As part of Women’s History Month, we’re sharing the following reflection from our partner Ariela Agosin on the importance of including women in the development of artificial intelligence and sustainability.
While the conversation about artificial intelligence revolves around productivity and growth, and the conversation about sustainability focuses on climate urgency, governance, and people, the conversation about gender is often reduced to gaps and representation. However, we rarely connect these three concepts as part of the same strategic equation. And we should.
The next wave of innovation will not be merely technological. It will be systemic. And within that system, women’s participation in the design, development, and governance of AI will be crucial to ensuring that technology drives—rather than undermines—sustainability.
Today, AI is redefining operations across all industries, generating significant benefits. But technology is not neutral. The data that feeds it, the priorities that guide it, and the problems it chooses to solve are decisive in its outcomes. This raises the key question: who is designing and providing these key elements?
If AI is going to decide what to optimize, what to measure, and what to prioritize, diversity in its development ceases to be a symbolic matter and becomes a question of efficiency and sustainability. Systems trained without a diverse perspective tend to reproduce biases, obscure social impacts, and underestimate critical variables.
Therefore, incorporating more women into data management, engineering, technology strategy, and leadership is not merely an equity policy. It is a policy of smart innovation, an issue that is clearly a priority today in all development and planning, in both the private and public sectors. Evidence shows that diverse teams manage risk better, anticipate complex scenarios, and make more robust decisions in uncertain contexts. And if anything characterizes the climate and digital challenges, it is precisely uncertainty, which is why this equation is absolutely applicable to the concepts this column aims to address.
Thus, the point of convergence between women, AI, and sustainability lies in how women’s participation in the development and training of AI enables it to achieve better, more efficient, and sustainable results, driving the reinvention and improvement of organizational operations. The cloud, data, and artificial intelligence can become drivers of energy efficiency, emissions reduction, and resource optimization. But only if they are guided by clear principles of governance, accountability, diversity, and long-term vision.
It is not enough for future innovation to be merely faster; it must also be more efficient, sustainable, and mindful. If we want artificial intelligence to contribute to real sustainable development, we need to broaden the range of people involved in its design and leadership. We need more women making decisions in technology, more women setting investment priorities, and more women integrating digital business models.
Because the challenge is no longer just technological. It is cultural, economic, and structural. And women’s leadership and participation are a key part of the solution.
Column written by:
Ariela Agosin | Partner | aagosin@az.cl
