"The AI and Data Science Bootcamp for Women and Minoritised Groups was designed to actively address the diversity gap in the AI field by lowering the entry barriers that women and minoritised groups face and empowering them with advanced technical and personal development skills to succeed in the AI and tech field. The theory of change of the programme was the product of an extensive literature review on the causes and consequences of the diversity gap in the tech industry and of FAIR Forward’s own experience across different fields of AI, from NLP to agri-tech climate action and capacity building. This effort evolved into a programme designed to attract women of all ages, backgrounds and caregiving responsibilities, aiming to open the door to their entry into the tech field. Small actions (childcare spaces, flexible schedules), while administratively intensive, enabled focused cohorts with peace of mind, fully present. Support for participants from diverse professional and geographical backgrounds expands the concept of inclusion to beyond young, working professionals in a capital city. One of the key outcomes of this gender-responsive initiative was demonstrating that the lack of diversity in the AI field cannot be attributed to a lack of interest from underrepresented groups. The Bootcamp received 7.600 applications for just 120 slots, which is clear evidence of strong interest and motivation. This underscores a crucial point: women do not need to be ‘fixed’; it is the systems that needs to change. There is no one ‘right way’ to conduct a curated programme like this. However, as demonstrated by past and upcoming iterations of the Bootcamp, success lies in adhering to the core principle of ‘leaving no one behind’. By conducting thorough research at the outset to understand the nuances of different economies, ecosystems and the specific needs of the target audience, such training programmes can not only succeed but also be effectively scaled to diverse locations and populations." (Conclusion, page 32)