Technology is neither good nor bad; nor is it neutral.Kranzberg’s First Law of Technology
The release of generative artificial intelligence products such as ChatGPT, Bing Chat, Bard, Midjourney and others – which allow anyone to use prompts to generate text, images, music or video for business or personal use – have democratized AI. By doing so, generative AI has become a game changer for many industries, offering new ways to automate tasks, increase productivity and improve quality.
While this technology will create new job opportunities and a growth in GDP, the exposure of generative AI to automate tasks in existing jobs will have an impact on those occupations as well. These include changes in job tasks and professional roles, the need to learn new skills to remain competitive and, unfortunately, the loss of jobs.
It may also mean, however, that workers will be freed up to be more efficient and creative, thus increasing both productivity and quality. New jobs will be created as well, and workers may find more meaning in their work if AI allows tasks that are time-consuming to be automated. Therefore, “impact” should not be thought of strictly as a negative, since there will also be positive changes in these job categories.
This analysis aims to analyze whether the potential impact of generative AI on jobs will impact men and women differently.
The main finding of this analysis is that eight out of 10 women (58.87 million) in the U.S. workforce are in occupations highly exposed to generative AI automation (more than 25% of the occupational tasks) vs. six out of 10 men (48.62 million). Overall, 21% more women are exposed to AI automation than men even though men outnumber women in the workforce. This is due to the affected occupations being populated by more women than men. “Highly exposed” means 25%-50% of the tasks in that occupation could be automated by generative AI.
This finding was determined using Goldman Sachs’ “The Potentially Large Effects of Artificial Intelligence on Economic Growth” as a base. The report identified 15 occupations that would be most affected. Within those occupations, the total number of employees and the gender breakdown determined the total number of men and women exposed to generative AI automation.
The Goldman Sachs report had the following key takeaways:
More specifically, the Goldman Sachs report projected that the following 15 occupations would be the most affected, with 25%-50% of the tasks in those occupations potentially exposed to automation via generative AI (see Figure 1). As you can see, these are primarily knowledge worker positions. Generative AI will have much less impact on jobs that require physical labor as, at this point in time, it lacks ability to perform that type of work.
|Office and Administrative Support||46%|
|Architecture and Engineering||37%|
|Life, Physical, and Social Science||36%|
|Business and Financial Operations||35%|
|Community and Social Service||33%|
|Sales and Related||31%|
|Computer and Mathematical||29%|
|Farming, Fishing, and Forestry||28%|
|Healthcare Practitioners and Technical||28%|
|Educational Instruction and Library||27%|
|Arts, Design, Entertainment, Sports, and Media||26%|
Using the Goldman Sachs list of the top 15 job categories impacted by generative AI (above), we then analyzed the gender breakdown for these occupations based on the U.S. Occupational Employment and Wage Statistics Report. These data come from the Bureau of Labor and Statistics, the source used in the Goldman Sachs report to determine the employment share of each occupation. The gender breakdown of the total of all the top 15 occupations were then calculated to determine the impact of generative AI by gender.
Figure 1 below shows the female-to-male percentages for the 15 occupations, ranked in order of number of employees in each occupation, largest to smallest. By looking at the total at the bottom of the chart, one can see there are significantly more women in these occupations (58.87M) than men (48.62M) even though there are more men (84.21M) in the workforce than women (74.08M). Thus almost 80% of women in the workforce are in occupations exposed to automation via generative AI vs. 58% of men.
Gender breakdown of jobs most heavily impacted by AI
|Office and administrative support occupations||16.10M||71.9%||28.1%|
|Sales and related occupations||14.32M||49.4%||50.6%|
|Healthcare practitioners and technical occupations||9.81M||75.7%||24.3%|
|Education, training, and library occupations||9.22M||73.3%||26.7%|
|Business and financial operations occupations||9.15M||54.5%||45.5%|
|Computer and mathematical occupations||6.17M||26.7%||73.3%|
|Healthcare support occupations||4.93M||84.6%||15.4%|
|Architecture and engineering occupations||3.46M||16.1%||83.9%|
|Arts, design, entertainment, sports, and media occupations||3.44M||48.8%||51.2%|
|Protective service occupations||3.06M||23.2%||76.8%|
|Community and social services||2.95M||67.2%||32.8%|
|Life, physical, and social science occupations||1.84M||48.2%||51.8%|
|Farming, fishing, and forestry occupations||.98M||26.2%||73.8%|
|Total of all jobs||158.29M||74.08M||84.21M|
|Total of jobs impacted / total jobs||68%||79%||58%|
The reason more women than men are exposed to AI automation is straightforward: A higher percentage of working women are in white-collar jobs (~70%) vs. blue-collar ones (~30%) while for men the ratio is roughly 50/50.
As discussed earlier, “impacted by generative AI” may mean positive or negative changes for society and workers. For society, it may bring economic growth as well as societal disruption. Whether the changes are good or ill for individual workers will depend on their occupation, firm, individual capabilities and ability to adapt. Some will adjust better than others. There will be winners and losers.
For every knowledge worker, there are some skills and attitudes that will enable them to adapt and thrive in the coming AI era. The first is a need to gain generative AI capabilities. As the saying goes: “You won’t be replaced by AI. You will be replaced by someone who knows AI.” Cognitive workers need to become familiar and then fluent in using generative AI tools and applying them in their current jobs to become more productive, knowledgeable and creative. They should also remain well informed about AI trends and how these tools are being used in their professions, industries and firms so they can find additional means of improving their value to their organizations.
Also, as New York Times columnist David Brooks put it, “In the age of AI, major in being human.” There are things humans can do that AI cannot do well or at all. These include taking the initiative, discovering problems, influencing others, developing creative solutions and navigating organizational politics – all things that are crucial to getting things done in organizations.
Lastly, resiliency and adaptability will be crucial. AI will move ever faster and disrupt both the workplace and society. Being able to cope with and respond positively to those changes will set one apart from the rest.
What should society do if the impact of AI in the workplace falls more on women than men is a question we must grapple with as we see the changes it brings. As discussed, the results will be a mix of positives and negatives, and at this point, it is difficult to say what the balance of those will be. While that may not be a satisfactory answer, we will have to adjust as the effects of generative AI develop.
Data for this report were compiled by Paige Smith, UNC Kenan-Flagler Business School MBA candidate.