State of the Data Center 2024: Hybrid IT Adoption Accelerates

More than ever, IT executives have options for strategically locating computing resources across multiple environments, with an eye toward interconnected digital ecosystems that deliver value, performance and flexibility. These specialized digital ecosystems are being strategically designed via combinations of colocation, cloud and on-premises resources aligned with business objectives.

The 2024 State of the Data Center Report from CoreSite shows that although C-suite confidence in the economy remains high, a VUCA (volatile, uncertain, complex, ambiguous) environment has many business leaders proceeding with caution when it comes to their IT and data ecosystems, with an emphasis on cost control and predictability, flexibility and risk management.

However, this cautious approach also must accommodate a growing volume of resource-intensive artificial intelligence (AI) and other high-density workloads critical to organizational growth and innovation. The result of this dichotomy is an accelerated embrace of hybrid IT ecosystems to support varying types of data and workload needs.

Specifically, 98% of organizations say they have currently adopted or plan to adopt a hybrid model using colocation, private cloud and public cloud to manage their workloads.


Source: CoreSite

"The 2024 data demonstrates that IT leaders are increasingly relying on hybrid IT environments to support business objectives, including better cost control and predictability, and to efficiently deploy specific workloads to maximize benefits," said Juan Font, CoreSite President and CEO and American Tower Senior Vice President. "Underscored by the evolving needs of AI and other high-density workloads, modern hybrid IT strategies allow for the type of flexibility that can reduce infrastructure footprints and focus IT resources and talent on growth, while delivering the performance organizations need to remain competitive."

Key insights from this year's report include:

Connection Reigns Supreme

Companies need to directly connect to the cloud and interconnect systems and locations to transfer large-scale amounts of data, while keeping latency, cost, security and quality in mind. In fact, cloud interconnection was the No. 1 reason for using colocation for nearly half of the 22 workloads included in the survey. However, only 31% of respondents say their current colocation provider offers interconnection to a variety of cloud providers.

Additionally, 95% of respondents said the ability of colocation providers to offer native, direct connections to the major cloud providers is important, with 69% citing it as very important.

A Public Cloud Exodus

The public cloud has historically been seen as an essential platform to replace legacy technology or quickly add new capabilities to improve agility and flexibility. However, "cloud smart" hybrid IT infrastructure environments are increasingly valued over an "all in" cloud approach for their ability to effectively and efficiently address cost concerns while meeting performance and compliance requirements.

Most participants in the survey say they have considered a move from public cloud to colocation across 22 different workloads, led by generative AI (GenAI) applications, BI/analytics, and IoT connectivity and management. Compared with the 2023 study, the use of public cloud is trending down across all workloads.

AI Is Hybrid IT Accelerant

Heightened use of AI — which requires more computing resources and high data volumes — is forcing IT leaders to re-evaluate options for hosting these and other high-density workloads within current budget constraints. The 2024 results show a shift of AI-specific workloads from on-prem environments, primarily to colocation data centers.

Additionally, at least three-quarters of respondents in this year's survey said they are considering moving AI-related workloads from the public cloud to a colocation data center, including GenAI applications (91%), chatbots (81%), predictive analytics (79%) and augmented AI applications (76%).

"IT executives have more options than ever for locating computing resources, and the CoreSite 2024 State of the Data Center Report demonstrates how highly customized hybrid environments that include colocation are becoming the option of choice for organizations that must remain highly competitive while continually managing cost predictably," said John Gallant, Enterprise Consulting Director at CIO. "These often-competing pressures only will become more salient with AI's explosive growth in the coming years. Adopting an ecosystem — and regularly optimizing that ecosystem — with a mix of colocation, private cloud and public cloud capabilities is a trend that likely will continue to remain dominant in the coming years."

Methodology: The report is based on a quantitative survey of 300 CIOs, CTOs and other IT decision-makers, plus in-depth interviews with seven senior technology executives from financial services, healthcare, retail and SaaS organizations. Foundry, an IDG, Inc. company, conducted the research.

Related Links

Hot Topics

The Latest

Alert Fatigue Is No Longer a Morale Problem, It's a Reliability Risk and a System Failure

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

Most Enterprises Think They Can Switch AI Vendors in a Month ... Most Who've Tried Couldn't

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Your Observability Stack Has a Telemetry Pipeline Problem

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

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 ...

How Intelligent Orchestration Enables Enterprises to Move from AI POC to AI Production

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 ...

Reliability Is the New Bottleneck of Innovation

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 ...

5 Takeaways from the Observability Forecast for Retail and eCommerce

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

State of the Data Center 2024: Hybrid IT Adoption Accelerates

More than ever, IT executives have options for strategically locating computing resources across multiple environments, with an eye toward interconnected digital ecosystems that deliver value, performance and flexibility. These specialized digital ecosystems are being strategically designed via combinations of colocation, cloud and on-premises resources aligned with business objectives.

The 2024 State of the Data Center Report from CoreSite shows that although C-suite confidence in the economy remains high, a VUCA (volatile, uncertain, complex, ambiguous) environment has many business leaders proceeding with caution when it comes to their IT and data ecosystems, with an emphasis on cost control and predictability, flexibility and risk management.

However, this cautious approach also must accommodate a growing volume of resource-intensive artificial intelligence (AI) and other high-density workloads critical to organizational growth and innovation. The result of this dichotomy is an accelerated embrace of hybrid IT ecosystems to support varying types of data and workload needs.

Specifically, 98% of organizations say they have currently adopted or plan to adopt a hybrid model using colocation, private cloud and public cloud to manage their workloads.


Source: CoreSite

"The 2024 data demonstrates that IT leaders are increasingly relying on hybrid IT environments to support business objectives, including better cost control and predictability, and to efficiently deploy specific workloads to maximize benefits," said Juan Font, CoreSite President and CEO and American Tower Senior Vice President. "Underscored by the evolving needs of AI and other high-density workloads, modern hybrid IT strategies allow for the type of flexibility that can reduce infrastructure footprints and focus IT resources and talent on growth, while delivering the performance organizations need to remain competitive."

Key insights from this year's report include:

Connection Reigns Supreme

Companies need to directly connect to the cloud and interconnect systems and locations to transfer large-scale amounts of data, while keeping latency, cost, security and quality in mind. In fact, cloud interconnection was the No. 1 reason for using colocation for nearly half of the 22 workloads included in the survey. However, only 31% of respondents say their current colocation provider offers interconnection to a variety of cloud providers.

Additionally, 95% of respondents said the ability of colocation providers to offer native, direct connections to the major cloud providers is important, with 69% citing it as very important.

A Public Cloud Exodus

The public cloud has historically been seen as an essential platform to replace legacy technology or quickly add new capabilities to improve agility and flexibility. However, "cloud smart" hybrid IT infrastructure environments are increasingly valued over an "all in" cloud approach for their ability to effectively and efficiently address cost concerns while meeting performance and compliance requirements.

Most participants in the survey say they have considered a move from public cloud to colocation across 22 different workloads, led by generative AI (GenAI) applications, BI/analytics, and IoT connectivity and management. Compared with the 2023 study, the use of public cloud is trending down across all workloads.

AI Is Hybrid IT Accelerant

Heightened use of AI — which requires more computing resources and high data volumes — is forcing IT leaders to re-evaluate options for hosting these and other high-density workloads within current budget constraints. The 2024 results show a shift of AI-specific workloads from on-prem environments, primarily to colocation data centers.

Additionally, at least three-quarters of respondents in this year's survey said they are considering moving AI-related workloads from the public cloud to a colocation data center, including GenAI applications (91%), chatbots (81%), predictive analytics (79%) and augmented AI applications (76%).

"IT executives have more options than ever for locating computing resources, and the CoreSite 2024 State of the Data Center Report demonstrates how highly customized hybrid environments that include colocation are becoming the option of choice for organizations that must remain highly competitive while continually managing cost predictably," said John Gallant, Enterprise Consulting Director at CIO. "These often-competing pressures only will become more salient with AI's explosive growth in the coming years. Adopting an ecosystem — and regularly optimizing that ecosystem — with a mix of colocation, private cloud and public cloud capabilities is a trend that likely will continue to remain dominant in the coming years."

Methodology: The report is based on a quantitative survey of 300 CIOs, CTOs and other IT decision-makers, plus in-depth interviews with seven senior technology executives from financial services, healthcare, retail and SaaS organizations. Foundry, an IDG, Inc. company, conducted the research.

Related Links

Hot Topics

The Latest

Alert Fatigue Is No Longer a Morale Problem, It's a Reliability Risk and a System Failure

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

Most Enterprises Think They Can Switch AI Vendors in a Month ... Most Who've Tried Couldn't

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Your Observability Stack Has a Telemetry Pipeline Problem

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

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 ...

How Intelligent Orchestration Enables Enterprises to Move from AI POC to AI Production

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 ...

Reliability Is the New Bottleneck of Innovation

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 ...

5 Takeaways from the Observability Forecast for Retail and eCommerce

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...