Longtime IT leader Matt Ausman envisions a future where developers may not have any backlog because AI will let them create new capabilities as quickly as they imagine them.
“The backlog will vanish because you will have infinite capacity,” says Ausman, SVP and CIO of Zebra Technologies.
He wonders whether business users will be able to keep up with the training required in a world where the software they use will change that rapidly. He also wonders whether IT workers are ready for that scenario: Will they be able to push back on bad ideas, or just build new capabilities simply because they can do so as rapidly as they’re proposed?
“Today we have to prioritize because we don’t have unlimited capacity. But in the future will they stop to ask, ‘Are we building the right things?’” he says, adding that “because someone thought it up, doesn’t mean it’s worth doing.”
Ausman acknowledges that such a reality is at least several years out, but he already sees AI changing how his IT team works, the work they need to do, and the skills required to do it.
For example, the average size of Scrum teams is shrinking, dropping from eight people to five or six who are producing more thanks to AI. Ausman believes Scrum teams may eventually be made up of two members: a functional product owner and a technical product owner who together use AI to gather requirements, generate mockups, create code, and so on, spending the bulk of their time supervising agents tasked with ensuring the architecture is right, bugs are fixed, security is in place, and the like.
Ausman also sees IT teams of the future producing work faster and drawing more from their business domain knowledge and less from their deep technical skills as they use AI to remake processes and workflows throughout the organization as well as in IT.
A shift in skills and mentality
These shifts will change not only how IT teams are structured but also the skills IT workers need, Ausman and other IT leaders and experts say.
True expertise in business domains, once merely a differentiator, is fast becoming a must-have for IT pros, Ausman notes. So is discernment (the ability to recognize when ideas aren’t worth pursuing), conviction (the ability to tell others that those ideas won’t produce benefits), and communication (the ability to be clear, concise, and diplomatic when telling others as much).
“They’ll need to be good partners to [the business] and be able to ask, ‘Are you sure we should do this thing?’” Ausman explains.
Of course, IT workers will continue to need technical skills, Ausman says, noting that most of his hiring today is for entry-level positions that draw in AI natives who help spread their AI knowledge throughout the enterprise. Still, he questions whether earning a computer science degree and knowing multiple programming languages will be as valuable 10 years into the future as they were a decade ago.
Problem-solving skills will be more highly prized in IT workers instead, he says. Emotional intelligence, authentic leadership, decision-making capabilities, and prioritization skills will also be in high demand.
“I think about my team and the fact that we can never outsource team care, the ability to have difficult conversations, emotional intelligence, [provide] psychological safety. Those things can never be automated,” he adds.
‘Hyperacceleration of learning needs’
CIOs across all industries are beginning to adjust their IT organizations in response to these evolving and anticipated changes as they contemplate the future of their IT workforces.
In a poll of CIOs at this year’s CIO 100 Awards and Conference in August, “talent, skills, and organizational change” topped the list of issues worrying CIOs, with 33% citing it. That put it ahead of “demonstrating AI business value and ROI” (27%) and “budget pressures and competing priorities” (21%).
When asked which capability will define the next generation of CIOs, 29% said “building organizational talent” — just behind “leading AI transformation” (30%) and ahead of “developing business strategy” (22%).
AI is obviously a factor here, as its use expands to automate more core IT tasks, but AI is only one of the dynamics driving change in IT. Demographics, market conditions, industry trends, and economics have all put pressure on organizations to be more responsive through the use of technology, says James Stanger, chief technology evangelist at CompTIA, an IT training and certification association.
Even as IT leaders feel the pressure of those dynamics, CIOs must also be ready to capitalize or respond to evolving technology as rapidly as it hits the market, Stanger adds. That puts further pressure on CIOs to rework their IT departments so that they’re able to meet such expectations.
Leading CIOs “have realized that technology is changing so utterly fast and because of that they need to change their organizations,” Stanger adds. “We’re finding that the traditional ways of doing things are being revised.”
Although most CIOs aren’t making radical changes yet, they are adjusting their approaches and the structure of their IT departments, Stanger notes.
CIOs are implementing more training initiatives and requirements to ensure their teams are better keeping pace with the changing tech landscape, Stanger says, noting that many CIOs have shifted from seeing training as a retention tool or a nice-to-have to something essential for enterprise survival.
And that commitment to learning is increasingly being incorporated into the day to day. “Microlearning is becoming more of a thing; there’s more of a steady stream,” he observes, adding that microlearning is beneficial because it can happen as rapidly as technology changes and accelerates hands-on retention of what is learned.
CIOs are also enlisting more talent from the business side to help develop technology solutions. These aren’t the citizen developers of yesterday, Stanger says, as they now often report via dotted lines to IT managers, allowing CIOs “to get a really good sense of what’s going on in those departments and what’s working and what is not.”
Conal Gallagher, CIO and CISO of Flexera, is leaning heavily into training to ensure his staffers have the skills necessary for the software maker to thrive.
AI fluency and AI use is at the top of Gallagher’s training list, as is AI administration and governance so that his staff can create AI tools that workers in other departments can safely use. And he’s working to develop more agentic AI skills among his workforce.
Like Stanger, Gallagher calls out the “hyperacceleration of learning needs” today, saying that most IT professionals are learning as they go, sometimes turning to online videos for instantaneous education.
The fast pace of technology evolution, however, makes it difficult to predict what will be needed from his IT workers a year from now. As a result, longer-term coursework is becoming less valuable.
“Traditional training as we know it probably doesn’t apply anymore,” he says, adding that the goal now may be to “just keep pace with the current.”
Reinventing roles to maximize IT capacity
Info-Tech Research Group’s 2026 IT Talent Trends report shows that IT leaders and IT pros alike expect nothing short of wholesale change for IT ahead. Nearly nine of 10 (89%) IT leaders anticipate restructuring their IT organization, according to the survey, and 95% of IT professionals acknowledge major skill changes would be required to keep pace with technology by 2030.
To help bridge IT to the future, CIOs are adding more service owners (the modern version of product owners) and business relationship managers, says Brittany Lutes, research director in Info-Tech’s CIO practice. IT leaders view these roles as essential for delivering AI and other IT capabilities that create value for the business.
“If they didn’t have them, they’re adding them,” she says. “If they had these roles before, they have more now.”
CIOs are also creating broader roles that enlist staff to operate in multiple domains, Lutes says. A networking engineer may now be expected to work in database administration and database engineering, for example.
CIOs want their teams to be more flexible and more modular, so they can move personnel more easily to where work needs to be done. To achieve that, some CIOs are grouping workers in pools or centers of excellence and then assigning them out as needed.
Broadening IT roles also helps keep those positions working at full capacity as AI picks up more of the manual tasks previously assigned to IT pros working as specialists.
“CIOs are not losing headcount, but the way they’re your utilizing that headcount is changing,” Lutes says, pointing out that these dynamics are changing job titles, too. For example, one IT organization Lutes knows of changed the all its IT workers’ titles to simply “engineer.”
Leading CIOs are also creating new roles centered around AI implementation and management, Lutes notes. These new roles include decision intelligence lead; forward-deployed engineer; human-AI interaction lead; knowledge engineer; master data manager; memory engineer; MLOps engineer; prompt engineer; synthetic data engineer; and trust engineer.
The seemingly contradictory trends reflect a profession in flux.
“We’re still in a messy phase as an industry,” Lutes says. “We’re not going to get to that major shift in the next two years, but five years out we may see a complete restructuring of the IT organization.”
Preparing for the future state
Nick Nadgauda, global CIO of MetLife, is preparing for that future state.
“We continually evaluate whether we have the right blend of engineering depth, business understanding, adaptability, and leadership,” he says. “The goal is not simply to fill today’s roles; it is to build a workforce that can learn, unlearn, and relearn as the work changes. That includes building a strong early-career pipeline and giving emerging technologists the technical foundations, mentoring, and hands-on experience to grow with the organization.”
This ongoing evaluation has reinforced three priorities at MetLife, Nadgauda says.
“First, AI fluency needs to become a broad workforce capability, not a specialty confined to a small group. Second, strong fundamentals in software engineering, cloud, cybersecurity, data, and architecture remain essential. We’re putting an emphasis on making our organization more technical. Third, we need teams organized around clearer accountability and closer alignment to business outcomes,” he says.
Nadgauda is investing in continuous role-based learning, creating more opportunities for hands-on learning, and bringing critical expertise in-house.
But he also acknowledges a degree of uncertainty about what’s ahead for IT, saying, “We can predict the direction more confidently than the exact destination.”
He adds, “We know AI will become a natural part of how work gets done across engineering, operations, and customer-facing teams. We also know that judgment, creativity, accountability, and deep domain expertise will remain critical. What is less certain is how quickly individual tasks and roles will change. That is why adaptability matters so much. The best hedge against uncertainty is a workforce that can learn continuously, experiment responsibly, and apply new capabilities to real business problems.”