Build or buy? Smart CIOs know the answer for AI talent

The key ingredient for successful AI deployment is largely becoming the talent available, not the AI tools installed, putting pressure on IT leaders to upskill their workforces.

With AI skills both the highest in demand and the hardest to hire for, many IT leaders and their C-suite colleagues are rolling out comprehensive AI training programs for employees, both for the IT pros who build AI tools and the business users who will use them.

Smart companies will need to invest heavily in upskilling, says Chris Campbell, CIO at DeVry University. “The pace of change is simply too fast to rely solely on external hiring,” he says. “Organizations that develop AI capabilities across their existing workforce will have an advantage over those trying to win a bidding war for a relatively small pool of experts.”

Moreover, the key elements of what leads to a beneficial AI deployment has changed over time, he says.

“Early on, everyone was worried about access to AI tools,” Campbell adds. “Today, the tools are everywhere. What I see organizations struggling with is figuring out how to apply them to real business problems and integrate them into how work actually gets done.”

At DeVry, some of the strongest AI advocates don’t come from traditional AI backgrounds, but from software engineering, business analysis, cybersecurity, project management, and operations, he says.

“They understand the business, know where the friction points are, and can see where AI can create value,” he adds. “Those skills are often more important than deep expertise in a particular model or tool.”

Experienced AI talent is difficult to find, especially when IT leaders seek candidates who have successfully transitioned AI initiatives from experimentation to production.

“I don’t think every company needs to build a large team of AI specialists,” Campbell says. “In many cases, the people best positioned to drive AI adoption are already inside the organization.”

Upskilling for an AI builder culture

Professional services and accounting firm KPMG is addressing its AI talent challenge by providing widespread AI training to employees, says Rema Serafi, vice chairwoman for tax operations there. Many organizations’ major AI problem in 2026 is a lack of talent, not a lack of technology, she adds.

Forty percent of CIOs surveyed for this year’s State of the CIO report cited lack of in-house talent as a top impediment to implementing their AI strategies.

To address this, KPMG has piloted a six-week AI training program, with the goal of enabling all employees to deploy their own AI tools, Serafi says. The program familiarizes employees with Python and other technologies that serve as building blocks for internal AI tools, she says.

KPMG also revamped its team structures to ensure that three categories of employees — AI power users, makers, and builders — work closely together, says Serafi.

“Everyone’s going to have access to our tools, and everyone’s going to be a power user,” she says, “to the extent that those professionals who didn’t come in with AI capabilities, who didn’t come in as engineers or technologists, if they want to learn, we’re going to certify them to build tools as well.”

Deploying sophisticated, best-in-class AI tools without training employees is like buying an F1 racing car but not hiring a professional driver, she says.

“If we don’t have professionals who know how to use it, they’re not going to be able to maximize the benefit of what’s available to them,” Serafi adds.

KPMG commissioned a study with the University of Texas and found that employees who use AI regularly produce higher-quality work and feel less stressed. Employees who are expert users of AI will progress faster in their careers, she suggests. One challenge for training programs, though, is keeping up with how fast AI is evolving.

“The roles are actually changing in a short period of time,” she says. “When you used to see traditional engineers working with AI, now you see professionals who can actually guide, shape, and direct AI in their client work.”

Retraining: ‘The only realistic path forward’

Another fan of comprehensive AI training for employees is Elmer Morales, founder and CEO of agentic AI coding startup koder.com. Finding outside AI talent has become extremely difficult for most companies, he says.

“Retraining isn’t optional anymore,” he says. “It’s the only realistic path forward for most organizations. The external talent market can’t supply what every company simultaneously needs, and waiting for universities to catch up isn’t a strategy.”

Companies that succeed with AI treat upskilling as a core investment, not just an HR initiative, Morales adds.

“The talent gap is the single most concrete ceiling on AI ambition right now,” he says. “Companies can buy the best models, the best infrastructure, and the best tooling, and still produce nothing of value because they don’t have the people who know how to wire it all together into something that actually works in production.”

Morales suggests that IT leaders look to their existing engineering team to build AI deployment talent.

“The engineers already obsessed with this on nights and weekends, who are shipping personal projects and experimenting with new models, those people just need permission, resources, and a real problem to solve,” he says. “The best AI teams I’ve seen weren’t built by recruiting, but by creating the conditions for the right people to step forward.”