Gender bias is a deep-rooted societal problem that influences everything from education and employment opportunities to political representation.
But in a world increasingly driven by artificial intelligence systems, many may have expected modern technology to help level the playing field and overcome some of the biases that have long shaped human decision-making.
Unfortunately, the reality is a bit more complicated than that.
For instance, researchers who analysed 133 AI systems across different industries found that 44.2% demonstrated gender bias, while around 27.5% showed both gender and racial bias. The study was commissioned by the Berkeley Haas Center for Equity, Gender and Leadership.
This bias can potentially affect everything from credit card limits to job recruitment, online advertising, health research and image generation.
A famous example involves Jamie Hansson, the wife of tech entrepreneur David Hansson, who claimed in 2019 that her husband’s credit limit was 20 times higher than hers despite their finances being managed jointly.
“While AI itself isn’t biased, it’s a mirror. When trained on historical data, AI tools reflect the gender prejudices that already exist. It’s the classic rule of the supply chain: garbage in, garbage out. If left unchecked, AI won’t just mirror past inequities; it will amplify and accelerate them at scale,” warns SAPICS, a South African supply chain industry body.
The organisation highlighted this topic during a panel discussion at the recent 2026 SAPICS Conference, where leaders stressed the need to tackle AI gender bias not as an IT issue, but rather as a cultural and leadership priority.
Panellists at the conference said that many recruitment algorithms favour male candidates because they have been trained on decades of historical data that reflects and amplifies inequalities that already exist.
“While algorithms don’t create bias, their input shapes the output, and this issue could stem from the fact that only 22% of AI and data science professionals are women,” SAPICS said.
The rise of AI could also pose challenges for women entering the supply chain sector, as automation begins to reshape entry-level roles. Research from Gartner found that 55% of supply chain leaders expect advances in AI to reduce entry-level hiring in the coming years.
Because these positions often serve as the first step towards future leadership roles, a shrinking entry-level pipeline could limit opportunities for women to progress into senior positions.
“In a profession like supply chain management, which is being reshaped by AI at an extraordinary pace, the technology’s impact on gender equity is a threat that industry leaders cannot ignore,” SAPICS said.
“While AI is becoming integral to how modern supply chains operate – including in demand forecasting, inventory optimisation, warehouse automation and predictive analytics – it could also have a negative impact on how women enter and progress in the supply chain profession.”
Supply chain specialist Katrina Tyson said the true value of AI shouldn’t be headcount or cost reduction, but rather elevating and strengthening existing staff.
“When routine tasks are automated, leaders reclaim their most valuable asset: time to think, reflect and approach complex problems with creativity and nuance,” Tyson said.
“Used intentionally as a thought partner to augment our thinking rather than outsourcing it, AI strengthens existing leaders by pairing deeply human qualities like empathy, intuition and consensus with the scale, speed and power of technology.
“A good AI strategy doesn’t look to replace talent, but to give exceptional leaders the space to actually lead,” Tyson concluded.
However, while there are still great concerns about the impact that AI will have on industries, the 2026 SAPICS Women in Supply Chain Leadership Survey did show some encouraging shifts. For instance, the number of women witnessing discrimination fell from 62% in 2025 to 44% this year, while the percentage of women who experienced resistance when leading men fell from 59% to 48%.
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