Women remain significantly underrepresented in computing and artificial intelligence (AI), facing barriers such as limited access to tools, training, and opportunities. As AI becomes increasingly integral to daily life, it has the potential to address these disparities and foster greater inclusion. Realizing this potential requires fair access, inclusive design, and strategies that actively promote confidence, participation, and representation. This study explores these dimensions, identifying pathways for AI to serve as a catalyst for change.A key finding is the lack of tools explicitly designed to support women's participation in AI. Beyond reducing bias, fostering diversity in AI development requires designing artifacts that actively promote knowledge, skills, and confidence. Empowerment in this context refers to equipping individuals to engage with and influence AI, whether as users or developers. Women's participation in AI can thus be understood as a cyclical process, where increased engagement leads to further inclusion and representation in the field.The research objective of this study is to provide information on the relation between empowerment and women in AI, using the Systematic Literature Review (SLR) methodology. The SLR proposes and analyzes 14 studies that serve as a basis to understand the relationship between women, empowerment, and AI.The results show that there is still scarce research explicitly connected to AI artifacts designed for empowerment, but there is a growing recognition of its importance. The SLR also reveals various challenges and success factors related to the role of AI in fostering gender inclusivity and empowerment, which calls for further attention.As further work, the authors will conduct empirical research to validate the findings and gather new insights, while co-designing an artifact to empower women in AI.
The Beauty of AI and Why AI Needs More Women
While women remain underrepresented in the Artificial Intelligence (AI) and tech workforce, their participation is considered crucial for developing the right AI for tomorrow.
Brief: Advancing gender equality through partnerships for gender-responsive artificial intelligence
Artificial intelligence (AI) can advance gender equality but may also perpetuate inequalities if not managed properly. This UN Women publication emphasizes the need for inclusive, safe, and equitable AI systems. It highlights the private sector's role in achieving this and calls for partnerships to support women in AI leadership, foster opportunities for women entrepreneurs, bridge the gender digital divide, and ensure AI policies integrate gender dimensions.
AI Development Needs More Women. Here’s What Leaders Can Do About It
Only 31% of professionals in AI development are women—learn how female talent can drive accountability, improve accuracy and improve AI's societal impact.
Paid Program: Why More Women Are Needed in AI
When the world of AI isn’t inclusive, it creates biases in what the data shows and how it’s used.
Why we need more Women in AI
In an age where artificial intelligence (AI) shapes much of our daily lives, the conversation about diversity in this field has taken on a…
Why We Need More Women In The AI Revolution
Research suggests that women make up less than a third of AI professionals and only 18% of AI researchers globally.
From users to architects: Why girls must shape the future of AI
If girls aren’t shaping AI, we’re building a broken future. Empowering young women in tech is now a global necessity, not just a matter of fairness.
Opinion: A gender gap is emerging in AI adoption, and women risk being left behind
Women appear less inclined to use AI tools, producing a disadvantage they can ill afford
Women and AI: The Gender Gap in AI Adoption and Recognition [Data]
Lean In’s survey shows how women are losing out in the AI age. Learn how women and men compare in AI adoption in the workplace, recognition, and more.
The 'AI gender gap' narrative is missing the full picture | Fortune
New research shows women leaders are shaping AI strategy, ethics, and oversight—even as concerns about adoption gaps persist.
A Proposed Conceptual Framework for Understanding Gender Disparities in Artificial Intelligence Adoption
This conceptual paper investigates the issue of gender disparities in artificial intelligence adoption within organizational settings. It highlights the importance of addressing these differences for workplace inclusivity and performance. The problem lies in the unequal of artificial intelligence adoption between male and female employees’ perspectives. The proposed framework is developed through a review of existing literature highlights differences between male and female employees in their artificial intelligence adoption. The methodology is based on conceptual analysis, derive on previous studies to build a comprehensive understanding of gender disparities in artificial intelligence adoption. An Independent T-Test will be used to analyze the disparities between male and female Malaysian sports graduates in testing the hypothesis development. By addressing these disparities, the paper provides insights into creating inclusive strategies that promote gender equity in the workforce. Overall, the findings aim to guide both researchers and practitioners in designing gender equality policies that address challenges to equal adoption of artificial intelligence.
Report: Where are the women? Mapping the gender job gap in AI
As AI becomes ubiquitous in everyday life, closing the gender gap in the AI and data science workforce matters.
Women Business Leaders on How To Solve AI’s Inclusivity Problem
Top executives at Takeda, PepsiCo and Meta discuss making AI more inclusive and preparing the next generation of women leaders for change.
Barriers to AI adoption for women in higher education: a systematic review of the Asian context
Artificial Intelligence (AI) is transforming higher education rapidly by enabling personalized learning, enhancing administrative processes, and improving access to educational resources. However, disparities in AI adoption, particularly among women in the Asian context, raise concerns about equity, inclusivity, and access. This disparity could lead to a deficit in AI skills among women, affecting their ability to contribute as effectively as men in the future. Therefore, it is necessary to understand the current state of women's adoption of AI and the barriers they face in Asian higher education. The systematic review has been conducted using PRISMA guidelines. This review paper synthesizes the findings from the studies conducted in various contexts of Asia to present an overall picture of the state of AI adoption among women in Asia. A total of 17 studies were selected for this review, highlighting socio-cultural barriers, lack of trust, technological unawareness, biases in AI algorithms, and inadequate representation of women in AI policy formulation. Besides highlighting these barriers, the results also shed light on recommendations given by earlier studies that facilitate and encourage women to adopt AI in higher education. Based on the Asian perspective, the conclusion proposes specific recommendations for policymakers and practitioners to promote inclusive AI that empowers women in Asia to contribute more effectively to higher education.
The Gender Gap in AI: Why We Need More Women in Artificial Intelligence - EIT Campus
Artificial intelligence is shaping our future, but who is shaping AI? In this blog, we explore the insights of Megi Mejdrechová, co-founder of RoboTwin, a…
Gender differences in artificial intelligence: the role of artificial intelligence anxiety
INTRODUCTION: Artificial intelligence (AI) is having a significant impact on people's lives. Despite the benefits associated with this technological advancement, there may be gender-related inequalities in accessing and using AI systems. The present study aimed to test gender differences in factors likely to influence AI adoption, in particular, the moderating role of gender in the relationship between AI anxiety and positive attitudes toward AI. METHOD: Participants were 335 adults (52.2% women; mean age = 29.96, SD = 13.88) who filled in an online self-report anonymous questionnaire. To test the hypotheses, both a MANOVA and a moderation model were adopted. RESULTS: Results revealed significant gender differences in AI adoption dimensions, with women reporting higher AI anxiety, lower positive attitudes toward AI, lower use of AI, and lower perceived knowledge of AI. A significant negative relationship was found between AI anxiety and positive attitudes toward AI. An interaction between gender and AI anxiety was found: At low levels of anxiety, women showed lower levels of positive attitudes toward AI than men, while at high levels of AI anxiety, gender differences were less evident. DISCUSSION: These findings suggest that AI anxiety works as a "gender differences leveler." The present study contributes to expanding knowledge about gender differences in technology, which will underpin practical interventions for reducing the gender digital gap. Limitations and future research directions are discussed.
