This paper explores pervasive gender data gaps affecting the global majority, highlighting their negative impact on health, particularly among women and girls. When these data gaps persist, the rapid use of AI can exacerbate existing inequalities by failing to fully incorporate the global majority’s experiences. We argue that synthetic data can be a powerful tool for addressing these gaps by generating representative datasets that reflect diverse gender experiences. While acknowledging the risks associated with synthetic data, including potential biases and cybersecurity threats, this paper emphasises the need for robust methodologies, ethical frameworks and guidelines to ensure its responsible use. By integrating real-world data and fostering collaboration with gender experts, we advocate for a multifaceted approach to AI development that prioritises gender equality. Ultimately, we call for policies that promote inclusive research and data practices, ensuring synthetic data contributes to equitable health outcomes for the global majority.