Artificial Intelligence, Big Data, and Cloud Infrastructures: Policy Recommendations for Enhancing Women's Participation in the Tech-Driven Economy

Favour Amarachi Ezeugwa *

Prairie View A&M University, 100 University Dr, Prairie View, TX 77446, USA.

Oluwaseun Oladeji Olaniyi

University of the Cumberlands, 104 Maple Drive, Williamsburg, KY 40769, United States of America.

Jennifer Chinelo Ugonnia

Ulster University, Centre City House, 7 Hill St, Birmingham B5 4UA, United Kingdom.

Abayomi Shamsudeen Arigbabu

University of Alberta, Edmonton, Alberta, Canada.

Princess Chimmy Joeaneke

University of the Cumberlands, 104 Maple Drive, Williamsburg, KY 40769, United States of America.

*Author to whom correspondence should be addressed.


Abstract

This study investigates the underrepresentation of women in Artificial Intelligence (AI), Big Data, and Cloud Infrastructures, exploring the barriers and challenges they face and assessing the effectiveness of current policies and initiatives to promote gender diversity within the tech industry. Employing quantitative research methods, the study used a survey distributed to 572 female professionals in tech-related roles across various industries, achieving a 67.9% response rate. Multiple regression analysis was utilized to test four main hypotheses concerning barriers to entry and advancement, the inclusivity of educational programs, the impact of diverse teams on innovation and performance, and the effectiveness of gender-inclusive policies. Key findings indicate that the type of organization and specific tech sectors significantly influence the barriers experienced by women. Notably, gender diversity within teams correlates strongly with improved innovation and performance. However, educational and training programs often fail to be sufficiently inclusive, underscoring the need for programs better tailored to women's needs in tech fields. Moreover, the study confirms that implementing gender-inclusive policies substantially increases women's participation in tech roles, especially when these policies are applied long-term. Based on the findings, recommendations are made for adopting comprehensive, inclusive practices at organizational and educational levels, promoting diversity in team composition and leadership, committing long-term to effective policy implementation, and developing supportive networks through mentorship and sponsorship programs. These measures are aimed at reducing gender disparities and enhancing the integration of women into the high-tech economy. The study underscores the critical role that strategic policy-making and organizational change play in fostering an inclusive tech environment that not only addresses gender disparities but also enhances overall industry innovation and performance.

Keywords: Artificial intelligence, big data, cloud infrastructures, women in technology, gender diversity, inclusivity, tech industry policies


How to Cite

Ezeugwa, F. A., Olaniyi, O. O., Ugonnia, J. C., Arigbabu, A. S., & Joeaneke, P. C. (2024). Artificial Intelligence, Big Data, and Cloud Infrastructures: Policy Recommendations for Enhancing Women’s Participation in the Tech-Driven Economy. Journal of Engineering Research and Reports, 26(6), 1–16. https://doi.org/10.9734/jerr/2024/v26i61158

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