I was on a call with a group of career professionals recently when a conversation about higher education gradually turned into a conversation about AI.
We talked about college degrees, apprenticeships, certifications, transferable skills, career changes, and how quickly the skills required in many professions are changing.
At one point, I shared something I’ve been thinking about with my own clients: before deciding you need another degree or certification, start with where you want to go.
What does that work actually require? Which capabilities do you already have? What are you missing? And what is the best way to develop what you need?
That conversation felt like a natural continuation of the first two articles in this series.
In Part 1, I wrote about earning three degrees and eventually discovering that education alone wasn’t enough to build the career I wanted.
In Part 2, I looked at the other side of that problem: how much capability can be hidden behind a job title when we focus on someone’s previous position rather than what they’ve actually learned to do.
But there is another issue we need to consider.
What happens when AI begins changing the work through which people traditionally developed those capabilities in the first place?
Entry-Level Work Was Also a Learning Environment
Think about some of the work people have traditionally been given early in their careers.
Research the issue. Pull the data. Prepare the first draft. Review the documents. Build the presentation. Summarize the meeting. Create the report.
Some of that work wasn’t particularly exciting.
But it served a purpose beyond getting the assignment finished.
It helped people learn how the organization worked. They saw how decisions were made. They learned what information mattered and what didn’t. They watched experienced colleagues handle difficult situations. They made manageable mistakes, received feedback, and gradually earned responsibility for more complicated work.
Now AI can perform or accelerate many of those tasks.
That’s not necessarily a bad thing.
I use AI extensively in my own business, and I’ve seen firsthand how much time it can save and how much more I can accomplish when the technology is used well.
But efficiency creates another question that I don’t think organizations can afford to ignore:
If AI takes over some of the work people used to learn from, what will replace the learning?
The World Economic Forum and PwC examined this issue in their 2026 report on AI and entry-level work. Their analysis found that 37% of young workers globally are in occupations with medium-to-high exposure to AI-driven task change. The report doesn’t simply ask which jobs will disappear. It looks at how organizations can redesign early-career work so people continue developing skills and gaining access to opportunity as tasks change.
That distinction matters.
The goal shouldn’t be to preserve repetitive work simply because previous generations had to do it.
The goal should be to preserve the development that happened while doing it.
Professional Development Needs to Start With the Work
The same issue applies well beyond entry-level employees.
When someone tells me they’re considering another degree or certification because they want to make a career move, I don’t think the first question should be, “Which program should you choose?”
I would start with the work.
Where do you want to go? What does that work require? Which capabilities have you already demonstrated, and what do you genuinely need to develop?
During our recent Business Insights discussion, I described it in similar terms: identify where you want to go, determine the skills required, and then figure out how to acquire the skills you’re missing. PARWCC Business Insights 2026-10-01 09.
Sometimes another degree will be the right answer. Certain professions require specific education, licenses, or credentials.
But sometimes the answer is a certification, stretch assignment, apprenticeship, mentor, volunteer role, cross-functional project, or targeted training.
And sometimes the capability is already there.
The person simply hasn’t recognized it because they’ve been looking at their career as a series of job titles rather than a collection of capabilities.
Look Beneath the Task
I’ve been spending quite a bit of time lately thinking about how professionals can evaluate their experience differently as work changes.
One distinction keeps becoming more important to me:
A task is not the same thing as a capability.
Suppose AI can now produce a report that once took someone several hours to create.
It’s tempting to conclude that report writing has become less valuable.
Maybe it has.
But what was the person actually contributing?
Were they gathering information? Interpreting conflicting data? Identifying risk? Understanding what mattered to the customer? Recognizing patterns? Making a recommendation? Persuading senior leaders to act?
Those are different capabilities.
Some parts of the work may become increasingly automatable. Some may become much faster because AI assists with them. Others still depend heavily on context, judgment, trust, relationships, influence, or accountability.
That’s why I think professionals need to get better at asking:
What can I make happen because of what I know how to do?
I’ve been working with this concept as I develop a new future-focused career strategy methodology for my clients. One of the ideas at the center of that work is separating the task someone performs from the capability underneath it, the problem it solves, and the value it creates.
That last part matters because an automatable task does not automatically mean an obsolete career.
It may mean the source of someone’s value is shifting.
Learning AI Isn’t Enough
There’s an obvious conclusion someone could draw from all of this: everyone needs to learn AI.
I think that’s incomplete.
I’ve been deliberately learning more about AI myself, but I’m interested in much more than prompting. I want to understand what these systems can actually do, how they can work together, where they save time, and where human judgment still needs to enter the process.
I recently worked with someone who walked me through several systems I hadn’t used before. Having someone explain how the pieces connected made a huge difference. Once I understood the foundation, I could experiment on my own and begin figuring out where the technology made sense in my business. That’s the kind of applied learning I think we’ll need more of. Business Insights 2026-10-01 09…
There is also an interesting complication when we talk about younger workers and AI.
Gallup surveyed more than 1,500 Gen Z Americans ages 14 to 29 in early 2026 and found that 51% were using generative AI at least weekly. At the same time, enthusiasm about the technology had declined. 80% believed using AI was at least somewhat likely to make learning more difficult in the future.
Among employed Gen Z respondents, 48% said they believed the risks of workplace AI outweighed the benefits.
I don’t think the answer is to dismiss that skepticism.
Part of what they’re concerned about is exactly what employers should be considering.
If AI performs the work through which people used to learn how to research, analyze, write, question, and solve problems, how do we make sure increased efficiency doesn’t come at the expense of development?
Learning to work with AI should include knowing how to question it, evaluate what it produces, recognize where it’s wrong, and decide when it shouldn’t be used.
That’s very different from knowing how to write a prompt.
Human Skills Aren’t Becoming Less Important
One of the ideas that came up repeatedly during our Business Insights conversation was the importance of what Angie Callen called human skills rather than soft skills.
I prefer that description.
The Oregon Employability Skills framework identifies ten areas employers and educators can develop: adaptability, analysis and solution mindset, collaboration, communication, digital literacy, empathy, entrepreneurial mindset, resilience, self-awareness, and social diversity and awareness.
What’s interesting is how closely those capabilities fit the AI conversation.
AI can give us information quickly.
That doesn’t mean it can decide what matters in a particular organizational context.
It can generate alternatives.
Someone still needs to evaluate them.
It can draft the communication.
Someone still needs to understand the people receiving it, anticipate how they’ll respond, and take responsibility for the decision behind it.
During our discussion, someone made a point I thought was particularly useful: working with AI isn’t entirely different from learning to work with another person. You learn what it’s good at, where its weaknesses are, and how to communicate with it effectively.
That led to another observation: if you have difficulty explaining to another person what you need, you’ll probably have difficulty directing AI effectively too. Business Insights 2026-10-01 09…
Technology proficiency and human capability aren’t competing skill sets.
Increasingly, they work together.
Employers Need to Replace the Learning, Not the Task
This is where I think the conversation becomes especially important for leaders.
If AI can complete a junior-level task in 15 minutes that previously required four hours, using AI probably makes sense.
But what did the employee learn during those four hours?
That’s the part I would want to understand before eliminating the work completely.
Maybe the employee no longer needs to spend hours assembling an analysis.
Could they spend some of that recovered time reviewing the AI-generated analysis with a more experienced colleague?
Could they identify where it’s incomplete?
Could they present the findings and defend their recommendation?
Could they participate in the meeting where the information is actually used?
Could they work on a cross-functional project and see how another part of the organization approaches the problem?
Those experiences may ultimately provide better development than the repetitive work AI replaced.
But they have to be created deliberately.
Organizations can’t automate the bottom of the career ladder and simply assume future managers and executives will somehow appear at the top.
Career Exploration Is Part of Professional Development
Another theme from our conversation was something much simpler: curiosity.
One participant suggested encouraging people to set aside time regularly just to explore industries, careers, and skills that interest them.
I liked that because professional development doesn’t always need to begin with a major commitment.
Sometimes it should begin with research.
The free O*NET Interest Profiler at My Next Move can help people identify types of work that align with their interests. CareerOneStop provides another way to investigate occupations, including the work people perform, typical education and training, skills, wages, and career outlook.
But I wouldn’t stop with online research.
Talk to people.
I mentioned during our conversation that people sometimes decide they want to change careers without ever speaking with someone who actually does the job.
They may know the title. They may know the salary. They may have read the job description.
But they don’t know what that person does all day.
They may discover that the work they thought sounded fascinating would actually bore them. Or they may discover an adjacent role they didn’t know existed. Business Insights 2026-10-01 09…
Research helps narrow the possibilities.
Conversations and experience help test them.
Professional Development Doesn’t Have to Mean Another Degree
Years ago, I was waiting to have my tires worked on and started talking with another customer about education and careers.
He was a nurse who had recently completed extensive specialized training to move into surgical nursing. He had invested the time and effort to become qualified for the work and was ready to make the transition.
But he couldn’t get hired.
The positions he was pursuing wanted candidates who already had experience doing the job.
I remember thinking, How are you supposed to get the experience if no one will hire you until you already have it?
I don’t know what ultimately happened with his career, but I’ve never forgotten that conversation because it illustrates a problem we still haven’t solved very well.
Education can teach someone the knowledge and technical skills required for a profession. That doesn’t necessarily give them the experience employers want when it’s time to get hired.
If a college, certification program, or specialized training provider is preparing people for a particular occupation, I think part of that preparation should include helping them cross that gap. That could mean clinical experience, internships, apprenticeships, employer partnerships, supervised practice, or connections to organizations willing to hire newly trained professionals.
Otherwise, someone can complete exactly the education they’ve been told they need and still encounter the same frustrating requirement when they reach the job market:
Experience required.
That problem becomes even more important as AI changes entry-level work.
If employers automate some of the assignments people once used to gain experience, and educational programs don’t provide enough opportunities to acquire it either, where exactly is someone supposed to get it?
That’s why I don’t think professional development can simply mean accumulating more credentials.
I value my own education. My degrees helped me become a stronger researcher, writer, communicator, and thinker. Graduate school introduced me to ideas and experiences that continue to influence my work.
But three degrees didn’t give me a roadmap for my career.
A lot of the development that mattered most happened later through experience.
I volunteered for opportunities. I learned coaching. I changed fields. I worked with people going through career transitions. I built a business. More recently, I’ve been learning how to use AI and automation in that business.
The work changed, so I had to keep changing too.
That’s why I would start with a different question:
What capability do I need to develop next, and what experience will allow me to demonstrate it?
The answer could be formal education.
It could also be an apprenticeship, certification, stretch assignment, mentor, professional association, volunteer opportunity, side project, new technology, or conversation with someone doing work you’re considering.
And if you’re choosing an educational or training program specifically because you expect it to lead to a particular career, I would ask another question before enrolling:
How will this program help me get from learning the work to actually being hired to do it?
That means looking beyond the curriculum. What practical experience will you gain? What employer relationships does the program have? Are there internships, clinical placements, apprenticeships, or other opportunities to demonstrate what you’ve learned? What support exists for making the transition into the actual job?
The education matters.
But so does the bridge between education and employment.
The Career Ladder Isn’t Disappearing. Some of the Rungs Are Changing.
Part 1 of this series started with education.
Part 2 moved into transferable skills and the capabilities that can be hidden behind a job title.
Part 3 brings those ideas together at a time when AI is changing some of the work through which people traditionally built those capabilities.
For professionals, that means looking beyond the task you’re performing today. What capability sits underneath it? What problem can you solve? What value do you create? Which parts of that value could become less differentiating, and which could become more important?
For leaders, the questions are different.
What are people learning while they work for you? Which developmental experiences are disappearing as technology changes the job? What will replace them? And are you developing people for the work your organization will need next, rather than simply making them better at the work it needs today?
Education still matters. Experience still matters. Technology certainly matters.
But people still need opportunities to apply what they know, work alongside people who know more than they do, make manageable mistakes, receive feedback, exercise judgment, and gradually take responsibility for harder problems.
AI may change how that happens.
It shouldn’t eliminate the need for it.
If the first rung of the career ladder changes, what are we building in its place?
Call to Action
If AI is changing parts of your work, the first question may not be whether you need a new career. It may be whether you understand which parts of your experience will continue to matter, which capabilities are becoming more valuable, and where those capabilities could take you next.
That’s increasingly part of the work I’m doing with executives who are considering their next move. We look beyond the job title to identify the business problems they know how to solve, the value they’ve already demonstrated, and how that experience can be positioned for where the market is going.
If you’re trying to figure out what your experience is worth in a changing market, let’s talk.
Schedule a Free Discovery Call
About Clair Levy
Clair Levy, CPRW, CARW, CPC, is the founder of Precision Resume Solutions and a certified resume writer and career coach with 15+ years of experience helping professionals manage career transitions. She works primarily with Director, VP, and C-suite executives to clarify their value, strengthen their positioning, and translate complex careers into compelling resumes, LinkedIn profiles, and career narratives.
Before founding Precision Resume Solutions, Clair spent 14 years helping professionals through job loss and career change. Her work today combines executive career strategy, personal branding, and an increasing focus on how AI and changes in the workplace are affecting the way experienced professionals position themselves for what comes next.
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