Women in AI: Why It Matters and How It’s Shaping the Future

Mar 9

5 min read

Artificial Intelligence is transforming how we live, work, and connect - revolutionizing fields like healthcare, finance, and education. As we reflect on progress and challenges on International Women's Day, it is worth highlighting the crucial role women play in shaping the future of AI, while addressing persistent gender gaps that continue to limit equal participation. AI-driven technologies are simplifying processes, improving decision-making, and enhancing human capabilities like never before. However, AI is only as effective as the minds that build it, making diversity in the field crucial to ensuring fair and inclusive advancements. Index

1. The Growing Impact of AI and the Role of Women

2 . Breaking Barriers Despite Underrepresentation

3. Trailblazers: Women Leading AI Innovation

4. The AI Gender Gap: Challenges by the Numbers

5. Why Diversity in AI Matters

6. Closing the Gap: Initiatives Driving Change

7. Towards an Inclusive AI Future

1. The Growing Impact of AI and the Role of Women

Women have shaped AI in transformative ways, yet their contributions often go unrecognized. According to a World Economic Forum (WEF) report in 2024, only 22% of the professionals working in AI across the world are women, and the figure is lower for top leadership positions.

2. Breaking Barriers Despite Underrepresentation

Besides their contributions, women in AI still face significant barriers. As per studies, women hold fewer than 15% of the highest positions in AI companies and are authors of fewer than 14% of AI research papers. This disparity also leads to biased AI algorithms that disproportionately affect underrepresented populations.

Still, despite these challenges, women leaders are making tremendous strides. Initiatives like Women in AI, AI4ALL, and Black in AI are creating spaces where women can thrive: offering mentorship, networking, and skills training. Companies and policymakers recognize that diversity strengthens AI, making it more effective and equitable.

3. Trailblazers: Women Leading AI Innovation

The future of AI isn’t just shaped by algorithms: it's shaped by the brilliant minds behind them. Here are some of the women leading the charge in areas like deep learning, natural language processing (NLP), computer vision, and ethical AI:

Dr. Fei-Fei Li - Human-Centered AI Advocate

Dr. Fei-Fei Li is a leading figure in computer vision, deep learning, and she created the ImageNet project that revolutionized training AI models. She is a vocal champion of human-centered AI, making sure AI systems are fair and inclusive. She co-founded World Labs in 2024, which specializes in spatial intelligence and generative AI.

Mira Murati - Leading Generative AI at Thinking Machines Lab

Mira Murati, ex-CTO of OpenAI, was instrumental in creating ChatGPT, DALL·E, and GPT-4o, spearheading generative AI innovation. She is a prominent voice for AI regulation and ethical implementation. In February 2025, she established Thinking Machines Lab, uniting the best researchers from OpenAI, Meta, and Mistral to create innovative AI solutions.

Dr. Joy Buolamwini - Championing Fair AI

Dr. Joy Buolamwini is the founder of the Algorithmic Justice League, an organization dedicated to exposing and mitigating bias and AI systems. Her research at MIT revealed significant gender and racial biases in commercial facial recognition technologies, leading to global debates on AI fairness. She continues to advocate for transparency in AI and the implementation of fairness-focused regulations in AI development.

Dr. Timnit Gebru - Ethical AI and Accountability Advocate

Dr. Timnit Gebru is an acclaimed researcher of AI ethics and co-founder of Black in AI, a community supporting Black professionals in artificial intelligence. She later founded the Distributed AI Research Institute (DAIR) to develop AI solutions with a strong emphasis on social responsibility and fairness. In 2024, she still voices greater accountability of AI, dismantling corporate AI bias, and demanding diversified AI research teams.

Dr. Rana el Kaliouby - Innovator in Emotion AI

Dr. Rana el Kaliouby is a pioneer in Emotion AI, co-founding Affectiva, a company specializing in AI that interprets human emotions through facial and vocal expressions. Her work has widespread applications in healthcare, automotive safety, and human-machine interaction. She strongly advocates for diversity in leadership in AI so that AI technologies consider the emotional and psychological aspect of human interaction.

These women are driving innovation in ethical AI, generative models, and human-computer interaction: though underrepresented, they are paving the way for a more inclusive and ethical AI future. Their research indicates that diversity in AI is directly correlated to better, equal, and richer technology.

4. The AI Gender Gap: Challenges by the Numbers

Despite their achievements, women in AI still face significant challenges that limit their full participation in the field. Persistent biases, lack of representation at leadership levels, and few opportunities to be involved in research work remain obstacles despite growing awareness and advocacy campaigns:

Workforce Representation: Women constitute approximately 22% of AI professionals globally, indicating a substantial underrepresentation in the field; Leadership Positions: The gap grows larger at senior levels, with women occupying fewer than 14% of executive roles in AI companies;
Research Contributions: Women authors contribute to fewer than 14% of AI research articles globally, highlighting a large disparity in academic contributions;
Academic Pipeline: In academia, women occupy about 22% of AI faculty roles, a number that has experienced only limited growth over the last decade.

Closing this gap requires joint efforts from educators, industry leaders, and policymakers to create an AI landscape where everyone has a seat at the table.

5. Why Diversity in AI Matters

Women's underrepresentation in AI affects both equity and the quality of technological advancements:

Consequences of Homogeneous AI Development

A study across 133 AI systems in various industries revealed that approximately 44% were found to be biased towards gender and 25% were biased toward both gender and race. These biases can be seen in technologies like facial recognition technology, which has been found to function less effectively on women of color, generating higher error rates for the identification of non-white women's faces.

The Value of Diverse Perspectives

Including diverse perspectives in AI development is crucial for creating inclusive and effective technologies. Teams that include members from varied backgrounds are more likely to challenge assumptions, identify potential blind spots, and design solutions that are effective for a wider population.

Women and particularly women of color can bring essential insights that help ensure AI systems serve all users fairly and equitably. According to UN Women, the AI platforms often reflect the biases and values of their creators; thus, the lack of diverse opinions becomes a cause of concern with respect to equality and representation.

Economic and Innovative Implications

Beyond ethical considerations, the gender gap in AI represents a significant loss of human talent in an increasingly expanding high-demanding field.

Excluding women limits AI’s potential, stifling innovation and diverse problem-solving. A gender-diverse AI workforce fosters creativity, stronger research, and more inclusive products.

Besides fairness, excluding women from AI worsens skill shortages and limits innovation.

6. Closing the Gap: Initiatives Driving Change

The good news? Change is happening. Here’s how we can accelerate it:

STEM Education & Outreach: A key strategy is attracting more girls and young women to AI-related roles. Initiatives like Girls Who Code, AI4ALL (co-founded by Fei-Fei Li), and various coding camps expose girls to computing and AI early on. Such efforts have helped bring about a gradual but increasing number of women entering AI careers over the last decade.

Mentorship & Community Networks: Mentorship initiatives and peer networks assist women in AI in navigating what has historically been an old boys' club. Organizations like Women in Machine Learning (WiML) and Women in Data Science (WiDS) create support groups for women to network, learn from one another, find mentors, and collaborate on research. Similarly, affinity groups (such as, Black in AI, Women in AI nonprofits, and “100 Brilliant Women in AI Ethics” network) also provide solidarity, and voice amplification for women, facilitating retention of talent, and building confidence.

Inclusive Workplace Practices: Many tech companies and research institutions are recognizing the value of diversity and making efforts to create it. This includes fair hiring practices (e.g. diverse interview panels, modifying job descriptions), providing mentorship/sponsorship for female employees, and establishing family-friendly policies to improve retention. Companies such as Google, IBM, Microsoft and others have started internal "women in AI" initiatives and set goals to improve representation. These efforts are slowly achieving results - for instance, more women are now leading AI teams or departments than previously. Highlighting these leaders (through awards, media, and conferences), also sets concrete role models for the next generation.

Policy & Global Initiatives: Governments and global organizations are stepping in at a systemic level to address structural obstacles. In late 2024, the Global Partnership on AI (GPAI) released a worldwide policy report calling for “transformative AI policy for gender equality” - with recommendations from funding STEM programs for girls to enforcing accountability for diversity in AI projects. UNESCO’s Women4Ethical AI platform in another initiative that aims at equal representation of women in the development of AI systems. Such policy recommendations highlight that ethical AI should have diverse teams by design and urge stakeholders to invest in gender-party initiatives. There is also growing advocacy to measure and publish diversity metrics in AI organizations, putting transparency pressure on institutions to improve. These initiatives provide young women with role models and skills, demonstrating that success in technology isn't gender-limited. Women are presenting AI research, leading startups, and shaping AI ethics policies. Each step forward creates a ripple effect: as more women excel in AI, they inspire others to join and stay in the field.

7. Towards an Inclusive AI Future

Women in AI are rewriting the future - one breakthrough at a time. Their dual role as innovators and advocates is redefining the future of AI for the better. Yet, as the statistics remind us, much work remains to achieve parity. In a world where AI promises to touch nearly every dimension of life, ensuring women’s voices shape AI is not just the right thing to do - it’s essential for a better, more equitable future. Change starts with awareness and action. Support organizations advocating for women in AI, amplify the work of female AI leaders, and push for diversity in your workplace or academic institution. Whether it’s mentoring, investing in inclusive hiring, or simply challenging biases in AI discussions - every step counts toward a more equitable AI future.