The Gender-Energy Nexus in the AI Era: Challenges and Opportunities

This report by Sustainable Energy for All (SEforALL) examines the intersection of gender equality, energy access, and Artificial Intelligence (AI). It highlights how existing gender disparities in energy and digital access are reinforced by AI development biases and funding gaps, while proposing strategies to ensure a gender-just energy transition through diverse AI teams, STEM representation, and gender-responsive policy.

• AI has significant potential to support Sustainable Development Goal 7 (SDG7) regarding affordable and clean energy, but it is severely under-utilized for SDG5 (Gender Equality). Out of approximately 600 identified AI-enabled use cases for the SDGs, only 10 support SDG5, the lowest number of any goal.
• Energy access gaps disproportionately affect women and girls, particularly in Sub-Saharan Africa. UN Women estimates that by 2030, 341 million women and girls will still lack electricity, with 85 percent of them located in Sub-Saharan Africa.
• A significant 'gender data deficit' in the energy sector leads to AI applications that perpetuate male-oriented biases. Because SDG7 lacks gender-specific indicators, AI systems trained on non-disaggregated data often produce suboptimal solutions or unfair resource allocations for women.
• The digital gender divide is exacerbated by energy poverty and sociocultural norms. Men are 21 percent more likely to be online than women globally, a gap that increases to 52 percent in least developed countries.
• Women are severely underrepresented in the energy and AI workforces. Women make up only 22 percent of the traditional energy sector workforce and 32 percent of the renewable energy workforce. In the AI sector, women hold only 12 percent of positions requiring over 10 years of experience.
• AI automation poses a disproportionate risk to jobs traditionally held by women. The ILO indicates that over double the share of women's employment may be disrupted by AI automation compared to men's, largely due to their concentration in clerical and administrative roles.
• There is a stark disparity in AI funding between energy goals and gender equality goals. Between 2018 and 2023, private sector investment in AI for SDG7 reached USD 49 billion, while investment for SDG5 was a negligible USD 0.62 billion.
• AI data centres can divert critical resources from low-resource communities. These facilities require massive amounts of electricity and water; for example, in Lagos, Nigeria, 10 data centres operate in a region where only 21 percent of the rural population had electricity access in 2021.
• Gender-diverse AI development teams are more effective at identifying and correcting algorithmic biases. Research indicates that gender-balanced scientific teams are more likely to produce novel and highly cited papers than same-gender teams.

APA

Strasser, A., & Idem, R. (n.d.). The Gender-Energy Nexus in the AI Era: Challenges and Opportunities. Sustainable Energy for All. https://www.seforall.org/system/files/2024-08/SEforALL_Gender_AI_report.pdf

Chicago

Strasser, Ava, and Rosemary Idem. The Gender-Energy Nexus in the AI Era: Challenges and Opportunities. Sustainable Energy for All, n.d. https://www.seforall.org/system/files/2024-08/SEforALL_Gender_AI_report.pdf.

Wikipedia

{{cite report |last1=Strasser |first1=Ava |last2=Idem |first2=Rosemary |title=The Gender-Energy Nexus in the AI Era: Challenges and Opportunities |publisher=Sustainable Energy for All |url=https://www.seforall.org/system/files/2024-08/SEforALL_Gender_AI_report.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{strasserndgenderenergy, author = {Strasser, Ava and Idem, Rosemary}, title = {{The Gender-Energy Nexus in the AI Era: Challenges and Opportunities}}, institution = {Sustainable Energy for All}, url = {https://www.seforall.org/system/files/2024-08/SEforALL_Gender_AI_report.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }