IT leaders prioritize addressing AI skill concerns

Recent data from the CompTIA Tech Jobs Report shows that tech jobs have seen a drop in unemployment, down to 3.1% in May from 3.5% in April, accounting for an increase of around 6,700 in May. Roles that saw the highest demand include software developers and engineers, systems engineers and architects, tech support specialists, cybersecurity engineers and analysts, and AI engineers.

And according to projections form the U.S. Bureau of Labor Statistics, the tech workforce is anticipated to grow twice as fast as the overall US workforce, with an expected replacement rate of 6% annually, or approximately 323,000 workers, for tech occupations between 2024 and 2034.

“More than ever, business success relies on technology,” said Seth Robinson, VP of  industry research at CompTIA. “Our research has shown a desire to build capability in core operational functions, which then allows companies to build advanced practices in AI, data, and cybersecurity.”Further data, this time from the CompTIA Sate of the Tech Workforce 2026 report, shows that 83% of IT leaders and HR professionals say their organizations are placing a high or moderately high priority on addressing skill concerns, and 62% say they expect the budget for AI training to increase in the next year. Organizations also seem to recognize the impact that skills development can have on employees, with 83% saying they expect these investments to have a high or moderate degree of impact on employee morale and engagement.

Cause and effect

There are two main factors driving the skills gap and pushing IT leaders to invest in training programs: AI accelerating technological change, and a shortage of AI skilled professionals in the hiring market. However, while AI is a main driver in the skills gap, 48% of IT leaders also say AI is crowding out other important needs, including a much-needed shift to skills-based hiring methodologies.

IT leaders are looking to build training programs that specifically address AI basics, data analysis, AI threat awareness, automation, data preparation, securing AI systems, building inputs and prompts, and creating AI agents. Currently IT leaders cite cost of training, training fatigue, turnover, lack of executive support, difficulty measuring ROI, and stale training curriculum as some of the biggest challenges when developing training programs, according to CompTIA.

So organizations that embark on upskilling and training will need a robust strategy in place to ensure employees take advantage of the training and remain engaged. Leaders will also need to set the expectations for how to integrate training into daily work, so they aren’t left feeling overwhelmed by the process on top of their current roles.

“What we’ve found that works is to embed AI into people’s workflows after the initial training, and pair people with colleagues who are further along in their AI utilization,” says Maruf Ahmed, CEO of IT solutions provider Dexian. “The gap between ‘I attended the training’ and ‘I’m actually using this differently in my job’ is where companies lose people, and closing it takes more than a single training cycle.”