The risk that Artificial Intelligence (AI) will magnify existing gendered harms and create new ones is relatively established among academic circles. Scholars highlight how AI replicates gender biases in the results of search engines or in the use of AI-driven technologies in employment or banking-related decisions when such technologies are designed, deployed, and used without due attention to gendered impacts. Yet, a question remains as to whether these gender perspectives are being incorporated into the AI-related laws emerging globally. At the time of writing, the race to regulate AI is intensifying, but too few initiatives pay attention to the gender-related challenges generated by AI systems. The vast majority of proposed or actual laws fail to adequately address gendered harms, if at all. In this article, I offer emerging global good practices to translate this gendered knowledge into legislation and seek to understand how an intersectional gender lens can be incorporated into domestic law. In Part II, I set out what is AI, what are its gendered implications and how do AI technologies replicate existing societal gender biases. I discuss the allocative harms of AI and the representative harms and elaborate upon an emerging but largely under-acknowledged harm, equality gaps in AI literacy. In Part III, I turn to the question of regulating AI with gender in mind. I seek to arrive at a better understanding of how non-discrimination, equality, and bias can be incorporated into the laws governing AI. A comparative multi-jurisdictional study, I draw upon the legislative debates unfolding in the US, Japan, China, and Australia before turning to the more promising examples emerging from the EU, Canada, and Brazil. I conclude by considering how we might regulate better to achieve algorithmic fairness for a greater diversity of women.