Ingram Micro’s message to channel partners is to focus less on where AI runs and more on what it does for customers and the business. Cheryl Rang, the company’s vice president of technology solutions, put it this way: “It’s about how you apply it, not just where.” For managed service providers (MSPs), that means finding useful, supportable applications—such as workflow automation, fraud detection or secure data management—rather than assuming they need to build infrastructure to train their own large language models.
What Ingram Micro is asking partners to change
In an interview published by CRN on November 11, 2025, Rang described AI strategy as a question of application: are partners using AI to build technology solutions, or building technology solutions for AI? Her broader point is that the technology will evolve, but its value depends on how a company applies it: “No matter what AI becomes, the through line is how you’re applying it.”
That framing shifts the first question from “Where will the model run?” to “Which customer or operational problem should AI help solve?” Deployment choices still matter for cost, security and integration, but they are means to an outcome, not the strategy by themselves.
Practical AI applications for channel partners
Rang’s examples span endpoints, industry-specific work and internal operations. They illustrate possible applications, not quantified results or proof that every use case is suitable for every customer.
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| Application area | Example in the interview | What a partner should establish |
|---|---|---|
| Endpoints | AI PCs, including PCs capable of running large language models | Which tasks benefit from on-device AI, and what device, software and data controls are needed. |
| Financial services | Fraud detection in banking | How the system fits existing review processes, what data it uses and how people handle flagged activity. |
| Healthcare | Secure data management | How the proposed approach protects sensitive information and works with the customer’s existing systems and obligations. |
| Security | Stronger security protocols | Which specific risk or control the AI-enabled service addresses, and how effectiveness will be assessed. |
| Workflows and customer experience | Agent-based efficiency improvements | Which steps can be automated safely, when a human must review an action, and what service outcome the customer expects. |
For an MSP, a viable use case needs more than a compelling demonstration. The partner should identify the customer’s problem, check whether the necessary data and integrations are available, define human oversight and security boundaries, and agree on how the customer will judge success. The interview offers no performance benchmarks or financial figures for these examples, so partners should treat expected benefits as hypotheses to validate with each customer.
Partners do not have to train their own foundation models
Rang said Ingram Micro does not expect partners to “build their own data center to train large language models.” The strategy she described is to help partners apply AI to business needs and deliver better customer outcomes, rather than making ownership of large-scale model-training infrastructure a prerequisite.
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That does not mean infrastructure decisions disappear. A partner still needs to assess where a particular workload should run and how it will connect to customer data, applications and controls. The distinction is that those decisions follow the use case: an endpoint application, a secured data workflow and an agent handling routine steps may call for different designs.
How an MSP can turn AI into a business practice
Rang’s advice is not to treat AI as a passing experiment. “You can’t go back to saying, ‘I remember life before ChatGPT and I’ll never use it again.’ Now it’s about how you take that and build a business practice around it.” For an MSP, that can mean moving from one-off experimentation toward repeatable discovery, implementation and support.
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Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →- Start with a customer problem. Identify a costly delay, repetitive workflow, security concern or service-quality issue before selecting an AI tool.
- Check feasibility and risk. Confirm data access, privacy and security requirements, integration needs, failure handling and where human review is required.
- Define the outcome. Agree with the customer on a baseline and a practical way to assess whether the solution improves the process. The CRN interview does not provide a standard metric or promised return.
- Plan ongoing service. Decide who will monitor the implementation, handle changes and exceptions, maintain integrations and communicate with the customer after launch.
- Use enablement where needed. Rang said Ingram Micro trains, enables and supports partners who are still getting comfortable with AI. Partners should confirm which training and support are currently available before building them into a delivery plan.
Recurring MSP revenue is a potential business opportunity, not an outcome guaranteed by adopting AI. It depends on whether a partner can provide ongoing value—such as managing a workflow, supporting integrations or maintaining appropriate controls—and whether the customer is willing to pay for that service.
What Ingram Micro’s Xvantage AI agent is described as doing
In the interview, Ingram Micro said its Xvantage platform included a built-in AI agent that could surface partner opportunities, recent company news and emerging solution areas. The stated use is to help associates prepare for customer meetings and have more substantive, less transactional conversations.
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The interview does not publish an adoption rate, measured productivity uplift or revenue impact for the agent. Its description therefore supports a picture of a sales-preparation aid, not a quantified claim about business results. The feature set and availability may have changed since the interview; partners should verify current Xvantage capabilities and access with Ingram Micro.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What partners should take from the strategy
The practical test for an AI initiative is whether it addresses a defined customer or business need, fits the available data and systems, and can be delivered with suitable oversight and ongoing support. As Rang put it, “No matter what AI becomes, the through line is how you’re applying it.” That approach leaves room for endpoints, agents and other tools without confusing the location of AI with the value it is meant to create.
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