Artificial intelligence (AI) skills are no longer limited to technical roles. As employers work to keep pace with advances in technology, they are seeking candidates with AI skills across a growing range of positions, according to LinkedIn’s Future of Recruiting 2025 report. Finding those candidates calls for a different approach than traditional hiring, since degrees and job titles often fail to show who has real AI experience.
The challenge is also one of clarity, and the target is moving. According to Workday’s October 2026 Global Workforce Report, demand for basic AI skills such as simple prompting peaked in job postings in January 2026 and then fell 25%, while demand for hands-on skills such as building AI tools, automating workflows and AI engineering rose 51% between September 2025 and July 2026. In other words, employers increasingly want people who can build with AI, not just use it.
Understanding which skills matter for each role and how to identify them can help organizations recruit with more confidence. This article outlines desired AI competencies employers can look for, as well as steps to strengthen the recruiting process.
Desired Employee AI Skills
Basic AI fluency is quickly becoming an assumption instead of a selling point. The Workday report suggests that employers increasingly expect candidates to arrive with that foundation. Understanding what AI tools can and cannot do, and using them in everyday work, is now the starting point for most roles.
The value of these skills also varies by industry. For example, in construction and manufacturing, AI skills can show up in practical tasks such as building an inventory tracker, standardizing item names across supplier lists, or turning voice-dictated shift reports and daily logs into clear documentation. Judgment carries added weight in these settings, since answers involving safety, load, electrical or code requirements should be verified against the manual or a qualified person, and sensitive information (e.g., customer data, proprietary drawings and pricing) should stay out of public AI tools. Similarly, nonprofits, which often rely on small teams with broad responsibilities, can benefit from candidates who apply AI to practical needs such as accessibility, communications and reporting.
What employers are looking for beyond that baseline is more complex. Accurate skills assessment is central to finding it, and LinkedIn reports that 93% of talent acquisition professionals believe accurately assessing a candidate’s skills is crucial for improving the quality of hire. The following AI skills and competencies are the ones that today’s employers are often seeking:
- Hands-on AI skills—Building AI tools, automating workflows and AI engineering are some of the fastest-growing skills. Some of these skills, such as workflow automation, can apply well beyond engineering roles, reaching operations and supply chain teams in manufacturing and construction, as well as program and administrative staff at nonprofits.
- Practical application—Candidates are increasingly using AI to build real things, such as a website without a coding background, a tool that improves accessibility or an analysis of social media performance. These examples show candidates solving real problems, which is stronger evidence than a list of tools.
- Judgment—Knowing where AI helps, where it falls short and which decisions belong to the person is key. Employers are now asking candidates what they’ve decided for themselves.
- Learning agility—Because AI tools change quickly, the ability to learn fast often matters more than any single credential. A record of projects, certifications and self-directed learning can show it, and candidates with real AI experience can usually name the specific concepts, tools or practices they have used.
- Human skills—People excel at critical thinking and creative problem-solving, and human skills such as communication are often better developed through real-world experience. Task-based assessments can help gauge adaptability and problem-solving.
Employer Considerations
Knowing what to look for is only part of the process. Finding and winning candidates with AI skills also depends on how organizations write job descriptions, screen applicants, conduct interviews and present themselves. Competition is strong, and Handshake reports that early-career candidates with AI experience receive nearly twice as much employer outreach as their peers without AI experience.
The following strategies can help organizations find candidates with AI skills at every stage of hiring:
- Define the skills for each role. Write specific, measurable AI skills in job descriptions rather than broad terms such as “AI experience.”
- Look past majors and degrees. Nearly two-thirds of early-career candidates with AI experience are not computer science majors, according to Handshake. Screen for projects, certifications and self-directed learning.
- Ask candidates to explain their work. Handshake found that more than 4 in 5 early-career candidates with AI experience list a specific AI concept, tool or practice on their profiles, so specifics alone do not distinguish strong candidates from the rest. Questions can cover the problem being solved, why the approach was chosen, where AI fell short and which decisions the candidate made independently.
- Test application, not just familiarity. Use skills assessments, problem-solving exercises or simulations, and consider allowing AI tools in assignments while evaluating the quality of the output.
- Standardize interviews. Structured questions that focus on skills help keep the evaluation consistent and reduce bias.
- Show where AI creates value. Explain in job postings and interviews how teams use AI today and where new hires can keep learning.
- Develop internal talent. Workday notes that AI can identify employees with transferable skills, and targeted upskilling can fill roles faster than external hiring. Deloitte reports that skills-based organizations are 79% more likely to provide a positive workforce experience.
- Keep fairness and oversight in place. Audit AI recruiting tools for bias, keep recruiters involved in final decisions and document how decisions are made.
Conclusion
As AI becomes part of more roles, the ability to find and evaluate AI skills is becoming a core recruiting capability. Even for roles that may not have relied heavily on technology in the past, basic AI skills and literacy are becoming increasingly relevant. Organizations that define the skills each role requires, look beyond traditional credentials and assess how candidates apply AI in practice are better positioned to identify talent that others overlook. Pairing that approach with internal development, fairness checks and human judgment can help employers build teams that are ready for continued change.
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This HR Insights is not intended to be exhaustive nor should any discussion or opinions be construed as professional advice. © 2026 Zywave, Inc. All rights reserved.
