The article Work: Which skills we really need in the age of AI appeared first in the online magazine BASIC thinking. With our newsletter UPDATE you can start the day well informed every morning.
Artificial intelligence has become part of our everyday lives within the last three years. But what skills does the change generated by AI require? A current McKinsey study also deals with this. I looked at the results.
Interestingly, the study does not add to the debate about job losses. Rather, it looks at the foundation of modern work, namely skills, competencies and human abilities.
Central thesis of the McKinsey study is that artificial intelligence will not replace humans, but rather shift their role. According to the study, work will be reorganized as collaboration between humans, AI agents and robots.
What sounds technical at first glance has far-reaching social consequences. Because when the meaning of skills changes, what we see as valuable, relevant and future-proof also changes.
Work 2026: From the job question to the skill question
The starting point of the study is that with today’s existing AI technologies, around 57 percent of working hours in the USA could theoretically be automated.
However, this number is not a “roadmap” for mass unemployment, but rather describes the technical potential. Adoption would not lead to major job losses in the coming years because it requires time, money, acceptance and regulation.
Historically, such upheavals such as those highlighted by AI often last decades. During these periods, adjustments to people’s abilities gradually occur.
For the study, millions of job advertisements were analyzed with the remarkable result that around 72 percent of the skills in demand today appear in both automatable and non-automatable activities.
The conclusion: Skills do not simply disappear, but rather migrate within professions and professional groups, change their meaning and are embedded in new contexts. Activities are therefore defined less by the “what” and more by the “how”.
How AI is changing the role of humans
A classic example is writing. While research and text production used to be largely human core tasks, today AI systems take over drafts, summaries and structural suggestions.
However, this does not make human performance obsolete, but rather shifts towards classification, tonality, contextualization and responsibility.
Writing becomes more editorial, more scrutinizing, more evaluative. Human performance in the area of writing does not fundamentally lose importance, but rather becomes more routine.
Silent appreciation of core human competencies
A change in abilities in the area of soft skills is particularly clear. The study shows that social, emotional and relational skills are the least threatened by automation.
Leadership, coaching, negotiation, empathy, conflict resolution and responsibility remain in human hands because they require situational action, trust and emotional intelligence. These capabilities cannot be reliably formalized using AI, let alone automated.
I experienced this myself this week when I was interviewed by Handelsblatt through an AI interview bot on the subject of AI agents. The conversation was at a high technical level, but there wasn’t much evidence of empathy or communication skills in the bot.
Future of work: Focus on human strengths
What I also found interesting in the study was that these human soft skills are not only relevant in nursing, education or social work, but increasingly also in knowledge-intensive professions.
As AI prepares decisions, provides analysis and simulates options, human judgment becomes even more important. The ability to critically question results, recognize ethical implications and take responsibility gains in importance as a result.
McKinsey speaks of a “skills partnership” in which machines provide routine and scale, while people provide meaning, direction and control.
Eight skills as the new operating system of work in 2026
From the analysis of job postings, McKinsey derives a core of eight skills that are and will remain relevant across industries and income brackets.
These include communication, problem solving, management, operations, leadership, detail orientation, customer relations and writing. These capabilities act as a kind of “operating system” for modern activities that AI will not replace but accelerate.
What is crucial, however, is adapting these capabilities to the conditions changed by AI. In the future, communication will not only mean conveying content, but also explaining and classifying AI results in an understandable way.
Problem solving is shifting from pure execution to precise problem definition, and management is evolving from task distribution to orchestrating hybrid teams of humans and machines. Those who master these skills and the necessary adaptations will benefit from AI.
Work 2026: New tasks for people
This creates new tasks for people. In customer service, for example, AI agents are increasingly taking on standard inquiries, while humans are taking on complex, emotional or escalated cases.
The crucial skill is no longer finding an answer quickly, but rather building trust and resolving extraordinary situations.
As part of leadership, systems take over planning, reporting and analysis. Managers thereby become designers of framework conditions, coaches for people and guardians of the AI systems used.
Creativity is becoming less a question of producing than of selecting, linking and evaluating, because texts, images and concepts are created more quickly with the help of AI, but their quality is increasingly dependent on human curation.
AI Fluency: The new general education
Particularly noteworthy are the statements in the study on the so-called “AI Fluency”. This does not mean the ability to program AI models, but rather to use them sensibly, control them and critically evaluate them.
AI fluency includes in particular the understanding of strengths and weaknesses of AI systems, the conscious handling of uncertainties and the ability to embed results into processes.
McKinsey’s study found that demand for this skill in US job advertisements has increased by a factor of nearly seven in two years.
When skill partnership becomes a dependency
What follows from this result of the “skill partnership”, i.e. the collaboration between people, AI and robots? Does everything automatically end well? Not necessarily. Because collaboration also has dark sides that we have to be prepared for.
On the one hand, we should not overlook the fact that AI is generally good at providing plausible answers – but not necessarily correct ones. Because AI answers always “sound good,” it becomes increasingly difficult to tell when an answer just sounds good and when it is really good. Judgment is becoming increasingly important, which I have already written about.
Complementarity between humans and AI is not a sure-fire success; it requires conscious design, clear responsibilities and a culture of doubt. Otherwise, dependency quickly develops.
On the other hand, the conscious and effective use of people is becoming increasingly important. Human supervision and final decision-making must not degenerate into a symbolic act, but must be practically effective, with clear options for intervention, transparency and accountability. Otherwise, there is a risk that incorrect decisions will be automated, which will ultimately be difficult to correct.
Work of the future: The quality of collaboration will be decided in 2026
Essentially, the result of the McKinsey study is an invitation to take personal responsibility. Human skills do not become useless or superfluous, but rather change their role. As AI becomes commonplace, it will be crucial how confidently people handle it.
So where should we place people when it comes to important skills? Especially when it comes to the skills that define people. AI Fluency will then develop into a new form of general education. And finally, critical judgment becomes a key competency in a digital society.
The future of our use of AI is not a question of technology alone. Rather, it is a question of attitude, education and the willingness not to delegate responsibility to systems, but rather to consciously accept and perceive it.
Also interesting:
- One-size-fits-all: ChatGPT makes social media posts all sound the same
- AI dialogues: Why artificial intelligence seems smarter than it is
- AI agents will change companies – but differently than expected
- Should we treat AI as a legal entity?
The article Work: Which skills we really need in the AI age appeared first on BASIC thinking. Follow us too Google News and Flipboard or subscribe to our newsletter UPDATE.
As a Tech Industry expert, I believe that in the AI age, there are several key skills that are crucial for success in the workforce. These skills include:
1. Data literacy: With the increasing importance of data in decision-making and AI algorithms, individuals need to be able to understand and interpret data effectively.
2. Critical thinking: As AI becomes more prevalent in the workplace, individuals need to be able to think critically about the implications and limitations of AI technologies.
3. Adaptability: The pace of technological change is rapid, and individuals need to be able to adapt quickly to new technologies and ways of working.
4. Collaboration: AI is often most effective when it is used in conjunction with human intelligence. Therefore, individuals need to be able to collaborate effectively with both machines and other humans.
5. Creativity: While AI can automate many routine tasks, it is still limited in its ability to think creatively. Individuals who can think outside the box and come up with innovative solutions will be highly valuable in the AI age.
Overall, the key skills that we really need in the AI age are those that complement and enhance the capabilities of AI, rather than compete with them. By developing these skills, individuals will be well-positioned to succeed in the increasingly automated and data-driven workplaces of the future.
Credits