How CIO consider AI fashions

Anthropic captured the lead in U.S. enterprise AI adoption, securing 34.4% of the market in comparison with OpenAI’s 32.3%, in response to Ramp 2026 AI Index in Might. Amongst companies adopting AI for the primary time, Anthropic is successful roughly 70% of head-to-head matchups.

“Anthropic gained early with the individuals who had been already making an attempt AI inside firms,” stated Ara Kharazian, lead economist at Ramp. He stated these early adopters have been “a superb main indicator of the place the remainder of the market goes.”

The shift marks a milestone within the AI platform wars. However for CIOs making shopping for choices, the leaderboard has by no means been the primary occasion.

“I might watch out on the head-to-head,” stated Phil Leslie, chief expertise and innovation officer at Cornerstone Analysis, an financial and monetary consulting agency that helps high-stakes litigation. “The variations among the many main frontier fashions are actual however slender, and so they maintain transferring. The extra helpful query shouldn’t be ‘which mannequin is greatest this quarter’ however ‘which setup lets us change because the frontier shifts.'”

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That pragmatism is widespread. Because the AI mannequin race intensifies, CIOs say they’re focusing much less on selecting a winner and extra on constructing architectures that do not drive them to.

Safety first, all the things else second

Earlier than efficiency, pricing, or options enter the dialog, CIOs say AI platforms should first cross safety and governance assessments.

“Our work is determined by strict consumer confidentiality, so a platform has to clear a number of non-negotiable bars earlier than it’s even a candidate,” Leslie stated. “Shopper knowledge isn’t used to coach fashions, interactions are usually not uncovered to human overview, and knowledge stays on U.S. infrastructure. These constraints outline the possible set; all the things else is a selection inside it.”

Eric Tempo, head of AI at Cox Enterprise, the industrial companies division of Cox Communications, put it equally.

“Safety is non-negotiable for us,” Tempo stated. “Given the quantity of essential infrastructure we handle, we now have to start out with threat and whether or not an answer suits inside our safety, authorized, knowledge privateness and governance necessities. If it introduces dangers that we might not be comfy standing behind, it isn’t value pursuing.”

At Lowenstein Sandler, a nationwide legislation agency, the bar is simply as excessive. “Safety and confidentiality aren’t one issue amongst a number of,” stated the agency’s chief info and innovation officer, Maureen Naughton. “They are the edge check.”

The mannequin is not the moat

With safety and governance necessities met, CIOs say efficiency issues — however not in the best way a lot vendor advertising and marketing suggests. The hole between main fashions is skinny and consistently shifting. Betting on in the present day’s benchmark winner is a short-term play at greatest.

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“The sturdy benefit was by no means the mannequin — the fashions are the straightforward half,” stated Jeremy Bruck, companion at administration and expertise consulting agency West Monroe. “The benefit is in an organization’s knowledge belongings, context, workflows, controls, and how briskly they can flip a sign into motion.”

Cornerstone Analysis constructed a model-agnostic stack on objective. “The frontier is transferring too quick to wire our structure to any single vendor; the lock-in threat is actual, and the hole that appears decisive in the present day could also be gone in two quarters,” Leslie stated.

Fairly than selecting a single winner, a number of CIOs describe operating a portfolio of AI platforms matched to totally different use circumstances.

A number of fashions serving distinct roles

“We do not method this as selecting a single winner,” stated Naughton of Lowenstein Sandler. “We consider them as occupying distinct lanes somewhat than competing for one seat.”

This method is changing into the norm. “The continual mannequin leapfrogging has helped firms settle for that the speed of change is just going to speed up,” stated West Monroe’s Bruck. “Firms are now not centered on ‘smartest mannequin’ however as an alternative on modular platforms that scale back switching prices as new options emerge.”

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Ramp’s Kharazian sees the identical sample in spending knowledge. “The analysis is transferring from ‘Which AI vendor ought to we use?’ to ‘Which mannequin ought to do that job, at what value?'” he stated. “That pushes firms towards multi-vendor setups, routing, open supply fashions, and inference platforms.”

Freedom inside a framework

Developer enthusiasm has been the driving drive behind AI adoption. However CIOs say that bottom-up demand works greatest when there are AI guardrails in place.

Tempo of Cox Enterprise describes the method as “freedom inside a framework.” The corporate offers a ruled set of mannequin choices throughout on-prem and cloud environments, and inside that framework, groups have flexibility to decide on what works greatest for his or her use case.

“Developer choice does play a job, significantly in mannequin choice,” Tempo stated. “The bottom line is that every one of this occurs inside a broader governance framework that we view as an enabler, not a constraint”

The dynamic is analogous at Cornerstone Analysis. “Our knowledge scientists are robust and opinionated; they run their very own evaluations and maintain actual views on mannequin efficiency,” Leslie stated. “That enter is indispensable.”

However a full analysis additionally requires IT to evaluate safety and authorized to vet confidentiality phrases — and people evaluations do not occur on their very own. “The job of management is to not overrule the technical judgment effervescent up from the workforce,” Leslie argued. “It is to ensure the entire analysis really occurs.”

At Lowenstein Sandler, Naughton frames it as a design precept: “The healthiest model of that is governance setting the boundaries,” she stated, “and the entrance line driving the priorities.”

Watching the meter: How CIOs handle consumption

Governance solves one downside. Prices create one other.

“AI is the fastest-growing spend class we have ever noticed,” stated Ramp’s Kharazian. “The typical enterprise is spending 13x extra on tokens than it was in January 2025.”

Utilization-based pricing means CIOs can see precisely what they’re spending, however not all the time what they’re getting for it. As adoption scales, CIOs are growing new disciplines for managing consumption with out stifling worth.

The primary transfer, stated West Monroe’s Bruck, is tying spend to outcomes. “You’ll be able to’t handle what you’ll be able to’t attribute,” he saids, “so disciplined enterprises observe which workforce, workflow, and more and more which particular person is driving spend, tied to a unit of enterprise worth, earlier than they attempt to spend much less.”

Tempo takes a value-first method to value administration at Cox Enterprise. “When AI helps somebody work by means of years of backlog in weeks, the dialog shifts from controlling value to asking what extra we will allow,” he stated.

Kharazian sees three developments rising:

“Most firms are usually not making an attempt to gradual AI adoption,” Tempo stated. “They’re making an attempt to get the upside with out letting the invoice run away.”

What CIOs are asking now: AI mannequin analysis shifts from outputs to actions

A yr in the past, CIOs had been questioning whether or not AI instruments really labored. That query is basically settled.

“Our standards have matured towards integration depth, safety posture, governance match, and more and more readiness for extra agentic capabilities — that means instruments that take actions somewhat than simply generate textual content,” stated Naughton. “The bar has moved from novelty to sturdiness.”

When AI techniques can take actions, the analysis adjustments completely.

“As soon as a system can search the online, name exterior companies, write and run its personal code, it’s a must to ask a special class of query,” stated Cornerstone’s Leslie. “What guardrails exist? What can we cease it from doing inside the environment?”

The outdated check was about what the mannequin produces. “The brand new check can also be about what the mannequin does,” Leslie stated. “That could be a genuinely tougher downside.”

Mannequin choice nonetheless issues. However for CIOs, so does constructing structure that may adapt when the leaderboard flips once more — as a result of it’s going to.