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Modernizing IT confidently starts with a plan for workloads, data access, security and equipment lifecycle—not a blanket move to cloud or a compute purchase. Use the steps below to identify what is ready, what needs work and where each workload should run.
How do I modernize IT without disrupting the business?
Start with the services people rely on, their operating requirements and the systems they depend on. Then make changes in a sequence that protects continuity: establish a baseline, address the most consequential readiness gaps, pilot a workload, and expand only when the results meet agreed criteria.
- Map business-critical services. For each one, record its owner, users, dependencies, data, peak and steady demand, and the impact of downtime or degraded performance.
- Check infrastructure and data access. Assess compute, storage performance, network capacity, data location and the time needed for applications to reach their data. A compute upgrade alone will not resolve a storage or access bottleneck.
- Set outcomes before selecting technology. Define what must improve—such as availability, deployment time, capacity for analytics, or ability to meet security obligations—and how the team will verify it.
- Choose a contained pilot. Select a workload with a clear owner and measurable success criteria. Test its dependencies, operating procedures, security controls and recovery plan before expanding the change.
- Plan operations and retirement. Identify who will monitor and support the modernized environment, and include older equipment and data in the change and disposal plan.
Dell’s September 1, 2026 summary of its Modern Enterprise Readiness Study reports that 66% of respondents said their data center and infrastructure were not fully ready to run their most demanding workloads, including AI and analytics, at production scale. Dell attributes the study to Dell Technologies and Vanson Bourne; it surveyed 2,950 business and IT decision-makers in 35 countries in June 2026. These are survey responses, not a census or a measure of every organization’s readiness.
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Evaluate the complete path from data to user-facing service. AI readiness depends on whether the organization can provide suitable data access, place and operate the workload, and protect information throughout its use—not only on whether it has enough processors.
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- Infrastructure: Can the environment support the intended workload at production scale, including its peak demand and deployment pattern?
- Storage and data access: Can the workload access the right data at the required performance, with appropriate controls and ownership?
- Roadmap: Do AI, data and security plans agree on priorities, responsibility and sequencing?
- Risk controls: Are data use, access, regulatory obligations and security requirements defined before a workload is put into service?
In the same June 2026 survey, Dell reports that 80% of respondents said storage performance and data access were bigger bottlenecks than raw compute for many critical workloads, while 50% said they lacked a clear, actionable roadmap across AI, data and security. The figures are respondents’ assessments as reported by Dell, not proof that these issues cause every AI project to fail. Dell’s summary provides the survey sample, geography and fieldwork date, but not the full questionnaire or methodology.
Should this workload run in the cloud or on premises?
Compare the workload against the organization’s needs rather than treating any one location as the default. Public cloud, private cloud and on-premises infrastructure are options to assess; the right placement may differ by workload and may change as demand or constraints change.
| Planning factor | Questions to answer |
|---|---|
| Demand pattern | Is usage steady and predictable, or does it vary sharply and require capacity for peaks? |
| Data location and access | Where must the data reside, who needs access, and what performance does the workload require? |
| Security and compliance | Which controls, regulatory obligations or internal rules apply to the data and workload? |
| Infrastructure readiness | Can the current environment support the workload, or would it require upgrades or a different operating model? |
| Operational capability | Does the organization have the people and processes to deploy, monitor, secure and recover the workload in the proposed location? |
| Cost predictability | How will costs change with demand, and can the organization estimate and manage them under realistic usage patterns? |
Dell’s May 19, 2026 guidance describes a hybrid approach that places consistent workloads on right-sized on-premises capacity and uses cloud for variable peaks. Treat this as Dell’s recommendation, not a universal cost rule: validate it against the workload’s actual demand, data movement, security requirements and operating costs.
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Define the protection requirements alongside the architecture. The relevant questions span the environment where the workload runs—cloud, on-premises or edge—and the information it can access.
- Which data may the workload use, and who is authorized to grant that access?
- Could a third party access data or intellectual property through the AI service or tool? What do the service terms and configuration permit?
- Which regulatory and internal requirements apply to the data, its location and its processing?
- What protections are needed at the application, operating-system and hardware layers?
- How will the organization monitor the workload, respond to incidents and recover service?
Dell’s summary of the June 2026 Dell Technologies and Vanson Bourne survey says 60% of respondents reported that security and compliance concerns were the primary reason their organization had slowed or paused AI adoption. Separately, 68% expressed concern about regulatory compliance when using their data for AI, and 68% said their data and intellectual property were too valuable to place in a generative AI tool where a third party might have access. These are reported concerns among surveyed decision-makers, not findings that a particular AI service is unsafe or that all organizations share the same obligations.
Dell’s December 3, 2025 discussion of AI data-center modernization covers security challenges across cloud, on-premises and edge, as well as Intel Xeon 6 and Intel Gaudi 3 with Dell PowerEdge. It is vendor material, not an independent security evaluation. Dell’s August 2026 article also describes Dell Pro PCs with Intel Core Ultra processors, Intel vPro and CrowdStrike Falcon, using customer testimonials about hardware-assisted protection and fleet security. Those examples do not establish that every configuration has identical features or outcomes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can private cloud use existing infrastructure?
It can be an option to assess when an organization wants a private-cloud operating model. Dell describes its private-cloud subscription as software that can run on new or existing Dell PowerEdge compute, Dell storage and networking chosen by the customer. Dell also describes automation and lifecycle management, validated blueprints, and support for VMware by Broadcom, Red Hat OpenShift, Nutanix and Microsoft Azure Local.
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How do we modernize while keeping older infrastructure useful?
Use a workload-by-workload plan rather than assuming every older system should be replaced immediately or kept indefinitely. Retain equipment where it remains suitable and supportable for its assigned role; schedule upgrades or replacement where capacity, security or operating needs are not met. Include end-of-life decisions in the same plan so obsolete equipment and stored data are not left unmanaged.
Dell’s February 11, 2025 IT refresh article connects business PC upgrades with secure retirement of older assets. It describes Dell Asset Recovery Services, including data sanitization, possible onsite shredding, reuse or recycling, and reporting through TechDirect. These are Dell service descriptions; confirm the current service scope, availability and terms directly before relying on them. A business laptop may be part of an endpoint refresh, but the evidence here does not establish a particular model or compatibility requirement.
What should the modernization plan contain?
Before approving a migration, refresh or platform change, write down the decision and how it will be validated. A useful plan identifies the workload owner, target operating location, dependencies, data requirements, security and compliance controls, success measures, support responsibilities and recovery approach. It should also state what happens to equipment and data that the change makes redundant.
Keep the plan adaptable: workload needs and technology choices can differ across the organization. Treat vendor product descriptions and survey findings as inputs to due diligence, not as substitutes for evaluating your own environment.
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