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How the booming investment in AI is leaving women behind

The average capital raised by women-founded artificial intelligence (AI) companies is six times lower than the average capital raised by an all-male team, data shows.
The average capital raised by women-founded artificial intelligence (AI) companies is six times lower than the average capital raised by an all-male team, data shows. Copyright Canva
Copyright Canva
By Oceane Duboust
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The average capital raised by women-founded artificial intelligence (AI) companies is six times lower than the average capital raised by an all-male team, data shows.

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The tech industry has a long history of underfunding and not attracting or retaining women in the sector - with data showing that this also extends to AI.

For the decade 2012-2022, 80% of the total capital invested by venture capitalists (VCs) in AI was raised by all-male teams.

In contrast, all-female teams raised a mere 0.3% in the UK, a report from the Alan Turing Institute published last month shows.

Moreover, the average capital raised by women-founded AI companies is six times lower than the average capital raised by an all-male founder team.

“This is significantly lower than the equivalent proportion when looking across all sectors. Simply put, this problem is worse in AI,” Dr Erin Young told Euronews Business. 

Young also highlightedconcerns regarding the recent boom in interest and investment in machine learning and said thedisproportionate funding is raising concerns, especially regarding how it could perpetuate biases in AI-powered tools and software.

“The people who fund and build AI technologies obviously bring their priorities, backgrounds and value systems, which in turn underpin the design and implementation of the safety and responsibility of AI,” said Young.

An optimistic take though, is that there has been an upward trajectory in recent years.

The Institute gave several recommendations to achieve a better balance in the future. One of them is “to establish incentives and targets for recruiting, up-skilling, retaining and promoting women” and make inclusion a key performance indicator (KPI).

The other recommendation includes supporting an inclusive company culture when it comes to the workplace organisation.

With the booming interest in AI came heavy investment in related companies. Topping the ranking, OpenAI rose over $11 billion (€10.30 billion) in value and is now at $80 billion, according to the Wall Street Journal. 

The phenomenon is also observed at lower levels in companies. More than twice as many young men than women aged 16-24 can program, an essential skill for AI development, according to OECD data.

Women are also under-represented when it comes to the academic field, an essential component in research and development (R&D). In 2022, only one in four researchers publishing on AI worldwide was a woman.

Women-funded startups historically under-funded

“VC firms can (re)evaluate their recruitment and promotion practices to begin addressing gender disparities in VC funding for AI startups,” suggested Young.

“This might include ensuring equal opportunities for women and under-represented groups in leadership and decision-making partner roles, and looking outside of the ‘traditional’ recruiting pipelines,” she added.

The underfunding of women-led startups is not exclusive to the tech sector. For example, the European Commission and the European Investment Bank investigated why women entrepreneurs were missing out on funding.

Among the reasons, it was highlighted that there were unconscious biases that could lead investors to consider them less competent or less committed to their businesses, a lack of access to networks and mentors - and an underrepresentation of women in the most technical fields like deep tech, that secure the biggest fundings.

There are fewer female role models in venture capital and angel investing than male role models, which can also make it difficult for women entrepreneurs to break into the funding ecosystem and get their businesses off the ground, according to the OECD. 

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It was also noted that steps should be taken to encourage more women to study science, technology, engineering, and mathematics (STEM).

Finally, mentorship and networking programs - like Women in AI or Women in Tech - can also help to connect women entrepreneurs with investors and other key players in the startup ecosystem.

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