By 2030, an estimated 92 million jobs will be displaced by AI, according to the World Economic Forum’s Future of Jobs Report 2025. This article explores how different communities will be impacted and displaced by AI. Research indicates that Black and Latino/Hispanic workers are more likely to experience AI-related job losses because these groups of workers are overrepresented in roles more likely to be replaced by automation and AI. Although AI has great potential, and the ability to close societal disparities, left unchecked, it may further exacerbate racial and economic inequalities in the workforce.

While 92 million jobs may be lost due to AI, the same report indicates that 170 million new jobs will be created because of AI, with the jobs expected to see the most growth including farmworkers, delivery drivers, construction workers, salespeople and food processing workers. The jobs most at risk include cashiers and ticket clerks, administrative assistants, caretakers, cleaners and housekeepers. According to a 2023 McKinsey report on the impact of generative AI on Black communities, Black Americans “are overrepresented in roles most likely to be taken over by automation.” Similarly, a study from the UCLA Latino Policy and Politics Institute indicates that Latino workers in California occupy jobs that are at greater risk of automation. Lower-wage workers are also at risk, with many of these jobs being especially vulnerable to automation.

Black, Latino and low-wage workers are not just overrepresented in jobs that will be lost to AI and automation—these groups are also underrepresented in AI and tech roles, which were projected to see the most growth in 2025, according to LinkedIn’s Jobs on the Rise list. The Black tech talent gap persists, according to a 2023 McKinsey report, which highlighted the lack of Black representation in the fastest-growing tech roles. A 2024 Axios article highlighted the lack of Latino representation in tech—a problem that starts as early as grade school. The lack of Black and Latino representation in tech can be attributed to several different factors: a lack of exposure to technical career options, a lack of resources for skill development and networking, a lack of access to mentorship opportunities, being overlooked or steered away from STEM fields due to bias, and feelings of imposter syndrome and inadequacy.

A lack of diversity in tech and AI can have deleterious impacts on the field. Issues like algorithmic bias, which is already pervasive in many hiring and recruitment tools, may be exacerbated by a lack of representation. A homogenous team creating tech tools may be less likely to recognize the need to create with different lived experiences in mind. For example, a lack of representation on a tech team could result in overlooking that a facial recognition system has a higher error rate for darker skin tones. A lack of diversity can lead to missing red flags during the creation of tech and AI systems which can lead to unintentional discrimination.