Many workers fear automation displacing their jobs. Yet new technology can also create new ones. The key is promoting policies which foster workforce development and facilitate career transitions between occupations.
Figure 6 indicates that since 1990, the proportion of workers employed in occupations with an increased predicted probability that machines may replace them has declined while automation-friendly occupations have seen their share rise.
How will it affect jobs?
Automation offers businesses an efficient solution for handling orders and projects more swiftly, freeing up employees to focus on more complex tasks and increasing overall job satisfaction.
Automating certain jobs may lead to job loss; however, new opportunities arise with automation as well. Therefore, policies must support responsible adoption of automation while mitigating any negative employment effects and providing training and upskilling programs for workers impacted by automation.
O*NET data suggest that occupations characterized by repetitive or structured work are more likely to be automated, while occupations with more flexibility tend to be less so. But correlations alone cannot explain changes in automation exposure over time – regional industries and labor markets often make transitioning from automation difficult, especially if other employers in her region are also automating.
What will it mean for the economy?
Though many fear the rise of robots, most publics around the world do not expect automation to spell an end to work. Most agree that while machines may replace human workers, they will also create new positions – with Japan, Poland and Hungary showing less optimism than average in this regard, particularly among older adults and those with less education.
Expert estimates of the likelihood that specific occupations will become automated vary considerably. Frey and Osborne  use textual descriptions of job tasks to classify jobs according to their likely automation, which has some correlation with actual exposure (as measured by O*NET).
However, most jobs involve multiple overlapping tasks that cannot easily be identified. Automation might not always replace humans; rather it could increase productivity while creating jobs in related sectors such as design and production of robots and AI.
How will it affect the financial sector?
While the media frequently reports on how automation will disrupt blue-collar jobs, white-collar office work could also be affected. According to Wells Fargo Research, 200,000 banking jobs could be replaced by automation over the next decade.
With data from O*NET, Frey and Osborne’s model of replaceability and our own analysis of whether tasks can be automated, we were able to classify occupations according to their exposure to automation. The upper right quadrant of the graph clearly demonstrates this trend – telephone operators, agricultural managers and administrative roles such as back-office administrative roles are highly vulnerable to automation.
Lower left quadrant shows that certain high-skilled jobs, such as lawyers, accountants and credit analysts are less at risk from automation due to requiring creativity and judgment when making decisions. Most people agree that increased automation will make finding jobs increasingly challenging in the future.
How will it affect consumers?
People fear automation will render their jobs obsolete and threaten their incomes, while others believe automation will create better employment opportunities.
Polled respondents from both advanced and emerging economies believe that in 50 years robots and computers will likely take over most of the work currently performed by humans. They anticipate automation having negative consequences for jobs; high proportions believe ordinary workers may struggle to find employment due to increased automation; furthermore they believe this may cause poverty or inequality due to job loss.
Even so, few of us know for certain whether automation will completely replace our current jobs. While many occupations will become more automated over time, most won’t be drastically affected as some might fear. Some examples include decision-heavy occupations like insurance underwriters and tax preparers where automation has a high rate of automation.