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

The report examines the 'gender-energy nexus' in the era of AI, highlighting how the digital gender divide and energy poverty disproportionately affect women. It identifies critical challenges, including gender bias in AI development, a deficit of sex-disaggregated energy data, and the risk of AI data centres diverting resources from low-income communities. The authors argue that while AI can optimize energy systems, its current development lacks gender diversity and funding for SDG5 (Gender Equality). The report recommends increasing women's representation in STEM, implementing gender-lens investing, and ensuring women are decision-makers in AI and energy policy to achieve a just transition.

• There is a significant disparity in AI-enabled use cases between energy goals and gender equality goals; while AI can support 134 of 169 SDG targets, SDG5 (Gender Equality) has the lowest number of identified use cases at only 10 out of approximately 600.
• Energy poverty disproportionately impacts women and girls, with an estimated 341 million women and girls projected to lack electricity by 2030, 85 percent of whom are located in Sub-Saharan Africa.
• A 'gender data deficit' in the energy sector leads to AI applications that perpetuate male-oriented biases. A study of 133 AI systems from 1988 to 2021 found that 44 percent displayed gender bias, and 26 percent showed both gender and racial biases.
• The digital gender divide is exacerbated by energy access gaps 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 technical workforces of both the energy and AI sectors. Women make up only 32 percent of the renewable energy workforce and 29 percent of science R&D positions globally.
• AI automation poses a higher 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 due to their overrepresentation in clerical roles.
• There is a stark imbalance in AI funding between energy and gender goals. Between 2018 and 2023, private sector investment in AI for SDG7 (energy) reached USD 49 billion, while investment for SDG5 (gender equality) was only USD 0.62 billion.
• AI data centres can divert critical resources from local communities in low-resource areas. In Lagos, Nigeria, 10 data centres operate in a region where only 21 percent of the rural population had electricity access in 2021 and only 21 percent of the rural population had access to safe drinking water in 2022.

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} }