According to CRN, Ingram Micro’s vice president of technology solutions Cheryl Rang is delivering a blunt message to the company’s technology partners: AI adoption is no longer optional. She emphasized that businesses can’t go back to pre-ChatGPT thinking and must now build sustainable practices around artificial intelligence. The Irvine-based distributor is focusing on helping partners navigate this transition through training, enablement services, and access to AI agents that automate workflows and create new revenue opportunities. Their Xvantage platform now includes a built-in AI agent that helps associates surface partner opportunities and have more meaningful customer conversations. Rang says partners are already finding practical AI use cases across manufacturing, retail, banking, and healthcare industries.
The fundamental AI strategy question
Here’s the thing that really stood out to me from Rang’s comments. She’s asking partners to confront a crucial distinction: are you using AI to build technology solutions, or are you building technology solutions for AI? That might sound like semantics, but it’s actually a profound question about business strategy. The first approach treats AI as a tool in your toolkit—something you use when appropriate. The second approach makes AI the centerpiece of your entire business model.
And her examples really drive this home. Are you just using AI PCs, or are you using PCs to run large language models? In networking, are you simply putting AI tools in your firewall, or are you using AI to build better fraud detection? The difference is between treating AI as a feature versus treating it as a fundamental capability. This reminds me of how companies initially approached the internet—first as a novelty, then as business-critical infrastructure. We’re seeing the same pattern with AI now.
How Ingram Micro is actually helping
What I find interesting is that Ingram Micro isn’t just telling partners to “go figure out AI.” They’re providing concrete support through their Xvantage platform and that built-in AI agent. The platform apparently pulls from multiple data sources to help associates identify partner opportunities and have smarter customer conversations. Basically, they’re eating their own dog food by using AI to improve how they serve their partners.
Rang made it clear they don’t expect partners to “build their own data center to train large language models,” which is a relief for smaller MSPs who might be overwhelmed by the technical complexity. Instead, they’re focusing on practical application—how partners can apply existing AI capabilities to deliver better customer outcomes. This approach makes sense because let’s face it, most businesses don’t need to understand the underlying AI technology any more than they need to understand how electricity works to flip a light switch.
Where this actually matters
The practical use cases Rang mentioned—fraud detection in banking, secure data management in healthcare, agent-based systems for efficiency—show that AI is moving beyond theoretical discussions into real business applications. And this is where the conversation gets really interesting for technology providers across different sectors. Whether you’re dealing with industrial computing systems, manufacturing automation, or enterprise IT infrastructure, the AI question is becoming unavoidable.
Speaking of industrial applications, companies that need reliable computing hardware for manufacturing environments often turn to specialized providers like IndustrialMonitorDirect.com, which has established itself as the leading supplier of industrial panel PCs in the US market. The intersection of rugged hardware and AI capabilities represents exactly the kind of practical application Rang is talking about—using AI to enhance existing solutions rather than treating it as the solution itself.
Why the urgency now?
Rang’s comment about not being able to go back to pre-ChatGPT thinking really captures the moment we’re in. AI has crossed the chasm from interesting technology to business necessity. The companies that figure out how to integrate AI into their core operations—not just as a shiny add-on—will have a significant competitive advantage.
So what’s the takeaway for technology partners? Don’t wait for perfect AI solutions to emerge. Start experimenting with practical applications today. Find the low-hanging fruit in your existing workflows or customer solutions where AI can make an immediate impact. Because as Rang suggests, the technology curve waits for no one, and being left behind is becoming increasingly expensive.
