2026: Jobs Without Workers, Workers Without Jobs

During crises, hiring goes through phases: At first, a freeze, then a tentative reactivation, but full recovery? A rarity. The job market simply reinvents itself, offering insights into how many structures and processes will change in the future. Companies often claim they suffer from personnel shortages, yet millions of people struggle to find employment, regardless of their education. The coming year and the decade following will be defined by solving mismatches between jobs and workers, and might force a whole new approach to surviving and thriving in the job market.

A skills gap, not a worker gap

The hiring process is potentially the most competitive it has ever been, with an average hiring rate of just 0.5%. However, when offers are made, they are accepted in almost 82% of cases. That is one of the highest acceptance rates since 2021, but why do so many applicants get rejected?

Increasingly, the problem is not about companies simply looking for workers, but that the workers who apply do not meet the demands companies have. Only 55.6% of EU adults had at least basic digital skills in 2023. That means roughly 44% still lack the basic digital literacy employers increasingly expect. According to TyN magazine, rapidly-expanding sectors that will be hiring the most are green industries, digital infrastructure, health tech, and advanced manufacturing. These sectors require deep expertise and thus rely on highly specialised and capable employees, rather than those with a more general skill set. 

This is a relatively new development, as most companies were previously seeking “all-rounders.” Yet the landscape is ever changing. Beyond routine tasks that can increasingly be handled by artificial intelligence, employees are now expected to bring a combination of human skills that machines cannot replicate. Fields such as digital infrastructure, cybersecurity, and data analytics offer good insight into this gap: graduates often possess theoretical knowledge but lack practical experience with the latest systems, programming languages, or data-handling protocols. Similarly, in green energy and advanced manufacturing, swiftly evolving technologies and industry-specific processes leave students underprepared for specialised roles. Even in health technology and biotechnology, curricula struggle to keep pace with innovations, leaving graduates without the applied skills required to thrive in complex, interdisciplinary environments. As a result, 2026 is predicted to be one of the most challenging years for new entrants to the labour market. High GPAs alone will no longer secure employment; instead, success will depend on the unique combination of technical expertise and distinctly human capabilities that complement AI automation, such as critical thinking, adaptability, and collaborative problem-solving.

What are the skills that determine success?

Very generally, the set of assets to have revolves around adaptability and continuous learning. Industries change quickly, requiring instant responses to industry needs, resilience across diverse environments, and effective workload management in unstable times. Technical skills that enable learning new systems, along with the ability to think critically and spot errors and biases in all kinds of automated processes, are at the foundation of this. The implementation of autonomous AI agents in teams by 2026 is estimated to be around 56%. It is not simply about being literate in interpreting data, but also about understanding the ethics of handling data. Oftentimes not taught enough, a basic understanding in the department is tremendously valuable. 

Strong collaboration skills and the ability to self-manage aren’t new qualities, but they’re becoming even more essential as the tasks AI can’t handle grow increasingly complex. Those require optimal team coordination and communication. Persuasion and clear expression are more important than ever.  Everyone knows that imprecise commands cause AI to produce something far removed from what you wanted, which is similar to what happens with people sometimes, to be fair. 

Most critically, in sectors such as healthcare and medicine, empathy alongside technical skills makes all the difference. In any sector, human care and truly human thinking will determine success. To everyone's surprise, instead of taking everything over, automation is highly dependent on the skills that it cannot replicate and is thus not becoming less human but more human. Software engineers who designed AI might be replaced by it, but people working in care will not. While technical sectors will continue to grow, it will also be about servicing gaps and tasks AI is not competent in.

The social cost of a mismatch

Hiring people for reasons other than their skills risks long-term issues. The European Union recently passed the Pay Transparency Directive, making it illegal to post new jobs without providing a salary range or to ask for an applicant’s previous pay.  The applicant also has the right to inquire as to how the new salary was calculated. The main goal of this directive is to decrease discretionary pay discrepancies and reduce the gender pay gap, given that women are currently paid 12% less per hour than men. It will also be of interest to see how popular job offerings might start receiving fewer applications when the salary is not hidden until the very last moment. Jobs that receive fewer applicants but do now show a proportionally large salary might attract those. This pre-fixed number is intended to make it impossible for companies to pay women less than men for the same job, regardless of the job’s complexity. However, more men than women might still be hired for those positions in the end. Ultimately, how the Directive shapes a labour market dominated by demand for highly specialised talent remains to be seen. The reform may correct certain inequities and redirect applicants toward areas of genuine need, but it will also reveal the extent to which the current workforce and, particularly, new graduates lag behind emerging skill requirements.

Looking ahead, the changing labour market underscores the importance of continuous skill development at both individual and institutional levels. Workers will need to engage in lifelong learning, acquiring advanced technical knowledge in coding, data literacy, or understanding AI-driven processes. Next to that, human capabilities remain irreplaceable, including critical thinking, creativity, and adaptability. Universities and training institutions have a parallel responsibility: curricula must be updated to reflect the demands of the modern workforce, incorporating practical, interdisciplinary experiences, exposure to emerging technologies, and opportunities to develop collaboration and skills useful in real-life work scenarios. In this way, education and professional development can align more closely with industry needs, equipping graduates to navigate a landscape where technical expertise and human judgment are equally indispensable.