Virtual machines remain a central component of cloud native infrastructure as AI workloads evolve, according to a Linux Foundation Research report released by the Cloud Native Computing Foundation (CNCF) and Broadcom on November 9, 2026. The timing of the underlying event is not specified. The report describes infrastructure adoption rather than announcing a policy, regulation or new technical standard, but its findings may help cloud buyers, platform suppliers and service providers assess procurement specifications and delivery choices.

What the research reports about VM platforms

CNCF and Broadcom jointly released the latest Linux Foundation Research report on November 9, 2026. Among respondents running virtual machines, 64% use on-premises hypervisor platforms and 51% use public cloud infrastructure as a service (IaaS). The research presents these findings in the context of evolving AI workloads and identifies virtual machines as a continuing core component of cloud native infrastructure.

The supplied information does not identify when the underlying event occurred. It also does not provide a sample size, survey methodology, breakdown by workload or further details of the report. The two percentages are reported among respondents who run virtual machines; the supplied summary does not establish that they represent mutually exclusive groups.

Where continued VM use may affect commercial decisions

Infrastructure buyers face a broader specification question

For organizations procuring infrastructure for AI workloads, the findings suggest that virtual machines merit explicit consideration when technical requirements are drafted. A buyer evaluating a platform may need to describe whether workloads must run on an on-premises hypervisor platform, public cloud IaaS, or both. The figures alone do not establish which option is suitable for a particular workload, but they support examining both settings before narrowing a procurement.

From an industry perspective, this could affect requests for proposals, technical evaluations and acceptance criteria. A specification that identifies the intended environment and workload assumptions may make supplier responses easier to compare. Buyers can also ask for evidence supporting claimed compatibility and delivery capabilities. These are potential procurement practices, not requirements introduced by the research.

Platform suppliers may need clearer evidence of compatibility

Suppliers of infrastructure platforms and related services may encounter questions about how their offerings support virtual machines alongside changing AI workload needs. Analysis suggests that the commercial issue is not simply whether a product can run a VM, but whether the proposed configuration matches the buyer's stated operating environment and delivery expectations.

In a bid or contract discussion, suppliers could be asked to explain platform prerequisites, supported configurations and the division of responsibilities for deployment and support. Clear technical documentation may help buyers assess those claims. The input does not establish that any supplier has changed its product, certification or commercial terms as a result of the report.

Integrators and service providers may see more complex handoffs

For teams combining infrastructure components or delivering managed services, the coexistence of on-premises and public cloud choices may make the boundaries between systems and suppliers an important part of project planning. A delivery team may need to establish which environment hosts a workload, who supplies the hypervisor or cloud service, and how responsibilities are allocated when a problem occurs.

These are possible project considerations rather than documented outcomes of the study. The reported percentages do not show how often the same organization uses both environments, how workloads move between them, or whether a particular delivery model is gaining share. Commercial planning should therefore use the research as a prompt for questions, while relying on project-specific evidence for commitments.

Turning the findings into procurement and delivery checks

Define the workload and environment before comparing bids

A practical first step for buyers is to document the AI workload under consideration and the environment in which it is expected to operate. Depending on the project, the evaluation could compare an on-premises hypervisor platform with public cloud IaaS or assess how each fits a different part of the requirement. The research does not rank these options or provide a basis for choosing one.

Procurement teams may also benefit from separating essential technical conditions from preferences. For example, bid documents can identify the environment a proposal must support and ask vendors to state any dependencies or limits. This can make differences between offers visible before a delivery schedule or price is accepted.

Check evidence against the actual configuration

Analysis suggests that technical claims are most useful when tied to the configuration being purchased. Buyers and integrators can review relevant product documentation, configuration descriptions and test evidence supplied for the proposed deployment. Where a contract or customer specification refers to certification or compliance, the parties can verify the applicable scope and supporting documents against that specific requirement.

The report summary identifies no new certification, compliance obligation or mandatory test. Any review should therefore be grounded in requirements that actually apply to the transaction, rather than treating the study as an authority that creates one. If a proposed configuration differs from the one covered by available evidence, further clarification or validation may be appropriate before acceptance.

Clarify support, responsibilities and acceptance

Delivery documents can specify which party is responsible for the infrastructure platform, deployment, issue resolution and acceptance of the finished service. This may be especially useful where a project involves more than one supplier or operating environment. Parties can ask how a proposed support arrangement applies to the agreed configuration and what information will be needed to investigate a delivery issue.

These steps are recommendations for evaluating a transaction, not execution details supplied by CNCF or Broadcom. The input provides no delivery timetable, contractual terms or evidence of a change in supplier obligations. Organizations should confirm those matters with the relevant providers and against their own project documents.

Keep procurement assumptions open to verification

The survey figures can inform an initial discussion, but they should not be used alone to forecast a supplier's availability, set a purchasing volume or determine a project's delivery date. Before making those decisions, buyers may seek information on the proposed product or service, its stated support arrangements and the evidence available for the intended workload.

Where an alternative platform is being considered, an evaluation against the same documented requirements may make trade-offs clearer. Any validation plan should reflect the specific deployment rather than assume that the research has confirmed interoperability or equivalent performance across options. The supplied summary provides no such comparison.

A market signal, with no rule change established

At this stage, it is more appropriate to understand the announcement as a research-based signal about reported infrastructure use than as an implemented rule change. The input identifies no new policy, regulation, standard, trade rule or certification requirement. It also does not establish that procurement specifications or delivery practices have already changed in response to the findings.

From an industry perspective, the figures are nevertheless relevant to conversations about what buyers may need to support as AI workloads evolve. They point to reported use of both on-premises hypervisor platforms and public cloud IaaS among respondents running virtual machines. They do not, by themselves, establish the proportion of all organizations using either approach, the rate of change over time, or the cause of adoption.

Further assessment would benefit from the full report and its methodology, including how respondents were selected, how questions were framed and whether the categories overlap. Those details could affect how confidently the findings are applied to a particular market or procurement. Later supplier responses, customer requirements and industry feedback may also help show whether the research influences commercial practice; none is established in the supplied information.

How to use the findings without overstating them

The reported results support keeping virtual machines in the discussion when assessing cloud native infrastructure for evolving AI workloads. For buyers, suppliers and delivery teams, the immediate value may lie in asking more precise questions about operating environments, technical evidence and responsibilities. The figures provide context for those questions, while project-specific requirements remain the basis for purchasing and delivery decisions.

The announcement is best treated as evidence of reported adoption within the described respondent group, subject to verification of the underlying research. It should not be presented as a new compliance obligation or as proof that one infrastructure model will prevail. Any later change in technical specifications, certification expectations or contract terms would need to be assessed on its own evidence.

Basis for this report and points to verify

This article is based on the user-provided news title, event-time information and summary. The summary states the report release date but does not specify the time of the underlying event. No specific official source link was provided in the input, so the report, its methodology and the cited figures require continuing verification against an official publication or other reliable source.

Further monitoring may include the full research report, relevant official announcements, supplier documentation, procurement documents and industry feedback. Any later claims about policy details, certification practices or implementation should be checked against the applicable source before being treated as an established requirement or market outcome.