Objectives:
This paper examines gender disparities in culture-related fields and their reproduction across professional, academic, and technological contexts. It aims to: a) identify structural and cultural barriers to women’s advancement; b) analyze how academic publishing and disciplinary divisions shape careers; and c) assess how emerging technologies, particularly artificial intelligence (AI), amplify biases. Emphasis is placed on implications for education, training, and professional development, which can both reinforce and counteract inequalities.

Methodology:
The study draws on international reports, including UNESCO, and recent empirical studies of gender disparities in cultural and creative sectors. These cover participation rates, leadership representation, salary gaps, authorship and citation patterns, and case studies in disciplines like archaeology. Examples of AI use in recruitment, healthcare, and cultural production illustrate technological bias. The approach combines comparative evidence with contextual interpretation, highlighting the intersection of gender with cultural norms, socio-economic structures, and educational opportunities.

Results:
Findings confirm that while women’s participation in the cultural and creative industries has increased, significant inequalities persist. Women are still concentrated in lower-paying positions, underrepresented in decision-making roles, and face limited career progression. Structural barriers, reinforced by gender stereotypes and disproportionate caregiving responsibilities, become especially pronounced at senior levels and among older age groups. In academia, women remain underrepresented as first and last authors in high-impact journals, and citation gaps persist even after accounting for institutional and methodological factors. These disparities accumulate over time, reducing opportunities for recognition, research funding, and mentoring roles. In cultural disciplines such as archaeology, women’s participation has historically been skewed toward lab-based research or specific topics, with fieldwork and leadership roles dominated by men. Although progress has been achieved, gendered divisions of labor continue to shape disciplinary practices.
Technological developments introduce a new dimension to these challenges. AI systems trained on biased datasets have been shown to reproduce societal inequalities. For instance, recruitment tools that systematically favor men, highlight how cultural stereotypes can be embedded in technological infrastructures. Such biases risk creating new barriers in education, training, and professional recognition if left unchecked.

Conclusions:
The persistence of gender disparities in culture-related fields underscores the need for targeted and multi-level interventions. Policies must address structural inequalities, while inclusive educational and training initiatives are required to challenge stereotypes, build equitable career pathways, and foster diverse leadership. Equally, the development of AI and digital tools must be guided by principles of inclusivity, transparency, and fairness. For education and training systems, this means equipping cultural professionals, researchers, and students with both awareness of gender bias and practical skills to mitigate it. Promoting gender equity is not only essential for justice but also for ensuring innovation, diversity, and sustainability in cultural and creative life.

Keywords: Gender disparities, Gender equality, Education and training, Cultural sector, Analytics, Career progression, Authorship and citation, Artificial Intelligence bias, Gender bias, Intersectionality, Inclusive practices.