AI and Hiring: New Challenges for the Ticino Market
The use of AI in recruitment raises concerns regarding discrimination and bias. An analysis of risks for candidates and companies in Ticino.
Contesto
In brief - AI is being used to optimize staff recruitment in Switzerland. - Cases of incorrect exclusion and unsuitable profiles have been reported. - Algorithms risk penalizing candidates with non-linear career paths. - A collective approach to software regulation is necessary. ## Key facts - What: Use of artificial intelligence in hiring - When: Second quarter of 2026 - Where: Switzerland and Canton Ticino - Who: Employers and human resources managers - Source: Manpower quarterly report Artificial intelligence has entered the Swiss labor market, bringing with it expectations of efficiency and new management complexities. According to the Manpower quarterly report for the second quarter of 2026, employers remain cautious in their hiring forecasts. In an attempt to attract talent and manage internal processes, companies are increasingly turning to AI-based software for candidate screening. This digital transition, however, is not without its critical issues. Human resources managers have begun reporting instances of the erroneous exclusion of potentially valid profiles, while some companies have reported receiving applications that do not align with actual operational needs. The problem often lies in how the systems are trained. Machine learning algorithms rely on vast sets of historical data. If these data reflect pre-existing biases or traditional career patterns, the software will tend to replicate those models, excluding those who do not fit standard criteria. The issue also directly concerns Canton Ticino, where the integration of advanced technologies into selection processes is under observation to ensure transparency and fairness toward every candidate. The challenge for local businesses consists of balancing the automation of recruitment processes with the ne...
Dettagli operativi
The Critical Impact on Female Careers The issue of discriminatory effects linked to AI becomes particularly evident when examining female professional careers. Algorithms, trained on historical data, tend to favor linear and continuous career paths, a characteristic more frequently found in male profiles. Consequently, resumes with interruptions, part-time work periods, or career changes are often penalized by selection software. Bea Knecht, founder of Zattoo, highlighted how systems learn from the past: if the past does not adequately document the female presence, the software risks not recognizing it as existing. For Professor Solange Ghernaouti of the University of Lausanne, the issue is even deeper: algorithms facilitate the automation of discriminations, making them almost indisputable as they are integrated directly into the software. In this way, artificial intelligence acts as an amplifier of inequalities already present in the labor market, rather than correcting them. This dynamic also affects minorities, whose profiles may not align with the dominant models used to train selection systems. Companies operating in Switzerland, including those active in the services and industry sectors in Ticino, must be aware of these limitations. Blindly relying on an algorithmic tool can lead to the loss of valuable talents and the creation of less diverse teams. It is necessary to question the ethics of the software used and the transparency of the selection criteria. According to experts, it is not enough to merely increase female presence in scientific sectors: models capable of proposing pluralistic and alternative visions to the current structure are needed. The concrete risk is that technology, born to improve efficiency, becomes an invisible but insurmountable barrie...
Punti chiave
Towards informed and regulated selection Despite the risks, the perspective on artificial intelligence is not exclusively negative. Bea Knecht suggests that AI can be a truly egalitarian tool, accessible to anyone without requiring long periods of specific technical training. The key lies in understanding how the tool works: women, and more generally all workers, must learn to manage these technologies to improve their professional standing. Political scientist Anna Jobin highlights the urgency of a collective approach to regulation, arguing that decisions regarding AI must go beyond technical expertise. For companies in Ticino, the next step is to implement control systems that work alongside AI, ensuring constant human oversight. Before adopting automated solutions, it is advisable to verify the compliance of selection criteria and the transparency of the data used by the software provider. For candidates, however, it becomes essential to present a resume that, while unique, is readable by screening systems. Optimizing one's professional profile also means understanding how algorithmic filters interpret career breaks or unconventional experiences. Despite technological evolution, the human interview remains the decisive moment to assert one's real skills. For those looking for work or wishing to evaluate their contractual situation in a market influenced by these changes, the use of comparison tools is increasingly useful. Before facing selection interviews in companies that use automated systems, it is helpful to have a clear understanding of one's salary and contractual position. By using our salary calculator, it is possible to obtain a precise estimate of your remuneration based on your profile, helping you to navigate the challenges of a labor market in continuo...
Punti chiave
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Frequently Asked Questions
- Why can AI be discriminatory in personnel selection?
- AI uses historical data to train its algorithms. If this data reflects past biases or traditionally linear career paths (more common among men), the system will tend to penalise those with gaps, part-time work or career changes, often disadvantaging women and some minorities.
- What risks have Swiss companies reported in 2026?
- According to Manpower's quarterly report, HR managers reported cases of wrongful exclusion of qualified candidates and receiving proposals for profiles unsuitable for open positions, indicating that automation is not always able to correctly assess the required skills.
- What do experts suggest to improve the use of AI?
- Experts, including political scientist Anna Jobin and Professor Solange Ghernaouti, suggest that AI should not be left to technicians alone. A collective approach and regulation that incorporates diverse perspectives are needed, preventing biases from becoming unquestionable because they are embedded in the software.