Learning What Everyone Else Learns Won't Make You Stand Out
Over the last decade, career advice, especially for university students, has been largely the same: learn to code, learn Python, learn AI. It might have been good advice in the past. But it is no longer enough.
While reading McKinsey's Technology Trends Outlook report published in September 2026, what impressed me most wasn't the investment figures or the new technologies. It was a small detail at the end of the section: how much demand there is for which skills, and how many people in the market have these skills.
The picture I saw there reminded me once again that this advice needs to be reconsidered.
Abundant skills, scarce skills
The report examines 14 technology trends: from AI agents to cybersecurity, from robotics to energy. There is the same pattern in each of them. The famous skills we have been directed to learn for years are no longer scarce; they are even in oversupply. In Python, machine learning, C++, and general software development skills, the supply meets, and even exceeds, the demand in most areas.
The shortage is somewhere else. It is in the skills of connecting the pieces, bringing the work into real life, and "taking ownership" of the responsibility.
To give a few examples:
The number of people who know machine learning is more than 4 times the demand. However, in the orchestration skill that connects agents, tools, and workflows, there is only one person for every five open positions.
Software now scans CVs in recruitment; it is not hard to find an expert who can use the system. The hard part is to be the person who translates a manager's abstract expectation of "I want someone good" into a clear profile and draws a realistic picture for the candidate. In other words, being able to do that "translation" between the manager and the candidate.
Imagine a moment of disruption: a delayed flight, a late aircraft delivery, or an overbooking issue. There are plenty of people who know exactly what to do according to the procedure. However, what is missing is the person who can mobilize different teams simultaneously during a crisis, provide accurate information to the passenger without any miscommunication, and follow through until the problem is fully resolved. In other words, that muscle of coordination and ownership.
In short, the job market now finds people who can use the tools. The person it is looking for but has a hard time finding is the talent who can combine tools, processes, and people to deliver a concrete result.
Looking from the recruitment desk
This picture perfectly matches my observations as someone who has been recruiting for years. Candidates' CVs are looking more and more alike: the same online certificates, the same conferences, the same training projects.
The most common missing thing we see in recent interviews is this: there are many candidates who say they use a tool, but very few can explain how they applied it to a real business problem and got a result. We have an incredibly hard time getting specific examples.
The question that makes a difference in an interview is no longer "Which tools do you know?". It is the question "What did you finish by putting together what you know?". A candidate who can answer this question with a concrete story gets ahead of a candidate with a longer resume.
The report shows one more thing: in maturing technology fields like communication infrastructure, cybersecurity, energy, and mobility, more than half of the job postings are now in non-R&D roles. That means in operations, sales, compliance, and support functions. Technology is ceasing to be a profession on its own and is penetrating the DNA of every profession. This is great news for all talents without an engineering background.
The uncomfortable part we need to talk about
There is another finding in the report that is not very easy to face, and I don't want to skip it.
Companies that use AI agents at the most advanced level are gradually moving to smaller teams. In these teams, a small number of experienced people manage a large number of AI agents doing routine tasks. Those routine tasks and observations that used to help us learn the job in the first steps of our career—which were actually our entry gate into the sector—are increasingly being handed over to AI.
This means the entry-level gate will become narrower compared to the past. The report still sees the long-term impact of this on organizational structures and labor demand as an "open question". To be honest, I don't have a clear answer to this question either.
But one result is very clear: If the gate is narrowing, you need to prove yourself before entering. The skills of "taking ownership", "coordination", and "delivering results" that used to be learned over time in the kitchen of the job are now expected to be brought to the table before you even step through that door.
So what should be done?
Well, how can a talent with no experience show these skills? We get this question a lot. Here are 3 clear suggestions to make a difference in your field:
Deliver a finished work: Instead of ten unfinished training projects, make a single project that actually works and is used by someone. It could be a registration system for a student club, inventory tracking for a family business, or a website for an association. The important thing is that the result works in real life.
Combine your field with technology: Law, medicine, logistics, tourism (which is also my major)... No matter what you study. One of the clearest messages of the report is that people who know both worlds are scarce. Someone who knows tourism dynamics and can do data analysis on top of it is more valuable than a hundred people who know only one of these two.
Be the "connector" in the team: Take on the role that brings different people, ideas, and processes together in your project assignments, volunteer work, or internship. Rest assured, this will be the strongest story you will tell in an interview.
Don't stop learning Python. But see it as the beginning of the journey, not the end. The technical skills everyone learns will only bring you to the door. What gets you inside is your ability to combine that skill with other things and turn it into a concrete result.
Source: McKinsey & Company, Technology Trends Outlook 2026, September 2026.
