AI in recruitment: risks and opportunities in Ticino

Context

TL;DR

• AI reshaping recruitment in Ticino, raising ethical concerns
• Algorithms favor linear career paths, penalizing unconventional ones
• AI may amplify biases, discriminating against women and minorities
• Human oversight crucial to prevent systematic errors in hiring

Key facts

• Cosa: AI is reshaping recruitment processes in Ticino
• Quando: Second quarter of 2026
• Dove: Canton of Ticino, Switzerland
• Chi: Bea Knecht, founder of Zattoo
• Chi: Solange Ghernaouti, professor at the University of Lausanne
• Chi: Anna Jobin, political scientist
• Importo: AI systems may exclude outstanding female profiles with non-linear career paths
• Scadenza: The challenge for 2026 and beyond is to learn how to govern AI in recruitment

Artificial intelligence is reshaping employment dynamics in Switzerland and the Canton of Ticino, introducing significant innovations in recruitment processes. According to the Manpower quarterly report published for the second quarter of 2026, employers maintain a cautious stance regarding hiring forecasts, while seeking to optimize operational efficiency through the integration of automated recruitment systems. Although the stated goal is to accelerate talent acquisition and foster flexibility, the use of algorithms is raising profound ethical and regulatory questions.

The issue of historical data

The central issue concerns the very nature of algorithms, which learn based on historical data. Since past databases often reflect corporate structures where professional continuity was the dominant parameter, systems tend to favor linear and uninterrupted profiles. This algorithmic bias penalizes those who have experienced less conventional career paths. As highlighted by Bea Knecht, founder of Zattoo, the risk is that the system, by not finding documented traces of certain paths, ends up ignoring the complexity of working life, especially regarding women. Solange Ghernaouti, a professor at the University of Lausanne, warns that automation risks transforming latent prejudices into indisputable technical decisions. This phenomenon turns AI into an amplifier of inequalities, where discrimination against women and minorities is embedded in the software, making it difficult to identify and counter. Local companies, while seeking to modernize, must therefore manage not only the efficiency of the software but also the responsibility for the decisions made by the systems they use, in a context where human oversight remains, at least at this stage, an indispensable element to prevent systematic errors in resume management.

Operational details

The practical implications of AI use in the Ticino job market are far-reaching and directly impact candidates' daily lives. When a company adopts an automated selection system, a CV is no longer reviewed solely by a human resources manager but instead passes through an algorithmic filter that assigns a score based on keywords and temporal continuity. For workers, this means gaps in employment, part-time roles, or career shifts may be interpreted by the software as red flags, leading to automatic exclusion even before the interview stage.

Before vs After: Comparison Scenarios

To grasp the impact of this transition, it's essential to examine how evaluation processes have evolved in recent years. Before the widespread adoption of AI, a human recruiter could contextualize gaps in a CV, understanding family or personal needs. Today, algorithms tend to dismiss profiles based on rigid patterns. Companies have started reporting discrepancies between expectations and outcomes, citing cases of unsuitable profiles recommended by systems or, conversely, the loss of valuable talent due to overly restrictive filters. The table below highlights the key differences observed in selection processes:

The main concern raised by HR managers revolves around the quality of profiles proposed by these systems. It’s not uncommon for algorithms, in their quest for the 'ideal' candidate based on historical male models, to exclude outstanding female profiles with non-linear career paths. This scenario calls for urgent reflection on the need for technical and human oversight to prevent AI from becoming a discriminatory filter rather than a supportive tool—something many advocates of innovation see as a means to equalize access to job opportunities.

📊 The Human Touch in AI-Driven Hiring AI tools are reshaping recruitment processes, but their rigid frameworks risk overlooking unique career trajectories. Balancing automation with human judgment remains critical to ensure fair and inclusive hiring practices.

⚠️ Key Takeaway While AI can streamline recruitment, unchecked algorithms may perpetuate biases. Cross-border workers in Ticino must stay informed about these shifts to navigate the evolving job market effectively.

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Key points

Addressing the integration of AI into the labor market requires an approach that goes beyond mere technical expertise. According to experts, it is not enough to simply increase gender representation within scientific teams; a pluralistic vision capable of proposing ethical alternatives is needed. Political scientist Anna Jobin has strongly emphasized the need not to delegate control solely to technicians, calling for a collective responsibility that explicitly integrates the female perspective during the design and monitoring phases of selection systems.

Recommended procedures and steps for candidates

To navigate this scenario, candidates must be aware that their CV might be evaluated by software. Here are some strategic steps to optimize profile presentation: 1. Tailor the CV to the specific keywords of the job posting, as scanning systems look for precise matches. 2. Include clear descriptions of skills acquired even during periods of inactivity or part-time work, transforming 'gaps' into periods of training or the acquisition of transferable skills. 3. Check if the company specifies the use of AI systems in selection, trying to see if direct human contact is possible to supplement the profile presentation. 4. Maintain an updated professional presence on industry digital platforms, which are often analyzed by algorithms as a complementary data source.

Companies, for their part, have an obligation to monitor the results produced by algorithms, periodically verifying that no biases or discrimination against specific groups occur. The challenge for 2026 and beyond will not be to eliminate AI, but to learn how to govern it. As suggested by Bea Knecht, the key lies in accessibility: women and candidates in general must understand how these tools work to turn them to their advantage rather than being subjected to them. To evaluate your position in the current labor market or compare your salary situation, you can use the salary calculator available on the portal.

Source: tvsvizzera.it