Opinion: Women are essential to drive data and AI for impact

The climate crisis, access to education, gender inequality, public health emergencies, the need for socioeconomic mobility, and financial inclusion. Calling attention to these seemingly intractable problems is how we open “Skilling that Scales,” the impact report on data.org’s Generative AI Skills Challenge, made possible by funding from Microsoft, with support from EY. We acknowledge that as these pressing issues become even more significant and complex, existing solutions continue to fail the communities most severely affected.

Existing solutions don’t cut it, and neither does the existing workforce.

Women are still being left behind in AI

Around the world, women are still being left behind in data and artificial intelligence. The Generative AI Skills Challenge — our fourth global innovation challenge to date — clearly reinforced that meaningful progress and inclusive growth will be possible only when women are part of the solution. We now have an opportunity not only to help women catch up but to lead.

Of the nearly 5,000 people trained by the five awardees of the Generative AI Skills Challenge, an incredible 87% identify as women or nonbinary. Both the workforce being built and the solutions being created offer insights into the potential to advance gender equality through data and AI.

From Data Elevates, empowering Venezuelan migrant women through a generative AI education-to-employment program to the Global Integrated Education Volunteers Association upskilling women entrepreneurs in Nigeria to use AI to increase sales, social impact organizations across the globe are realizing that considering a gender lens isn’t just an altruistic, nice thing to do — it’s essential to stay competitive.

Moreover, the demand is clearly there.

Across all three of our capacity-building workstreams — digital learning, the Capacity Accelerator Network, and global innovation challenges — women are enthusiastically pursuing opportunities to access AI and build their skills.

Through our India Capacity Accelerator Network Hub, for example, our partners at Ashoka University ran a cohort that was 53% women, despite a growing gender disparity in the country, where only 10% of eligible working-age women participate in the workforce. Our under/over campaign likewise illustrates the many ways in which women and gender-diverse individuals should be better represented and more prominently working on the power of data to drive social impact.

AI’s potential goes beyond technology

That momentum will continue to grow, not only as more organizations expand the integration of generative AI and data solutions into their strategic priorities, but also as the field evolves and we better understand that these tools are not just an exercise in software engineering. They can and should be applied to a range of creative problem-solving approaches for real-world challenges.

Interdisciplinary leaders across sectors — from health care to social services to environmental science and beyond — can all benefit from a better understanding of and skills to meaningfully use data and generative AI. We continue to see that application to these community-centered challenges drives engagement, and women are at the frontline of this next-generation workforce.

At the 79th session of the United Nations General Assembly, appropriately situated during Climate Week, I heard an anecdote that I offer as a humble reminder while we put our collective feet on the gas pedal for women in data and AI. At a breakfast focused on improving gender data collection and accelerating female purpose-driven data capacity, it was observed that we lack a meaningful understanding of how extreme heat — increasingly worrisome amid the climate crisis — affects women. Existing studies focus on elite athletes and men ages 18 to 40, leaving out women entirely. Women must be represented across the continuum: From the data we collect to the analysis we apply, to the solutions we design, and to the workforce we are building.

Walk before we run

Similarly, our approach to workforce capacity building must be both comprehensive and evolving. There is no finish line — only an evolution of need, tied to the changing challenges of communities and the advancements of technology. Generative AI isn’t the silver bullet we’ve been waiting for. It’s a powerful tool, but just a tool — and at the end of the day, we need people with the right skills to use it effectively. That is why data.org is so deeply committed to training 1 million purpose-driven data practitioners by 2032. It is an ambitious goal, but an essential one if we want to accelerate impact.

In the AI race, we must walk before we can run. Closing the digital divide means starting with foundational skills around data ethics, such as our digital learning partnership with the government of India. It means building shared understanding around data governance and offering multimodal skilling programs that meet people where they are, such as the work happening across the Capacity Accelerator Network. It means living at the intersection of what is possible and what is practical like we continue to do with our innovation challenges.

As the Generative AI Skills Challenge showed us, it means ensuring that women have the resources, skills, and connections they need to join the race in the first place.

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