Opinions expressed by Entrepreneur contributors are their own.
Key Takeaways
- Hire for learning velocity, not just past experience. Curiosity and the ability to apply feedback predict performance better than a resume does.
- Separate the capabilities a role needs from credentials that describe past methods. Narrow job definitions shrink the talent pool just as AI changes the work.
Hiring in a service business has a way of challenging what you think you know about talent. Over the years, I’ve seen candidates who looked nearly perfect on paper struggle once the job became unpredictable. I’ve also watched people without the obvious résumé rise quickly because they could learn, communicate and make good decisions when nobody was standing beside them telling them what to do.
Those experiences have changed the way I think about qualifications.
Experience matters, particularly in positions that require specialized knowledge. The mistake is assuming experience automatically predicts future performance, especially as technology changes what many jobs require. It can show that someone understands the fundamentals, but it cannot reveal how that person will respond when familiar tools, expectations or customer needs shift.
That makes an old hiring question increasingly less useful: Has this person already done this exact job? A better question may be: Can this person succeed in the job this is becoming?
The labor problem may also be a definition problem
Employers have good reason to be frustrated with the labor market. The National Federation of Independent Business reported in September that 45% of small-business owners trying to hire had few or no qualified applicants. 26% identified labor quality or availability as their single most important business problem, more than twice the historical average.
Many industries clearly face a talent shortage. Some businesses may be worsening the shortage by defining “qualified” too narrowly. A job description built around five years of experience performing a specific set of tasks assumes those tasks will remain relatively unchanged.
AI, automation and other technologies are challenging that assumption. Employers should separate the capabilities a role truly requires from credentials that merely describe how the work was performed in the past. That distinction can open the door to candidates with adjacent skills and greater potential.
The U.S. Chamber of Commerce’s 2026 Empowering Small Business report found that 47% of small businesses using AI say it’s creating jobs, while only 6% say it is reducing them. That suggests the more immediate workforce question for many entrepreneurs is not how many jobs AI will eliminate. It’s how existing jobs will change as people gain access to better tools.
Hire for what is difficult to teach
Commercial cleaning is a great place to learn about talent because the work is both process-driven and highly people-dependent. We can teach procedures. We can establish quality standards, provide extensive onboarding and use technology to improve scheduling, communication and accountability. Those systems matter enormously when distributed teams perform work across different client locations.
A client has an unexpected request. A team member calls out. Something at a facility doesn’t look right. An employee notices a problem that technically belongs to someone else. What happens next tells you a great deal about that person.
Some employees wait for instructions. Strong ones tend to take ownership of the outcome. They know when to act, when to ask for help and when a small issue could become a larger client problem if nobody addresses it. That kind of judgment has become one of the qualities I value most.
Look beyond experience to learning velocity
Leading within a franchise system has reinforced another lesson for me: The ability to learn quickly can be more valuable than arriving with all the answers. Franchise organizations operate across markets, customers and teams that are never completely identical.
The same operating principles may apply broadly, but people constantly encounter circumstances that require them to absorb information and adjust. Technology is accelerating that reality.
An employee may learn one software platform this year and work with an AI-enabled version next year. A manager who built expertise around producing reports may suddenly have technology that can produce those reports in seconds. Their value then shifts to interpreting the information, spotting what matters and deciding what to do next.
That is why I increasingly think about learning velocity when evaluating talent. Does this person get curious when something changes or defensive? Can they take feedback and apply it? Can they transfer something learned in one situation to another?
In interviews, practical scenarios can reveal these qualities more clearly than another résumé screen. Ask candidates to explain how they approached an unfamiliar challenge, what they learned and what they would do differently now. Listen for self-awareness, resourcefulness and a willingness to revise their thinking.
The best hire isn’t the person who already knows every answer. It’s the person ready to find the next one. For business leaders, that means designing interviews and development plans around adaptability, judgment and ownership — not simply checking boxes on a résumé. Experience should inform hiring decisions, but it shouldn’t limit our view of potential.
As AI continues to reshape roles, the companies that build resilient teams will be those willing to recognize talent in new places and give capable people the tools, trust and opportunity to grow with the work.
Key Takeaways
- Hire for learning velocity, not just past experience. Curiosity and the ability to apply feedback predict performance better than a resume does.
- Separate the capabilities a role needs from credentials that describe past methods. Narrow job definitions shrink the talent pool just as AI changes the work.
Hiring in a service business has a way of challenging what you think you know about talent. Over the years, I’ve seen candidates who looked nearly perfect on paper struggle once the job became unpredictable. I’ve also watched people without the obvious résumé rise quickly because they could learn, communicate and make good decisions when nobody was standing beside them telling them what to do.
Those experiences have changed the way I think about qualifications.
Experience matters, particularly in positions that require specialized knowledge. The mistake is assuming experience automatically predicts future performance, especially as technology changes what many jobs require. It can show that someone understands the fundamentals, but it cannot reveal how that person will respond when familiar tools, expectations or customer needs shift.
