Generative artificial intelligence (GAI) has accelerated changes in the job market due to its unprecedented capacity to automate work and increase worker productivity (Kochhar, 2023; Butner et al., 2023; Di Battista et al., 2023b). Going forward, the professions that will be most significantly impacted by GAI are those most vulnerable to automation, including those that involve routine and repetitive procedures that don’t require a high degree of interpersonal communication, such as financial services, management analysts, statistical assistants, and digital communications personnel, (DeBattista, 2023 a; Ellingrud et al., 2023; Linkedin, 2023). For other careers, there is a high potential for job augmentation and increased productivity when individual employees partner with GAI, including jobs in IT, STEM fields, data management and analysis, and computer programming. (DeBattista, 2023 a). Those jobs that will be least affected are those that involve physical or personal interaction in non-language tasks, such as therapists, nurses, home health aides, clergy, and paralegal assistants (DeBattista, 2023 a).

These changes are already affecting the distribution of tasks associated with jobs, and the skills required of workers (Ellingrud et al., 2023; Linkedin, 2023; Di Battista, et al., 2023 a). Approximately 30% of hours worked today could be automated within the next 7 years (Ellingrud et al., 2023). Linkedin (2023) indicates that there is an accelerating trend to define jobs by collections of skills and tasks, rather than job titles. They further indicate that skill sets required for listed careers will change an average of 65% by 2030, with 55% of their members’ jobs likely to be disrupted or augmented by GAI (Linkedin, 2023). 

Educators must be mindful that when graduates enter the job market, employers will expect that they are prepared to engage with GAI technology. Since mediocre writing and ideas can easily be generated autonomously, those who get and keep the jobs of tomorrow will be those who are GAI literate (e.g. able to find the right GAI tool for the job, adept at crafting better prompts, able to use iterative queries, and with knowledge that allows recognition of biases and hallucinations), and who can demonstrate their skill at working with GAI tools to perform better than GAI or the individual could alone (Bowen and Watson,  2024). Those industries with the greatest demand for employees with GAI skills currently are Professional Services, Finance, and manufacturing (Linkedin, 2023).

Although faculty tend to agree that a college education isn’t simply job training, most students attend college with the hope of gaining knowledge, skills, and dispositions that will qualify them for a well-paying career. It is therefore no surprise that The Association of American Colleges and Universities routinely polls employers about what skills and dispositions they think are important to success in the workforce (Finley, 2021). Across years, most employers have quite a lot or a great deal of confidence in higher education, and nearly 90% view obtaining a college degree as either definitely or probably worth it (Finley, 2021), indicating that there is workplace value in the knowledge, skills, and dispositions taught in college. To maintain the value of college degrees, it is important that our students have skills to work with these new technologies in preparation for careers where they will be relevant (Bowen and Watson, 2024).

In the era of GAI, in addition to GAI and digital literacy, career prepared graduates should have well developed ability to work in teams and robust critical thinking skills (Finley, 2023), as well as the ability to formulate appropriate questions (Bowen and Watson, 2024). As the specific tasks performed in jobs change, workers will have to be flexible and acquire new skills. To ensure this, employers will value to employers dispositions including drive/work ethic, the ability to take initiative, self-confidence, persistence, self-awareness, and resilience (Finley, 2021; Bowen and Watson, 2024).

Reading & References #

Bowen J.A., and C. E. Watson. 2024 Teaching with AI. Johns Hopkins University Press, Baltimore.

Butner, K., T. Ivory, and W. Lobig. 2023. Seizing the AI and Automation Opportunity: The Moment Is Now. IBM Institute for Business Value.

Di Battista, A., S. Grayling, E. Hasselaar, T. Leopold, R. Li, M. Raynar, and S. Zahidi. 2023. Future of Jobs Report 2023, World Economic Forum, Cologny/Geneva, Switzerland. 

Di Battista, A., E. Hasselaar, A. Silva, S. Zahidi, T. Castagnino, N. D’Augustino, N. Decety, and H. Espinosa. 2023. Jobs of Tomorrow: Large Language Models and Jobs. White Paper, World Economic Forum & Accenture. 

Ellingrud, K., S. Sanghvi, G. Shingh Dandona, A. Madgavkar, M. Chui, O. White, and P. Hasebe. 2023. Generative AI and the Future of Work in America.  McKinsey & Company. 

Finley, A. 2021. How College Contributes to Workforce Success: Employer views on what matters Most. Association of American Colleges and Universities and Hanover Research. 

Linkedin, 2023. “Future of Work Report: AI at Work. LinkedIn.

Kochhar, Rakesh. 2023. “Which U.S. Workers Are More Exposed to AI on Their Jobs?” Pew Research Center’s Social & Demographic Trends Project, Pew Research Center.