As artificial intelligence (AI) becomes more integrated into workplace systems and operations, it’s reshaping each how work tasks are accomplished and the very experience of labor itself.
For many employees, AI is stress-testing their tolerance for uncertainty and job insecurity. Some positions are being automated entirely. Others have gotten redundant. In many cases, full-time roles are being reduced to part-time or contract work.
These changes have been very visible on this 12 months’s news headlines. UPS, for instance, 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 chop 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 as much as 30 per cent of recent code on its projects.
Employees don’t stand on equal footing within the face of those changes, nor do they experience the identical level of vulnerability. The capability to reply to AI-related job threats varies sharply based on income, education, race and digital access.
These disparities ultimately shape who can adapt and leverage latest 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 support, retail, administration, warehousing and food service. Reports show these jobs are as much as 14 times more more likely to be displaced than higher-wage positions. Women are 1.5 times more likely than men to be pushed into latest occupations consequently.
People in these roles also face greater barriers in accessing employment and advancement opportunities, which perpetuates cycles of economic insecurity amongst groups which might be already vulnerable.
Some job positions are being automated entirely by artificial intelligence.
(Michael Fousert/Unsplash)
In contrast, AI is significantly boosting efficiency and productivity for knowledge staff in higher-wage positions. Surveys show 75 per cent of data staff now use AI tools and report a 66 per cent average increase in productivity.
These employees are much better positioned to integrate AI into their workflow. For example, national data shows that Canadian employees profit 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 amongst employees with graduate degrees and steadily declines as education levels drop. As a result, the advantages related to AI flow disproportionately to higher-educated, high-income skilled staff, enabling them to administer larger workloads and complete tasks faster. Some staff save as much as one-third of their work hours.
AI also can improve the standard of their work. Research shows consultants who use AI produce work that’s greater than 40 per cent higher in quality than those that don’t use AI. These benefits can speed up profession 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, skilled roles while deepening precarity for those in low-income, entry-level and front-line roles.
Uneven access to skills training
Upskilling and reskilling are sometimes presented as solutions to AI-related job threats, but access to those opportunities is unevenly distributed across social groups.
Upskilling refers to developing more advanced skills inside a current role, while reskilling involves learning entirely latest skills to transition into a distinct job. High-income, highly educated professionals receive way more institutional support to upskill or reskill, comparable to employer-funded training, paid time to learn latest tools and access to advanced digital tools.
Upskilling and reskilling are sometimes presented as solutions to AI-related job threats.
(Getty Images/Unsplash+)
In contrast, staff from lower socioeconomic backgrounds and low-income jobs often lack the financial means, time and organizational support needed to develop latest skills.
These structural gaps are reflected in participation rates: a survey by Gallup and Amazon shows that 75 per cent of staff in computer-related occupations engage in upskilling, compared with lower than one-third of staff in office administration, food service, production and transportation roles.
As a result, staff in precarious and vulnerable positions are further disadvantaged by the barriers they face in accessing opportunities to reply to technological threats.
Digital access shapes who advantages
Differences in digital access and literacy create one other 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 web, AI tools and access to digital skills training. They also develop AI literacy through formal education and job training, which provides 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 tougher 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 advantages of AI amongst 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 important if AI is to profit our society more broadly and equitably.
