Automation exists to substitute work undertaken by humans with work done by machines, with the aim of increasing the quality and quantity of output at a reduced cost.
How do humans and automation interact?
If a machine can do a task currently done by humans, it will do it with greater precision, speed, and at a lower cost—but there are limitations to such substitution.
A job is a collection of tasks, and even under the most aggressive scenarios, it is unlikely that machines will substitute for all tasks in any one occupation.
Workplace activity that isn’t taken over by automation is complemented by it—making the remaining human tasks more valuable.
Automation-driven cost and quality improvements can increase demand to a degree that offsets any would-be job losses.
When machines handle routine, time-consuming activities, human capacity is freed-up to create new products and new tasks.
There are many reasons why technological adoption falls short of potential, so it is a mistake to equate technological potential with likely projected outcomes.
Workers who supply tasks that are substituted by machines are more likely to benefit from automation than are workers who supply tasks that machines can complete.
Wage gains for the remaining tasks completed by humans will be larger when the barriers to entry (e.g. education, training, certification) are higher.
Automation drives cost and quality improvements for products, as well as productivity and wealth increases for workers, which can mitigate some labor displacement.
The report’s predictions assess the susceptibility of different jobs, places, and demographic groups to disruption by workplace automation and AI. Data produced by McKinsey Global Institute are employed to estimate the percentage of tasks in a given occupation that are potentially automatable given currently available technologies.
Almost no occupation will be unaffected by technological change in the AI era. Some of the most vulnerable jobs are those in office administration, production, transportation, and food preparation. Such jobs are deemed to face “high risk” with over 70 percent of their tasks potentially automatable. All of these either involve routine, physical labor or information collection and processing activities.
“High risk” jobs represent only one-quarter of all jobs, however. The remaining, more secure jobs include a broader array of occupations ranging from professional and technical roles with high educational requirements to low-paying personal care and domestic service work characterized by non-routine or abstract activities and social and emotional intelligence.
Automation will take place everywhere, but its inroads will be felt differently across places, varying with local industry, task, and skill mix. Overall, smaller, more rural communities seem significantly more exposed to the automation of current-task content than larger ones. This relationship holds when comparing metropolitan to rural areas as well as among metros of different sizes. Among the country’s 100 largest metros, workers’ education attainment will prove to be decisive.
The sharp segmentation of the labor market by educational attainment, gender, age, and racial-ethnic identity ensures that some demographic groups are likely to bear more of the burden of adjusting to the AI era than will others. The probable divides are clear: Men, youth, and less educated workers, along with underrepresented groups all appear likely to face significantly more acute challenges from automation in the coming years. Young workers and Hispanics will be especially exposed.
Federal, state, local, and civic leaders need to initiate sustained efforts to ensure the labor market works tolerably for people in the AI era of automation.
Five major agendas require attention to mitigate coming stresses as the nation moves into the AI period of automation.
Ian Hathaway provided significant contributions to the production of this report.