AI experience is the hottest IT hiring need. What if you don’t have much?

AI has quickly become a top skill on the IT talent market, with 91% of IT leaders prioritizing AI expertise when hiring this year, according to recent survey from AI analytics vendor Reveal. Eight in 10 of tech leaders reported using AI in software development and 77% said expanding AI use throughout the organization is a top strategic goal for 2026.

However, as typically happens when there’s a rush to adopt any emerging tech, the talent market often can’t keep pace, creating a talent gap around these new, in-demand skills. According to Reveal, 50% of organizations already cite difficulties in “recruiting and retraining skilled technical staff,” while 80% say the shortage is directly impacting the organization’s operations and ability to act on AI projects — a challenge confirmed by CIO.com’s 2026 State of the CIO Survey.

While the talent market takes time to meet the demand, leaders will likely be looking to prioritize candidates who show a mix of technical, business, and communication skills as that can help “bridge the gap between AI output and actual results,” says Kareem Osman, VP and market director of technology talent solutions at Robert Half.

Highlighting valuable technical skills for AI

While concerns around AI-related layoffs and job displacement are rising, 48% of Reveal survey respondents say they have instead seen AI-related job creation, while 18% reported layoffs — further indication that AI is reshaping the job landscape in conflicting ways.

As these new jobs arise, filling them requires a flexible understanding of the concept of AI experience, which can range from proven hands-on experience with AI tools and services, to AI-adjacent knowledge of relevant programming languages, cybersecurity, or other relevant skills.

“Many companies are still experimenting with AI, so ‘experience’ can come from a mix of formal credentials and hands-on use cases — that could be examples of saving time, improving decision-making, or creating more effective outputs. What stands out right now is the ability to interpret AI results and apply judgment. It’s not just about the tools you’re familiar with but more about how you’ve used it to improve real work,” says Osman.

Job descriptions and listings will give a better idea of what a company is looking for, but according to Reveal, the most sought-after technical skills include Python (56%), machine learning (47%), Java (34%), and cybersecurity (33%), along with C/C++, SQL, .NET, JavaScript frameworks, and web development. The report points out that smaller organizations tend to look for C/C++ and cybersecurity skills for infrastructure needs, whereas larger organizations are more likely to emphasize a need for Python and AI-specific skills.

“Tech roles today are much more connected and less siloed, so drawing a clear line between past IT experience and AI applications can really strengthen a resume,” says Osman.

Demonstrating AI or AI-adjacent experience

Despite being a relatively new technology, companies are eager to hire talented workers with experience or expertise with AI and AI-powered tools. The hardest-to-fill tech role, according to Reveal’s data, is AI engineer (39%), followed by cybersecurity engineers (38%) as AI raises concerns around privacy and compliance.

If you aren’t an AI engineer or you don’t have cybersecurity experience, there are other opportunities to highlight relevant skills on your resume that translate well to AI skills or demonstrate you are eager to upskill. Robert Half’s Osman recommends highlighting any projects or workflows where you’ve used AI, explaining what the problem was, how you and your team used AI to address it, and the ultimate results.

“When it comes to AI, employers are placing more value on practical application and clear thinking than just years of experience. Even one strong example of AI application in your work can go a long way, so it’s worth digging into if it aligns with the role,” he says.

Emphasize work experience that shows you know how to improve workflows, translate technical concepts, communicate across teams, or solve business problems strategically. Demonstrate instances where you’ve helped your organization save time, improved outputs or decision-making, refined processes, met or reduced budgets, collaborated across different business units, and other similar examples to show that you understand the overall goal of AI implementation is to improve productivity and efficiency.

“Highlight the things that make a recruiter want to find out more. That could be examples of saving time, improving decision-making, or creating more effective outputs. What stands out right now is the ability to interpret AI results and apply judgment. It’s not just about the tools you’re familiar with but more about how you’ve used it to improve real work,” says Osman.