention, investment, and action."

Key findings from the report include:

■ Enterprise operators say data security is the biggest impediment to moving mission-critical workloads to the public cloud. Resiliency and transparency are lesser concerns.

■ Most operators believe acceptance of the use of artificial intelligence will grow in data centers, but operators are distrustful of its ability to make reliable operational decisions.

■ More than half (55%) of operators reported they have had an outage at their site in the past three years, the lowest number yet recorded. This continues a trend of steady improvement.

■ Power outages continue to be cited as the single biggest cause of outages.

■ Nearly two-thirds of operators have problems recruiting or retaining staff – however, this figure is not currently growing. The largest skill gaps are in operations, mechanical and electrical roles.

Methodology: Uptime conducted the survey online from February–April 2023 and collected responses from more than 850 data center owners and operators and nearly 700 vendors and consultants.

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The Share of Enterprise Workloads Run in On-Premise Data Centers Falls Below 50% for First Time

As more organizations opt for a hybrid approach to IT, the share of enterprise workloads that are run in corporate, on-premises facilities has fallen to below half for the first time and is expected to shrink further, according to the Uptime Institute Global Data Center Survey 2023.

"Our data shows operators grappling with several issues," said Andy Lawrence, Executive Director, Uptime Intelligence. "In 2023, the lingering effects of the COVID-19 pandemic have receded, but other challenges have emerged. Digital infrastructure managers are now most concerned with improving energy performance and dealing with staffing shortfalls, while Government regulations aimed at improving data center sustainability and visibility are beginning to require attention, investment, and action."

Key findings from the report include:

■ Enterprise operators say data security is the biggest impediment to moving mission-critical workloads to the public cloud. Resiliency and transparency are lesser concerns.

■ Most operators believe acceptance of the use of artificial intelligence will grow in data centers, but operators are distrustful of its ability to make reliable operational decisions.

■ More than half (55%) of operators reported they have had an outage at their site in the past three years, the lowest number yet recorded. This continues a trend of steady improvement.

■ Power outages continue to be cited as the single biggest cause of outages.

■ Nearly two-thirds of operators have problems recruiting or retaining staff – however, this figure is not currently growing. The largest skill gaps are in operations, mechanical and electrical roles.

Methodology: Uptime conducted the survey online from February–April 2023 and collected responses from more than 850 data center owners and operators and nearly 700 vendors and consultants.

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Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...