What Is Skills-First Hiring in the Age of AI?

The case for skills-first hiring has gained attention across the business world. Harvard Business Review documented the rise of skills-based hiring in 2022. The Financial Times subsequently reported on employers including IBM, Google, Accenture, and McKinsey looking beyond traditional university pathways to find talent.

How is this movement impacted by AI given the huge changes that technology is bringing to the workforce? The World Economic Forum reports that employers expect 39% of workers’ core skills to change by 2030. Pew Research Center found that 73% of U.S. adults under 30 expect AI to reduce jobs over the next two decades. A separate 2026 Gallup survey found that 51% of Americans ages 14–29 use generative AI at least weekly, yet only 22% feel excited about it.

By the numbers

AI and the early-career workforce

39%

of workers’ core skills are expected to change by 2030

World Economic Forum, 2025

73%

of U.S. adults under 30 expect AI to reduce jobs over the next two decades

Pew Research Center, 2026

51% vs. 22%

of Americans ages 14–29 use generative AI weekly, vs. those who feel excited about it

Gallup, 2026

74%

of Gen Z use AI to some extent in their day-to-day work

Deloitte Gen Z and Millennial Survey, 2026

Skills-first hiring may actually offer an answer for how we can realize efficiency from AI but not eliminate early-career pipelines and alienate emerging talent. A skills-first approach today can help build an organization’s capabilities and resilience for a rapidly changing workforce landscape and also create a pathway for early-career talent to the future.

“The real question isn’t how AI will impact skills-first hiring, but how can skills-first create a pathway through a landscape shaped by AI?”

Hiring for Future-Forward Capabilities

Hiring often begins with a familiar, and usually outdated, job description and a search for someone who has done similar work before. When technology changes how that work gets done, employers need to reconsider which capabilities will produce desired business outcomes.

For example, a team using AI to prepare routine reports may spend fewer hours assembling information while needing greater ability to question findings, recognize missing context, and explain what the results mean. Searching primarily for years of experience producing those reports overlooks someone with the analytical, problem-solving, and communication skills needed for the work ahead.

Basic data literacy might be necessary before joining a team. But understanding the company’s systems, customers, and decision-making processes requires exposure and guidance.

Experience remains valuable, but employers should examine the capabilities behind it. Problem-solving, for example, can be seen in how a candidate approaches an unfamiliar situation, identifies missing information, or adjusts after receiving feedback. These kinds of skills are actually more valuable in leveraging AI because they depend less on entrenched processes and more on innovation and discernment.

Employers also need to distinguish between essential entry-point skills versus knowledge people can develop inside the organization. That distinction is especially important for early-career talent. If AI changes or reduces the routine assignments through which new employees once gained experience, employers need to create other opportunities to learn. Hiring for demonstrated capabilities, then providing supported opportunities to apply them, gives people a way into the workforce even as traditional entry-level roles evolve.

Hire for it

Entry-point capabilities

Analytical thinking Problem-solving Communication Basic data literacy

Grow it inside

Organizational know-how

The company’s systems Its customers Decision-making processes

A Practical Structure for Learning on the Job

Apprenticeships provide one practical structure for connecting those two stages. By combining paid work, instruction, and mentorship, they allow people to contribute while developing the capabilities an employer needs. A well-designed apprenticeship makes learning part of the employment relationship, with opportunities to apply new skills, receive feedback, and take on greater responsibility.

Paid work

Contribute from day one

+

Instruction

Build skills the role requires

+

Mentorship

Feedback and guidance

=

The capabilities employers need

Learning built into the employment relationship

That is a useful principle for any hiring decision, but particularly in the context of AI: understand what someone brings, what they will need to learn, and how the organization will support that learning.

Coaching Becomes Essential

AI can produce polished work before an employee fully understands the thinking behind it. A well-written recommendation might conceal an unsupported assumption. An accurate report may come from someone who cannot yet explain why a finding matters.

Coaching helps make that thinking visible. A manager can ask an employee to explain the evidence behind a recommendation, identify what they verified, or describe what would change their conclusion. These conversations develop judgment and connect an employee’s skills to the particulars of the business.

There is also evidence that AI can help people gain proficiency. A study published in The Quarterly Journal of Economics, examining more than 5,000 customer-support agents, found that less experienced and lower-skilled workers increased the number of issues resolved per hour by approximately 30% with AI assistance. The researchers also found evidence of learning. In that setting, AI helped newer workers benefit from knowledge embedded in the tool.

~30%

more issues resolved per hour by less experienced, lower-skilled workers using AI assistance

That possibility deserves attention alongside concerns about losing opportunities to learn. Employers can use technology to support development while helping employees understand, question, and apply what it provides.

At YUPRO Placement, our weekly Professional Development Hour (PDH) gives apprentices opportunities to strengthen communication, workplace effectiveness, and their understanding of emerging technology. Recent feedback from participants on an AI development session illustrates how that development connects to daily work.

“Ask questions, seek clarification, and communicate what I need to be successful.”— YUPRO Placement apprentice, Professional Development Hour

One participant described learning to “ask questions, seek clarification, and communicate what I need to be successful.” Another found that creating a growth plan and working with an accountability partner helped them stay on track. Participants also described the value of regular check-ins, honest feedback, and having someone available when challenges arose.

What apprentices said helped them grow

A personal growth plan

An accountability partner

Regular check-ins

Honest feedback

Support when challenges arise

Practical AI for daily work

Their AI learning had practical applications, too. One participant reported using AI to draft professional emails, organize projects, and prepare reports, which they said allowed more attention for problem-solving and relationship-building.

For employers, these examples make development concrete. Learning needs time, feedback, and opportunities for application. If AI reduces time spent on routine work, leaders should consider how some of that time can coach and train employees to prepare them for greater responsibility and greater opportunity.

Early-Career Talent Has a Role in Innovation

The discussion about young people and AI can overlook what they already bring to the workplace. Deloitte’s 2026 global survey reports that 74% of Gen Z respondents use AI to some extent in their day-to-day work. That familiarity gives employers a starting point for discovering capabilities and ideas they may not have expected.

Case Study: Sam Ebengho’s Internship

A Year Up United graduate, Sam joined an IT team and studied AI engineering during his long commute. Using Microsoft Power Automate alongside ServiceNow, he developed workflows that helped filter alerts and prioritize urgent tickets. His contribution addressed a practical problem the team faced in its daily work.

Sam’s skills that brought value included the ability to notice a problem, learn about possible solutions, and connect that learning to the team’s needs. His story gives employers a reason to look beyond the tasks initially assigned to an intern.

The problem

A flood of alerts

Sam’s solution

Power Automate + ServiceNow workflows

The result

Urgent tickets prioritized

Organizations can create opportunities for similar contributions by inviting newer employees to examine recurring problems and propose improvements. Experienced colleagues can provide context, help test assumptions, and evaluate results. Emerging talent gains meaningful responsibility while the organization benefits from their questions and experimentation.

This requires attention to individuals. The PDH feedback mentioned earlier included regular AI users, people still exploring its applications, and someone who preferred not to use it. Age alone does not establish proficiency. Employers need to understand the skills and interests people actually bring, then give them appropriate opportunities to contribute.

Build the Experience Your Organization Needs

Skills-first hiring creates a pathway through a workplace shaped by AI by connecting what people can do today with opportunities to develop the capabilities employers will need tomorrow. For early-career talent, that means employers recognizing potential beyond prior job titles and providing meaningful work through which to build experience.

Hiring is the starting point. Apprenticeships, coaching, and opportunities to solve real business problems turn that initial access into professional growth. As AI changes entry-level work, employers need to be deliberate about preserving opportunities to learn, exercise judgment, and take on greater responsibility. That is the purpose of YUPRO Placement’s Hire-Grow-Advance™ model: connect access to employment with continued development and advancement.

The Hire-Grow-Advance™ model

From access to advancement

Step 01

Hire

Recognize potential beyond prior job titles. Hire for demonstrated capabilities.

Step 02

Grow

Apprenticeships, coaching, and real business problems turn initial access into professional growth.

Step 03

Advance

Opportunities to exercise judgment and take on greater responsibility, building the talent organizations will depend on.

Employers also need to remain open to what emerging talent can contribute along the way. The answer to a company’s next AI challenge may come from an intern provided that intern has the opportunity to understand the problem and the support to pursue an idea. Investing in that pathway helps young people build careers while helping organizations develop the talent they will depend on.

“The answer to a company’s next AI challenge may come from an intern.”