I have spent a significant part of my career working with talent. I built a 300-person technology talent pool in the Caribbean, helped create a pipeline that reached thousands of university students across the region for opportunities at Microsoft, and have personally hired about 160 people. Based on public reviews, I have a 4.8 out of 5-star rating as an employer.
So when I say I believe we have a big talent problem, I am not saying it because of one difficult hire or one frustrating week. I am saying it because I have spent years hiring, developing, managing and learning from people, and something feels different.
Artificial intelligence is part of that change.
AI has made people extraordinarily capable. Someone can now write, research, design, code, analyze, create a presentation or start building a company with tools that were unimaginable a few years ago. I use AI heavily myself, and I believe it will make many of us dramatically more productive.
But there is a downside we are not discussing enough. AI can make someone appear capable before they have developed the judgment, discipline and experience that traditionally came with becoming capable.
We are increasingly able to produce the output without necessarily developing the person behind the output.
That matters because businesses do not simply need output. They need people who can own work.
Ownership does not mean everybody should be the CEO. It does not mean everybody should make every decision. It means that when you are responsible for an outcome, you stay with it. You communicate. You investigate problems. You follow up. You ask for help when necessary. You warn people when timelines change. You do not simply return the problem to someone else every time reality becomes inconvenient.
Those qualities sound basic because they are basic. That is part of the problem.
We are becoming more sophisticated while forgetting fundamentals.
People can produce beautiful documents and still fail to tell a client when the document will arrive. A professional can possess highly specialized knowledge and still fail to communicate availability, deadlines or project status. Someone can have impressive credentials while being extraordinarily difficult to depend on.
Technology has improved the document, but it has not eliminated the relationship.
Good old-fashioned communication still matters. Tell people when you are available. Tell them when you are not. Give a realistic timeline. If the timeline changes, communicate early. Keep your word. If you cannot keep it, say so.
No artificial intelligence tool makes those responsibilities obsolete.
I recently interviewed an educator who is seeing a related issue with students. Students can now use AI to create work that appears far more sophisticated than their actual understanding. One response is to rely more heavily on presentations and questioning. Can the student explain the work? Can they defend it? Can they answer questions that move beyond the generated response?
That same challenge is arriving in the workplace.
A résumé can be improved by AI. A portfolio can be improved by AI. A writing sample, coding exercise or business plan can be improved by AI. Employers increasingly need to ask a different question: how much does this artifact actually tell me about the human being behind it?
That has changed the way I hire.
I rely more heavily on behavioral interviewing and methods such as STAR, which focuses on the situation, task, action and result. I want to understand what the person actually did. What problem were you responsible for? What decisions did you make? What went wrong? What did you do when the first approach failed? What did you learn?
I also increasingly use short contract periods before making a deeper commitment. Probation is not a new concept, but I believe practical verification becomes more important when so much professional output can now be assisted by AI.
This is especially true when most of someone’s track record was created during the generative AI era. That is not a criticism of younger workers. I am in my twenties. I am Gen Z myself. It simply means the signals are changing, so employers need better ways to understand what someone can actually do.
Give someone a real problem and watch how they operate. Do they ask thoughtful questions? Do they communicate when they get stuck? Do they improve after feedback? Do they bring back solutions or simply bring back problems? Can they finish?
The future of hiring may involve fewer declarations of competence and more demonstrations of competence.
There is also a larger cultural problem. We have spent years telling people to seek leverage. Automate. Delegate. Start a company. Become an entrepreneur. Build passive income. Stop trading time for money.
Much of that advice is useful. I believe in leverage myself.
But I think we sometimes forgot to explain the order.
The lesson should not be to avoid work. The lesson should be to understand work deeply enough to know what should be automated, delegated or leveraged.
Everybody wants to own something. Fewer people seem excited about apprenticeship.
Yet apprenticeship is where many people historically learned judgment. You started with smaller responsibilities. You made mistakes. You were corrected. Eventually you needed fewer instructions. Then someone trusted you with a problem instead of a task.
We should absolutely eliminate pointless work. We should not preserve suffering simply because older generations experienced it. But we should be careful not to eliminate every form of productive struggle.
Some difficult work teaches patience. Some repetitive work teaches patterns. Some junior work teaches how customers behave, how businesses make money and how systems fail. If AI removes those experiences, we need to intentionally replace the learning that used to happen inside them.
When I find someone who does demonstrate judgment, reliability and ownership, I also believe employers should give that person a reason to stay.
That may mean higher compensation, commission, profit sharing, bonuses, equity or greater autonomy depending on the role. There is enormous value in people who understand the fundamentals and can also use today’s technology.
But economic ownership, ownership of results and decision-making authority should not be confused.
Someone can deserve a meaningful share of the value they create without running the entire company. A salesperson can earn substantial commission without controlling product development. An engineer can have equity without making every business decision. A person can own an outcome without being the CEO.
Contribution should create opportunities for greater responsibility and greater participation in the upside, but those things should grow alongside demonstrated capability.
Some people will probably read this and think I sound like an older generation complaining about young people.
The funny thing is that I am one of the young people.
I am part of the generation that was supposed to disrupt everything, embrace technology and create the future. I still believe we will.
But if one of the people standing inside that future is saying there is smoke, perhaps we should at least check the room.
I am fortunate to work with people who still demonstrate excellent communication, humility, reliability and ownership. They exist, and I value them deeply. But in my experience, those qualities increasingly feel more scarce than they should.
That is why I think the opportunity is not to reject AI or return to an older model of work. It is to combine the best of both worlds.
Use AI. Automate aggressively where it makes sense. Remove useless work. Give people access to better tools. Let talented people accomplish more with smaller teams.
But bring the basics with us.
Teach people how to communicate. Teach them how to manage commitments. Create apprenticeships with shorter learning cycles and real responsibility. Hire through demonstrated work, not polished artifacts alone. Reward people when they prove they can own outcomes. Give strong contributors a path to participate in the value they create.
We do not need to choose between innovation and professionalism.
We need people who can use the newest tools while practicing some very old principles: learn your craft, keep your word, communicate clearly, take responsibility, become dependable, and leave things better than you found them.
The future of work will probably look very different.
But someone will still have to do the work that makes the future function.
