What are the factors driving private cloud adoption?
- Many organizations are undergoing “cloud repatriation”: a process where organizations move resources from public clouds back to private clouds.
- Increasing costs are one driver of private cloud adoption. But other factors in the migration from public clouds to private clouds include data security and data sovereignty, workload performance, and the increasing use of AI models.
- Managed service providers are uniquely positioned to help organizations with private cloud migration and cloud repatriation—and help organizations build a strategic approach to managing their assets wherever they reside.
For much of the past couple of decades, migration to public clouds was all the rage. But of late, private cloud adoption has been gathering steam.
For much of the 2000s, public cloud adoption dominated headlines and IT budgets—with more than 90% of organizations using public cloud as of 2024. But as organizations adopted public clouds, they often experienced sticker shock as cloud costs increased with the pay-per-use model and resource intensive-workloads, like AI.
In addition to cost increases, public clouds weren’t always optimum for organizations given latency and performance concerns. Public clouds also challenged data security, and workload-specific needs where private clouds could be attractive. As a result, some organizations are opting for cloud repatriation and moving resources from public clouds back in-house. Still, after years of touting the benefits of public cloud infrastructure, this reversal to private cloud adoption can seem counterintuitive.
With virtualized assets in a private cloud—deployed and overseen by an expert managed service provider—can reduce costs, boost application performance, and enable organizations to retain control of sensitive data assets.
According to recent data, 83% of enterprises plan to move their workloads to a private cloud from a public cloud. And a 2025 report by Gartner, more than 65% of enterprises building AI models now prefer private or hybrid cloud environments over public cloud-only strategies. This signals a clear shift toward owning the infrastructure to drive future innovation.
Why are organizations returning to private cloud adoption?
There are several reasons that organizations are considering moving resources back to private clouds.
According to 2024 data, 69% of companies have moved at least some workloads from a public cloud and back to on-premises systems. include data security and compliance concerns (50%), better integration with existing on-premises systems (48%), and cost savings (44%). Cost savings has become an increasing concern as organizations increasingly use AI and other resource-intensive workloads.
In some cases, organizations are also considering using hybrid cloud architecture—where organizations combine public and private clouds to provide a flexible mix of cloud computing services. Hybrid cloud architecture enables organizations to get the benefits of public and private clouds, such as the scalability and cost-effectiveness of public clouds and the security and compliance control of private clouds.
According to data, 73% of respondents to a recent survey are opting for this best-of-both-worlds option.
“A hybrid cloud architecture gives organizations several benefits: greater agility, more control over data security and compliance, and the ability to get more value from existing infrastructure,” said James Wood, VP of technology at Integris. “Organizations gain the flexibility and innovation the public cloud provides by running certain workloads in the cloud while keeping highly sensitive data in their own data center to meet client needs or regulatory requirements.
Key benefits of private cloud and hybrid cloud adoption—and how MSPs can help
Now let’s explore some of the key benefits of repatriating some or all resources to a private or hybrid cloud architecture.
Cost optimization. Consider that enterprise cloud costs rose an average of 30% in 2024, according to a survey. Spending on AI applications and generative AI specifically—workloads that demand more cloud resources—were cited as top drivers for half of respondents.
Hybrid and private clouds can help curb public cloud costs by enabling organizations to strategically allocate workloads in public and private clouds based on workload requirements, balancing cost-effectiveness with security and performance needs. Managing assets across public and private clouds, though, requires expertise.
Managed service providers can also help provide cost-benefit analysis of which resources may be cost-effectively run on premises versus in a public cloud. They can architect resources for real-time allocation, optimize costs, and they can help organizations prevent sticker shock by developing proactive cloud cost forecasting. Most organizations lack the skills in-house for this private cloud management, and it’s where an MSP’s support and expertise can shine.
Greater control and data security. Private clouds provide organizations with greater control over which data resides where and customized security protocols and access controls, including data sovereignty (where data privacy is governed by the laws of the region in which data is housed). Greater control of data is crucial for industries such as healthcare, financial services, and legal practices, where data privacy and compliance are paramount. Public cloud providers and their service-level agreements can make it challenging to know where an organization’s data resides, and organizations may not be able to ensure governance policies are being met.
Further, artificial intelligence and machine learning algorithms are resource-hungry and rely on extensive data sets, a significant portion of which consists of sensitive and confidential information. While private clouds offer organizations the ability to house, manage, and analyze data in a protected private cloud environment rather than residing in a public cloud architecture.
If organizations are considering bringing some data back in-house and retaining some data in public clouds, managed service providers are well positioned to help organizations identify which data should reside where and how to migrate that data safely.
Customization and optimization of cloud architecture. Private clouds enable organizations to customize infrastructure to meet specific needs, such as optimizing for a particular type of AI model or workload—and may frequently involve sensitive or proprietary data. By adopting a workload-driven strategy, particularly for hybrid cloud architecture, organizations can tailor their cloud environments to meet specific operational demands, ensuring optimal performance and scalability.
This kind of customization enables better application performance and efficiency compared with public cloud environments, which offer more generic and less customizable options.
MSPs are well positioned to analyze workloads and IT environments as organizations adopt, then optimize, private cloud architecture. They can architect hybrid clouds to quickly scale up or down based on business requirements, ensuring that companies can handle sudden increases in traffic or data processing needs without experiencing downtime or performance issues. MSPs can also ensure that the infrastructure can grow as the business grows, allowing the addition of new resources or services.
Boosted workload performance. Instead of having to send data to a public cloud and then bring it back in-house for use and analysis, private clouds can reduce the latency and performance issues associated with sending data off-site.
MSPs can undergo regular capacity planning exercises to ensure infrastructure can handle current and future workloads and scale workloads accordingly. MSPs can also ensure continuously monitor key performance metrics, including response time, throughput, and resource utilization.
For compute-intensive workloads such as AI, MSPs are uniquely positioned to help organizations optimize their cloud architecture. MSPs can use GPU virtualization, which allows multiple virtual machines to share a single physical GPU. This approach can lead to faster training and inference times for AI models, resulting in improved efficiency and productivity.
Reduced latency. As noted, MSPs AI workloads to a private cloud, they can eliminate the latency associated with transferring data to and from the public cloud. This is particularly important for real-time AI applications where low latency is critical for performance and accuracy.
Compliance and regulatory needs. For industries such as banking, legal, and healthcare, Private cloud architecture can help organizations meet their compliance and regulatory requirements for AI applications, particularly in industries with stringent regulations.
This can ensure that AI systems operate legally, securely, and are compliant with industry regulations.
Enabling edge computing. Bringing AI closer to the users and devices that consume these models requires an architecture that enables bringing that data closer to the edge
Edge computing is a distributed computing approach that brings data processing and storage closer to the sources of data, such as IoT devices, mobile phones, and tablets.
The edge is particularly noteworthy in AI/ML deployments where huge amounts of data and decision-making move closer to the data sources—again, minimizing latency, boosting performance, and enabling data security.
MSPs can help with the challenges of bringing data and applications securely to the edge, including deploying and managing, ensuring data protection at edge devices, and integrating edge computing with existing cloud services, IT systems, and Internet of Things devices.
Consider a factory floor, for example: Gathering, analyzing, and acting on data on the factory floor in real time offers profound benefits. Reducing downtime, accurately predicting maintenance, and improving overall product quality results in higher yield, reduced waste, increased throughput, and lower overall costs. As manufacturers face slim margins and rising input costs, reducing downtime and improving quality are key components of helping the industry be profitable.
Conclusion: MSPs can help organizations gain the benefits of private and hybrid cloud adoption
MSPs can help organizations consider the benefits of private and hybrid cloud architecture. For those organizations considering repatriation or ramping up hybrid cloud setups, MSPs are uniquely positioned to help organizations identify which applications and data should reside in private or public clouds, design tailored hybrid cloud architectures, and ensure integration and data migration. Managed service providers also provide ongoing monitoring and optimization, leverage automation and orchestration tools, and ensure compliance within the hybrid cloud environment.
MSPs act as trusted partners, guiding clients through the transition to private cloud-based services. Clients are relying on MSP expertise and experience to facilitate a successful migration. According to some data, 54% of respondents say that MSPs help organizations manage IT more effectively, and 36% say MSPs help reduce costs.
“MSPs are invaluable resources as organizations optimize their cloud strategies,” Wood said. “When organizations turn to their MSP for expertise on cloud architecture, data security and sovereignty, workload allocation, and cloud monitoring, they can spend time developing their core business.”
Checklist for organizations considering private cloud adoption and hybrid cloud
Here are some characteristics that might encourage an organization to repatriate resources to a private cloud:
☐ Companies that have an uncontrolled and unconsolidated cloud estate—potentially among many vendors
☐ Organizations that are capturing and storing sensitive data who need assurances that this data will remain local and under their country’s data protection laws
☐ Enterprises with high-frequency transactional systems that perform better in edge architectures designed for lower latency
☐ Enterprises that initially needed the advanced tooling and scalability of public cloud, but now have workloads with stable requirements that could be run more efficiently on other infrastructure
☐ Businesses with storage-heavy workloads