Written by: Isabella Gentry
Over the past several years, artificial intelligence (AI) has changed the way people live—students use it to study, businesses use it to attract customers, and just about everyone relies on it for drafting emails and as their everyday search engine. More recently, we have seen the role of AI grow in the workplace, automating responsibilities that were previously held by employees and trained professionals. As many seem interested in predicting the future of the job market, there is growing controversy over whether AI will have disproportionate effects on white-collar or blue-collar workers. Understanding the future of artificial intelligence is critical when imagining what the job market and labor industry will look like many years from now. Furthermore, an unpredictable job market makes for an even harder-to-predict economy, given the central role jobs play in determining production, consumption, and overall economic welfare.
When examining the role of AI in different industries, it is first important to define white-collar vs. blue-collar jobs. White-collar workers normally require a formal education, with most jobs taking place in a professional setting, such as an office. In contrast, blue-collar workers typically perform unskilled manual labor in industries such as manufacturing or construction. Unlike white-collar workers, those working blue-collar jobs rely heavily on physical ability and strength. Many argue that a blue-collar worker’s ability to be successful and make a living depends largely on their being a hard worker (McClure, 2025). More specifically, the movement and the physical discipline of manufacturers and construction workers cannot be replicated with AI. While some may say that this alone would protect blue-collar workers from the takeover of artificial intelligence, the ability of machines to perform tasks is soon becoming possible through agentic AI.
Unlike typical large language models (LLMs), agentic systems extend the capabilities of simply generating information by applying this output towards completing specific tasks and goals (Stryker, 2025). Traditional forms of AI work reactively to concentrate data from the internet in response to a prompt, whereas agentic AI proactively to conquer goals. This technology allows for AI applications to not only think more like humans, but also do more like humans. Due to the unique abilities and powerful functions of agentic and physical AI (robots), the market for humanoid robots is expected to grow exponentially over the next decade, and potentially reach $38 billion by 2035 (The global market for humanoid robots could reach $38 billion by 2035, 2024). Soon, machines that previously required human supervision and operation will be capable of fulfilling tasks with minimal supervision, leaving many without employment. In the current status quo, fixed location blue-collar jobs, like manufacturers, are the most threatened (Stafford, 2025).
While workers in hands-on roles are not at immediate risk for job displacement due to large language models, as the industry for agentic and physical AI grows, the long-term risk becomes a concern. However, the greater concern lies in the fact that only about 42% of blue-collar workers have a college degree, making it harder for these workers to find suitable employment should they become displaced (Industry Inequalities, 2022).
As for white-collar workers, much of their typical workload is already being shifted onto automated systems that are enhanced and made more efficient with AI. This increased efficiency, without the cost of paying workers higher wages or hiring new talent, is likely to correlate with lower hiring rates. In fact, at the World Economic Forum annual meeting, Jamie Dimon, the CEO of JPMorgan Chase, said that he expects the leading US bank to hire fewer people over the next few years due to AI (Mullen, 2026). The positions that seem to be the most susceptible to be replaced by AI are those that require repetitive tasks, such as data analysis and financial reporting (Kelly, 2024). This is because these responsibilities are largely digital and text-based, meaning that the information is easily accessible to large language models (Kinder, 2024). While this does pose a large risk to those working in accounting or analytical roles, research indicates that there is significant value in learning how to use AI as a tool in the workplace rather than a replacement for human labor.
AI literacy—learning about how AI works and acknowledging its potential—is a critical skill that is necessary for maintaining a spot in the workforce as it becomes more prevalent across the job market. Understanding and being able to use AI productively is so crucial that “40% of employees will need to be reskilled by 2027 due to the introduction of AI” (Schulze, 2025). It is also likely that demonstrating proficient skills in AI may even become a requirement for many roles in the future. Employees who are reluctant to adapt to this changing landscape will be left behind, reiterating the importance of adaptability and willingness to learn new skills.
Additionally, it is important to consider the many jobs being created by AI. In particular, The McKinseyGlobal Institute predicts that the industry could create anywhere from 20 to 50 million new jobs worldwide by 2030 (Manyika, 2017). Although many jobs may be negatively impacted by the surge of AI, a whole new job market is being introduced for those proficient in AI integration, oversight, engineering, and other AI-related roles.
Given income inequality in the US, there is exacerbated tension over the projected effects of AI on blue-collar jobs as compared to white-collar jobs. Many have concerns that AI in the workplace will only widen the income gap, allowing highly educated workers to become more specialized in advanced technology, while manual workers will simply be replaced by machines and robots. While the unprecedented nature of artificial intelligence sparks these concerns, it is important to note that AI is transforming the economy through the goods and services we demand and produce, rather than solely destroying it (Frazier, 2026).
References
Frazier, K. (2026, January 27). AI Is Transforming the Economy—Not Destroying It. Cato Institute. https://www.cato.org/blog/ai-transforming-economy-not-destroying-it
Industry Inequalities | Porch. (2022). Porch.com. https://porch.com/resource/industry-inequalities
Kelly, J. (2024, February 28). What White-Collar Jobs Are Safe From AI—And Which Professions Are Most At Risk? Forbes. https://www.forbes.com/sites/jackkelly/2024/02/28/what-white-collar-jobs-are-safe-from-ai-and-which-professions-are-most-at-risk/
Kinder, M., Muro, M., Liu, S., & de Souza Briggs, X. (2024, October 10). Generative AI, the American worker, and the future of work. Brookings. https://www.brookings.edu/articles/generative-ai-the-american-worker-and-the-future-of-work/
Manyika, J. (2017, November 28). Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsey & Company. https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
McClure, S. (2025, July 2). Truth Beneath the Fiction. Medium. https://seanamcclure.medium.com/truth-beneath-the-fiction-e908a75125ae
Mullen, C. (2026, January 22). Dimon: AI’s effect on labor market “may go too fast for society.” Banking Dive. https://www.bankingdive.com/news/jpmorgan-dimon-ai-effect-jobs-workforce-davos/810247/
Schulze, S. (2019). AI Skills: What Employees Should Be Capable of in the Future. Masterplan.com. https://masterplan.com/en-blog/ai-skills
Stafford, A. (2025, May). The AI Robots Coming For Blue Collar Jobs. Forbes. https://www.forbes.com/sites/sap/2025/05/01/the-ai-robots-coming-for-blue-collar-jobs/
Stryker, C. (2025, February 24). Agentic AI. Ibm.com. https://www.ibm.com/think/topics/agentic-ai
The global market for humanoid robots could reach $38 billion by 2035. (2024). Goldmansachs.com. https://www.goldmansachs.com/insights/articles/the-global-market-for-robots-could-reach-38-billion-by-2035