Across industries, organizations are adopting AI at a rapid pace. But many are doing so using the same fragmented, tool-first mindset that defined earlier technology cycles, which could help explain why AI isn’t yet delivering its promised returns.

That’s the view from Kristin Russell, CEO of IT solutions provider CBTS and former CIO for the state of Colorado.

“I’m not sure there are new services,” Russell told Channel Dive. Instead, when it comes to AI, “it’s really about how do you bring all of those services and products into the full scope of things, so that there’s more of a full-spectrum journey.”

What vendors and channel partners often frame as an expansion of services is, in fact, a coordination problem. They’re installing pieces — say, infrastructure, security, data, engineering — but they’re still delivering them in isolation. Doing that with AI, too, stalls innovation.

“You can’t really look at [AI] as a point solution, because you’re just not going to get the return on that investment,” Russell said. “You really need to think about the comprehensive suite of services that have to be delivered and understood from that full journey perspective, so that customers could actually know where they're at … and then understand what is going to deliver outcomes for their business.”

AI’s value

Russell sees the ROI disconnect show up early in most organizations’ AI journeys, starting with how AI is defined or, more often, how it isn’t. “Many business and technology leaders are still seeing AI as a tool to be implemented, but it’s really an enterprise capability that must be built, architected and managed,” Russell said.

Channel partners should note the difference between organizations that extract value from AI and those that absorb the high costs and subsequent lack of transformation. To avoid the latter, begin with the business problem itself, then work backward to determine whether the environment can support AI.

“If you don’t have the right infrastructure, if you don’t have the right security, if you don’t have the right data, you're not going to be able to take advantage of the technology changes that AI is bringing,” Russell said.

In many cases, the basics act as the real constraints. That’s because AI doesn’t just sit on top of existing systems, rather, it changes the demands placed on them. Russell pointed to a shift from variable, user-driven workloads to far more constant and resource-intensive ones.

“With AI agents, that usage becomes much more persistent and puts different stress and other requirements on the infrastructure and backbones to support the business,” she said.

That forces partners to consider which product to deploy and whether the foundation can support what’s coming.

“We talk about this concept of AI-ready infrastructure, and it means that the compute, the network, the storage can handle the AI workloads without performance degradation,” Russell explained. “It’s a pretty high bar because most traditional enterprise infrastructure was not built to meet that need. If you think about a business user, you know their demand could be spiky, and there's lots of variability in that performance and that usage of all those resources. But today, with AI agents, that usage becomes much more persistent and puts different stress and other requirements on the infrastructure and backbones to support the business.”

Channel changes

All of this puts channel service providers, including agents who traditionally sell network capacity, into a different position. Instead of responding to defined requirements, partners are being called upon to guide customers through sequencing, tradeoffs and long-term implications.

“Customers need to demand that full cycle, that full picture of AI and what that looks like versus point solutions,” Russell said. “That expectation leaves less room for transactional models. … [T]he days of just schlepping product and saying, ‘I'm going to provide this to you,’ are over.”

Indeed, organizations can’t just buy AI off the shelf. “That's not the way that AI is working,” Russell said. 

Here, partners can help organizations – and CIOs, especially – to understand the security, governance, business model and human component of building AI into the environment.

“It’s a scary time for them,” Russell said of CIOs. As such, it’s imperative that channel partners serve as the “trusted advisor.”

“[S]it down with [the CIOs] and say, ‘You're not alone in this journey. You don't have to have all the answers. I'm going to help step through this journey with you,’” Russell said. “That’s a fundamental shift from maybe how some vendors [and partners] were perceived before.”

CBTS said its new Forge AI framework reflects that ethos, combining advisory, data readiness, engineering and managed services into a single engagement model rather than treating them as separate motions.

CIO pressure points

Again, the weight of AI lands most heavily on CIOs. Russell said it is similar to what CIOs faced when cloud computing became the hottest must-have.

“Cloud is a story about where compute happens, and AI is a story about where work happens,” Russell said. “Because a lot of companies and boards and CEOs are saying, ‘I don't know what it is, but we have to do it, we have to do AI,’ they turn to the CIO and they say, ‘Go implement AI.’ Then the next question is, ‘Okay, where's the return on that investment, and how much is it going to cost?’ You need to shift dollars from this bucket over to this bucket to pay for it. And so the amount of load that the CIO is carrying in this AI transformation is pretty extensive.”

CIOs are urged to move, often before organizations are even capable of supporting AI.

“AI is probably the loudest technology transformation as it pertains to the boardroom,” Russell said.

Augmented intelligence

Amid the urgency surrounding AI, Russell jumps in to reframe current thinking about it.

“I wish we would have called it augmented intelligence instead of artificial,” she said. “Because there's actually no artificial intelligence. It's about, how do we use technology to help humans do what they only can do?”

Again, the call for channel partner guidance is loud. AI is removing the traditional model of delivering discrete solutions with one where outcomes depend on how everything fits together. This forces partners to rethink how they operate internally and with customers and across the lifecycle of every engagement. The combination adds great pressure, but offers immense opportunity.

“There’s never been a more important time in technology for channel partners to step up and serve customers,” Russell said.