Gender gap in AI development could impact business outcomes, warn industry leaders

As artificial intelligence becomes increasingly central to business operations, experts say the lack of gender diversity in AI development is emerging as a serious concern, with implications for fairness, innovation, and long-term performance. Industry leaders warn that the underrepresentation of women in AI roles may lead to biased systems and products that fail to reflect the needs of diverse users.

According to Harsha Solanki, VP GM Asia at Infobip, the direction AI takes depends largely on the people building it. When development and decision-making are shaped by a limited set of perspectives, businesses risk blind spots that can affect how systems behave in real-world situations. He noted that teams may overlook critical questions during development, such as whether datasets represent all customers, whether systems work equally well across languages and devices, and whether automated decisions are made consistently and fairly.

Solanki said diversity in decision-making does not automatically remove bias, but it significantly reduces the likelihood of errors going unnoticed. He added that organisations need to widen access to skills through structured learning, hands-on projects, and mentorship so that underrepresented groups can participate in technical and leadership roles. When diverse voices are involved in decision-making, companies are better able to identify risks early and build AI systems that customers can trust, he said.

Priya Pandey, Head – People & Culture at Thriwe, said products developed by a limited group often reflect a narrow viewpoint and may not serve the full range of users. As AI becomes more deeply integrated into business and daily life, she said, inclusive design is not just a social responsibility but also a business necessity.

Pandey noted that leaving women out of AI research, product design, and leadership roles could widen existing gaps and create new challenges in the future. Increasing participation of women in these areas would help ensure that technology is more equitable, relevant, and aligned with real-world needs.

Experts say companies that depend on AI must prioritise diversity within their development teams to build reliable and responsible systems. A broader mix of perspectives can improve product quality, reduce the risk of bias, and strengthen user trust, all of which are essential for sustainable growth in an AI-driven economy.