IBM tweaked investor anxieties last week with a cautionary note from CEO Arvind Krishna noting a steeper than anticipated year-over-year decline in the company’s infrastructure segment revenues. With Q2 2026 earnings just a week away, Krishna said customers had diverted capital investments from mainframes to server, storage and memory hardware as component prices spiked.
The company’s stock value tumbled, despite record growth in IBM’s distributed infrastructure segment, which includes hybrid cloud, storage and edge compute.
Mainframe malaise is nothing new. The cloud loomed as an existential threat to the platform for more than a decade before hyperscalers acknowledged hybrid strategies were an enterprise norm. More recently, LLM assistants trained to refactor legacy COBOL code sent mixed signals into the mainframe community.
“We went through a little bubble where the talk was that AI will help translate COBOL, therefore all mainframes will go away,” Brian Klingbeil, chief strategy officer at managed service provider Ensono, told Channel Dive. “Then people started to realize that AI also remediates the weaknesses of the platform and makes it an obvious place for storage. Now you can modernize the mainframe and make it more agile.”
Klingbeil likened the platform to Apple’s iPhone. “It’s a purpose-built piece of integrated soup-to-nuts hardware that is deeply integrated with IBM’s z/OS operating system,” he said. “The iPhone is a wonderful piece of high-end hardware that is highly performant and secure and deeply integrated with iOS.”
Ensono built a solid business around hybrid cloud management. The MSP touted $1.1 billion in annual revenue and a base of more than 250 clients on its tenth anniversary in January. Klingbeil estimated that recurring revenue from service offers comprise roughly 85% of Ensono’s business. The other 15% is project based.
“When there's a large enterprise that has a big transformational aspiration, we get a lot of phone calls from the big systems integrators who want the deal and don't have mainframe capabilities,” Klingbeil said.
Mainframe modernization expertise has opened the door to broader opportunities for Ensono.
“I want access to other parts of the IT estate because I’m not just a mainframe provider,” Klingbeil said. “I know we’re known for it and it’s hard to get out of that box sometimes, but mainframe services are only 67% of my revenue.”
Mainframing AI
While the race to deploy AI capabilities started in the cloud,many enterprises are reconsidering on-premises infrastructure to cap costs and secure data. Organizations aiming to migrate off mainframes may also be overly optimistic about the process.
More than 70% of mainframe exits initiated this year are expected to fail, according to a Gartner report published in June.
“The right mainframe strategy depends heavily on the profile and complexity of an organization’s environment,” VP Analyst Alessandro Galimberti said in the report. “For many mainframe customers, GenAI can be more effectively used to enable modernization in place rather than accelerate migration off the platform.”
Ensono has a similar perspective that predates the current AI craze.
“The mainframe is ideally suited for certain workloads that either cannot be replicated in cloud or would cost three times as much,” Klingbeil said. “When it's the right thing to move off the platform, we do it. When it's the right thing to modernize on it, that's what we do.”
As AI costs and data security concerns mount, hardware vendors and distributors expect hybrid strategies to remain entrenched. TD Synnex CEO Patrick Zammit told Channel Dive that the shift from AI subscriptions to token-based billing may be a tipping point.
“I’m at the point where I’m saying hardware could become sexy again,” Zammit said.
Klingbeil added that AI pricing has become a pain point for Ensono.
“It’s confusing as hell,” he said. “What the hell is a token, and why do they cost different amounts of money, and which one's good, and what did I get out of it?”
AI is also a potential boon for the MSP industry. Providers are using the technology internally while also helping clients deploy use cases.
Ensono jumped into the fray last year, investing $250 million in an AI innovation unit. The company developed a predictive analytics tool to prevent hardware failures, a diagnostic AI assistant to help its teams identify and address tech problems and an AI application called Change Guardian that assesses IT risks.
Klingbeil said the company has halved the time it takes teams to work through IT help tickets. The key to making it work is a data platform that the company invested a year in building.
“Without good quality data the only thing you'll get from AI is the ability to make mistakes with more confidence,” Klingbeil said.
