AI's Missing Link: The Gender Gap in the Talent Pool.

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Autor/inn/en	Lazzaroni, Ruggero Marino; Pal, Siddhi
Institution	interface - Tech analysis and policy ideas for Europe
Titel	AI's Missing Link: The Gender Gap in the Talent Pool. Gefälligkeitsübersetzung: Das fehlende Glied in der KI-Kette: Die Geschlechterkluft im Talentpool.
Quelle	Berlin (2024), 41 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Monografie
Schlagwörter	Frau; Künstliche Intelligenz; Region; Großstadt; Beschäftigungsstruktur; Erwerbstätiger; Fachkraft; Informationstechnischer Beruf; Informationswirtschaft; Internationaler Vergleich; Geschlechterverteilung; Quote; Welt; Europäische Union; Arbeitnehmer; Ausländer; Einwanderer; Führungskraft; Europa; Herkunftsland
Abstract	"The artificial intelligence (AI) industry is facing a critical diversity crisis, with women severely underrepresented across all seniority levels. This data brief quantifies the multifaceted underrepresentation of women in the global and European Union (EU) AI talent pool, highlighting the pressing need for targeted interventions to increase female participation in this rapidly expanding field. Our analysis of data on nearly 1.6 million AI professionals worldwide reveals stark gender imbalances. Women comprise only 22% of AI talent globally, with even lower representation at senior levels - occupying less than 14% of senior executive roles in AI. Within the EU, the disparity is equally concerning. Europe has closed 75% of its gender gap, with Sweden and Germany among the top five European economies in closing the gender gap. However, our data reveals a stark contrast in the AI sector: Germany and Sweden have some of the lowest female representations in their AI workforces in the EU, at 20.3% and 22.4% respectively. This discrepancy raises serious questions about the unique barriers faced by women in the AI field. This gender gap in AI talent pools is significantly more pronounced than in the overall workforce. In countries like Portugal and Estonia, which have achieved near gender equity in their general labor force, the AI sector shows dramatic imbalances of up to 51%. Even in leading AI hubs, diversity remains a challenge. In Frankfurt, a major European tech center, just 19% of AI talent is female. Milan leads among European AI hubs with 30.7% female AI professionals, still far from parity. This underrepresentation of women in AI has serious implications, potentially exacerbating biases in AI systems and limiting innovation. While having more women and underrepresented groups in AI won't automatically fix existing biased data sets, it will drive a push for more diverse and representative data collection over time. Diverse teams are more likely to question the status quo, recognize gaps in data collection, and advocate for more inclusive practices. The gender gap also represents a significant loss of potential talent in one of the most crucial industries of our time. As AI becomes increasingly central to innovation and economic growth, we're essentially operating at partial capacity. In our last data brief, we highlighted the heated global demand for AI talent and the brain drain causing a significant talent shortage in many countries. Increasing the number of women in AI is not just about equity-it's about meeting the pressing need for more AI specialists overall. Addressing this diversity crisis is not just a matter of equality, but crucial for developing AI systems that work equitably for all of society. As the EU aims to become a global leader in AI, closing the gender gap must be a priority. This will require multi-faceted efforts, from encouraging more girls and women to pursue STEM education to improving workplace cultures and retention of female talent in AI careers. With AI poised to reshape numerous industries, ensuring diverse perspectives in its development is essential for realizing the full potential of this transformative technology and upholding democratic values in an increasingly AI-mediated world." The study refers to the period 2023-2024 (Author's abstract, IAB-Doku).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2026/4