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March 12, 2026
The use of AI is becoming a key skill in the labor market. How does this affect women’s employment?
According to the World Economic Forum’s 2025 report, global companies consider artificial intelligence (AI), data work (Big Data), cybersecurity, and technological literacy — the ability to work with digital tools and systems — to be the most important technical skills for the next five years. Combined with analytical thinking, creativity, and agility, these competencies will be crucial for competitiveness in the labor market, according to leading global companies.
When it comes to technical skills, survey results show that companies identify artificial intelligence and machine learning (90.9%), data work and analytics (66.7%), cybersecurity (48.5%), and technological literacy and the use of digital tools (45.5%) as key competencies for the coming years. In addition, companies emphasize the importance of continuous learning and the ability to adapt to rapid technological change.
The Digital Serbia Initiative, in cooperation with the United Nations Development Programme (UNDP) in Serbia, published the report remAIn relevant: Skills for Jobs of the Future, which maps the key competencies expected to shape the labor market in the years ahead. From employers’ perspective, AI has already become a basic competency. In the survey, as many as 90% of companies identified AI use as a key technical skill expected within the next five years.
The research included representatives of companies operating both domestically and internationally. As many as 94% of companies in the sample have more than 100 employees, while 72.7% are in foreign or mixed ownership. This structure increases the relevance of the findings in the context of global expectations regarding future skills.
Key findings show that:
90.9% of companies believe AI use will be a key technical skill in the next five years;
81.8% highlight flexibility, adaptability, and continuous learning as the most important non-technical skills;
54.5% cite a lack of experience in specific technologies as the biggest hiring challenge;
87.9% expect increased demand for AI and machine-learning specialists, while 72.7% emphasize the need for data and analytics experts;
57.6% assess candidates’ analytical and creative thinking as being at an average level.
Unfortunately, according to multiple reports — particularly those by the World Economic Forum and Stanford University — the development of AI technologies may deepen existing gender inequalities. Globally, women make up only about 22–30% of the AI workforce, and even less in leadership positions (around 14–15%). Looking beyond the AI industry itself, only about 29% of workers trained to use AI tools are women. The average gap in AI usage stands at around 25% — roughly three men for every woman.
Research suggests that women tend to adopt a more critical stance toward AI and are more likely to raise questions about its broader societal impact. In other words, women are often concerned not only with the economic benefits of AI but also with its ethical implications.
There is another challenge: women’s jobs are more exposed to automation (27.6% of female-dominated roles compared to 21.1% of male-dominated ones). Administrative and clerical positions — where women are overrepresented — are among the most vulnerable to AI-driven automation. United Nations estimates suggest that around 65 million women’s jobs globally face a high risk of AI transformation.
Moreover, the introduction of AI systems in recruitment processes may also disadvantage women. Researchers at Stanford have found that automated hiring systems can portray women as younger and less experienced and may filter out candidates with career breaks, such as maternity leave.
Artificial intelligence can deepen the gender gap in the labor market, but with timely action it can also become a tool for reducing it. A key solution lies in earlier and broader inclusion of girls and women in education related to digital and AI skills. This includes curriculum reforms, accessible training programs, STEM scholarships, and the promotion of female role models in technology.
At the same time, companies play a crucial role. Investing in reskilling and upskilling women can help prevent their displacement from professions most affected by automation. Flexible working conditions, transparent promotion criteria, and inclusive hiring policies can also contribute to more equitable access to AI-augmented jobs.
It is equally important to design AI systems that are inclusive by default. This means building diverse development teams and conducting regular algorithm audits to reduce gender bias in hiring and performance evaluation. Finally, public policies should encourage stronger cooperation between education systems, businesses, and governments to ensure equal access to future skills. If AI is viewed as a shared opportunity rather than solely a technological threat, it can help create a fairer labor market instead of widening existing inequalities.
