By Sophia Velastegui: C200 member, AI advisor for the National Science Foundation; Former Microsoft Chief AI Technology Officer and General Manager, AI Product; former Google/Alphabet and Apple, where she partnered with multiple universities and government entities around AI and emerging technology; Board Director at Blackline (NASDAQ); and member of Georgia Tech’s President’s Board. Read more on LinkedIn.
Artificial intelligence is reshaping industries, economies, and daily life, but its roots run deeper than the breakthroughs of today’s tech giants. Women make up 50% of the global consumer market, yet AI products often fail to meet their needs because those developing the technology do not reflect their experiences. If AI is to be an effective business tool, it must be built by those who truly understand its customers. This oversight isn’t merely an equity issue—it’s a missed business opportunity.
Understanding Women Means Capturing Market Value
In business, understanding your customers is everything. AI thrives by accurately predicting consumer behaviors, delivering personalized experiences, and meeting market demands. Without diverse leadership and developers, companies risk creating AI solutions misaligned with women’s needs, ultimately losing market share and profitability.
Consider voice recognition technology, foundational to virtual assistants like Siri and Alexa. Early algorithms trained predominantly on male speech patterns often misinterpreted women’s voices, frustrating users, delaying adoption, and resulting in expensive product fixes. Understanding and including women’s perspectives from the start could have prevented these costs.
Real Costs, Real Consequences: The Healthcare Example
Healthcare vividly illustrates the risks and costs associated with excluding women from AI development. One notable example involved an AI diagnostic tool for heart disease that initially failed to recognize symptoms commonly seen in women because it relied heavily on male-dominated datasets. Hospitals faced costly retraining, regulatory challenges, and compromised patient outcomes due to missed diagnoses. In fact, a University College London study revealed AI systems predicting liver disease from blood tests were twice as likely to overlook the disease in women as in men, a severe oversight rooted in gender-biased data.
Similarly troubling, these flaws are more than technical—they are life-threatening, expensive mistakes that underscore the real-world implications of lacking gender diversity in AI development.
Conversely, initiatives led by women, like AI-driven breast cancer diagnostics developed at MIT and Google, demonstrate the immense value of inclusive perspectives. These targeted diagnostic tools, specifically designed with women’s physiology in mind, have substantially improved early detection, saved lives, and reduced healthcare costs. Such examples illustrate the power and necessity of integrating diverse voices into AI leadership.
Fintech’s Untapped Opportunity
In financial services, AI-driven tools must consider distinct ways women manage money, access credit, and invest. Traditional AI lending models often overlook women’s financial behaviors, limiting capital access for women entrepreneurs and depriving financial institutions of significant profit opportunities.
Yet women-led fintech firms are changing this narrative, developing AI-powered platforms explicitly designed for women’s financial realities. Tailored credit analysis tools, investment platforms, and financial planning applications developed with women’s financial habits in mind have already demonstrated strong market traction. These innovations don’t simply benefit women; they also present substantial untapped revenue streams for banks and fintech firms. Women-led fintech is a savvy business move.
Diversity in Data: Beyond Ethics to Economic Success
It’s tempting to frame AI diversity simply as an ethical imperative, but its primary benefit is economic. Diverse AI teams inherently have broader perspectives, leading to richer, more accurate data models. This means fewer costly fixes, less market friction, and higher consumer adoption.
Importantly, advocating for inclusive AI isn’t limited to women. Many men in AI recognize that accurate data diversity translates directly into better business outcomes. Diverse perspectives and experiences drive more accurate predictions, relevant products, and stronger customer engagement, delivering real-world profitability.
Women-led teams at tech giants such as Microsoft, Google, and OpenAI have shown remarkable results by fine-tuning AI-driven customer insights, creating intuitive products that resonate deeply with female consumers. These products not only sell better, they redefine markets. AI designed with diverse leadership perspectives is both ethically sound and strategically superior.
To leverage this competitive advantage fully, businesses must prioritize funding women-founded AI startups, which currently receive only a fraction of venture capital investment despite often delivering higher returns on investment. Investing strategically in women-led AI businesses is not philanthropy—it’s an investment in growth, innovation, and profitability.
AI Must Reflect Society to Serve It
As AI increasingly influences decisions in healthcare, finance, and consumer technology, businesses cannot afford to overlook the insights of half their market. Companies that understand and anticipate the needs of all consumers will dominate the next wave of AI-driven innovations. Those failing to do so risk obsolescence and market irrelevance.
The future of artificial intelligence will be defined by its leaders. Ensuring women are among them isn’t just fair—it’s essential for capturing value, driving growth, and sustaining competitive advantage. Embracing diversity at every AI decision-making level positions businesses to lead in a rapidly evolving marketplace.