AI promises efficiency, but it’s also amplifying labour i...

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As AI reshapes workplaces, its benefits and risks are falling unevenly across the labour market, widening existing socioeconomic divides. (Getty Images/Unsplash+) AI promises efficiency, but it’s also amplifying labour inequality Published: December 3, 2025 5.14pm GMT Mehnaz Rafi, University of Calgary

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Mehnaz Rafi
PhD Candidate, Haskayne School of Business, University of Calgary

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Mehnaz Rafi does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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https://doi.org/10.64628/AAM.5gsm9dvqh

https://theconversation.com/ai-promises-efficiency-but-its-also-amplifying-labour-inequality-258772 https://theconversation.com/ai-promises-efficiency-but-its-also-amplifying-labour-inequality-258772 Link copied Share article

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As artificial intelligence (AI) becomes more integrated into workplace systems and operations, it’s reshaping both how work tasks are completed and the very experience of work itself.

For many employees, AI is stress-testing their tolerance for uncertainty and job insecurity. Some positions are being automated entirely. Others are becoming redundant. In many cases, full-time roles are being reduced to part-time or contract work.

These changes have been very visible in this year’s news headlines. UPS, for example, announced 20,000 layoffs in April while expressing interest in deploying humanoid robots from Figure AI to take over warehouse tasks.

Recently, this disruption has moved beyond front-line roles. Amazon has revealed plans to cut 14,000 corporate jobs to reorganize around AI-enhanced efficiency. Microsoft laid off roughly 6,000 employees — most of them software engineers and programmers — as AI systems now generate up to 30 per cent of new code on its projects.

Employees do not stand on equal footing in the face of these changes, nor do they experience the same level of vulnerability. The capacity to respond to AI-related job threats varies sharply based on income, education, race and digital access.

These disparities ultimately shape who can adapt and leverage new technological opportunities, and who becomes excluded from them and left behind.

AI’s uneven impact on the workforce

Employees face unequal vulnerability to AI-related job threats largely because automation disproportionately targets entry-level and front-line positions. These are typically lower-wage roles, often held by people from lower socioeconomic backgrounds and marginalized communities.

Such positions typically involve routine or repetitive tasks in sectors like customer service, retail, administration, warehousing and food service. Reports show these jobs are up to 14 times more likely to be displaced than higher-wage positions. Women are 1.5 times more likely than men to be pushed into new occupations as a result.

People in these roles also face greater barriers in accessing employment and advancement opportunities, which perpetuates cycles of economic insecurity among groups that are already vulnerable.

A tech demonstration showing bartending robots pouring drinks

Some job positions are being automated entirely by artificial intelligence. (Michael Fousert/Unsplash)

In contrast, AI is significantly boosting efficiency and productivity for knowledge workers in higher-wage positions. Surveys show 75 per cent of knowledge workers now use AI tools and report a 66 per cent average increase in productivity.

These employees are far better positioned to integrate AI into their workflow. For example, national data shows that Canadian employees benefit most from AI when their jobs involve “complementary” tasks. These are tasks that AI can augment or enhance.

This complementarity is strongly tied to education. It is highest among employees with graduate degrees and steadily declines as education levels drop. As a result, the benefits associated with AI flow disproportionately to higher-educated, high-income professional workers, enabling them to manage larger workloads and complete tasks faster. Some workers save up to one-third of their work hours.

AI can also improve the quality of their work. Research shows consultants who use AI produce work that is more than 40 per cent higher in quality than those who don’t use AI. These advantages can accelerate career progression and income growth for people already in privileged socioeconomic positions.

These patterns reinforce existing class inequities by expanding opportunities for those in high-income, professional roles while deepening precarity for those in low-income, entry-level and front-line roles.

Uneven access to skills training

Upskilling and reskilling are often presented as solutions to AI-related job threats, but access to these opportunities is unevenly distributed across social groups.

Upskilling refers to developing more advanced skills within a current role, while reskilling involves learning entirely new skills to transition into a different job. High-income, highly educated professionals receive far more institutional support to upskill or reskill, such as employer-funded training, paid time to learn new tools and access to advanced digital tools.

Upskilling and reskilling are often presented as solutions to AI-related job threats. (Getty Images/Unsplash+)

In contrast, workers from lower socioeconomic backgrounds and low-income jobs often lack the financial means, time and organizational support needed to develop new skills.

These structural gaps are reflected in participation rates: a survey by Gallup and Amazon shows that 75 per cent of workers in computer-related occupations engage in upskilling, compared with less than one-third of workers in office administration, food service, production and transportation roles.

As a result, workers in precarious and vulnerable positions are further disadvantaged by the barriers they face in accessing opportunities to respond to technological threats.

Digital access shapes who benefits

Differences in digital access and literacy create another layer of inequality in how different groups experience AI.

The digital divide is tied to disparities in digital and AI literacy across income, geography, age, education and occupation.

People in high-income, white-collar roles, urban areas and well-resourced institutions typically have reliable internet, AI tools and access to digital skills training. They also develop AI literacy through formal education and job training, which gives them more opportunities to experiment with AI and integrate it into their work.

However, those in manual jobs, rural areas, low-income households, marginalized communities and older age groups often lack stable connectivity, updated technology and access to formal training, making AI adoption more difficult for them.

This leaves them more vulnerable to AI-related job threats. These gaps in access and skills reinforce existing socioeconomic inequalities by concentrating the benefits of AI among advantaged groups while heightening the risks for those with fewer resources.

AI holds great potential to positively impact employees, organizations and the workplace. However, without equitable access to upskilling, reskilling, training, digital resources and AI literacy, the technology can deepen the disparities between different social groups. Closing these gaps and creating fair opportunities for adaptation is essential if AI is to benefit our society more broadly and equitably.

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