Exposure to generative AI is higher for highly skilled workers in large urban areas and women.
Around 26% of workers in countries that are part of the Organisation for Economic Co-operation and Development (OECD) are exposed to the impact of generative AI, although this proportion could reach 70% in the near future as this technology is integrated into the workplace.
Generative AI could have a "much broader impact on the labor market than previous technologies" that drove task automation, affecting a broader group of people and places, according to a report by the think tank for advanced economies released Thursday.
Thus, across the OECD, around a quarter of workers are exposed to generative AI (at least 20% of their work tasks could be performed at least 50% faster with the help of AI), although at the moment only 1% of workers are considered highly exposed (50% of their tasks could be performed at least 50% faster with generative AI).
However, as generative AI technologies become more integrated into the workplace, the OECD warns that up to 70% of workers could be exposed to this technology in the near future, with 39% of them highly exposed.
The report notes that exposure to AI will continue to grow as new software with generative AI technologies is developed or integrated, with the proportion of workers who could be highly exposed likely to range from 16% to over 70% across OECD regions.
Unlike previous automation technologies, generative AI excels at performing cognitive, non-routine tasks, which changes the exposure of the regional labor market, so the regions most exposed to generative AI are those that concentrate employment in sectors such as education, ICT or finance.
"Regions previously considered to be at comparatively low risk of automation are those most at risk of generative AI," the report notes, highlighting that while previous automation technologies primarily affected non-metropolitan and manufacturing regions, generative AI has the potential to disrupt a significantly larger share of jobs in metropolitan regions and cities.
On average, it estimates that 32% of workers in urban areas are exposed to generative AI, compared to 21% in non-urban regions. Moreover, this gap can exceed 17 percentage points in countries such as Colombia, Greece and Romania.
It also finds a similar reversal when analysing worker exposure by gender and educational level, as exposure to generative AI is higher for highly skilled workers and women, whereas previous technologies mainly affected low-skilled workers and men.
The OECD analysis notes that job exposure to AI varies significantly across OECD regions, with the expected share of workers highly exposed to generative AI in the near future ranging from 16% in Guerrero, Mexico, to 77% in Greater London, UK, with the dispersion within countries averaging about 14 percentage points, indicating that the top region of a country is 1.6 times more exposed to generative AI than the bottom region.
Industrial composition is believed to be the main driver of differences in exposure to generative AI in local labor markets.
Thus, in the EU, only 5% of agricultural workers are considered exposed to generative AI compared to 71% of information and communications workers, with 5% of these already highly exposed, although this figure could reach almost 90% in the future, as the proportion of highly exposed workers in the financial and insurance sector in the future could be almost 97%.
According to the OECD, almost half of all sectors could see the majority of their workers highly exposed to generative AI, and in eight of the eighteen sectors analysed in the EU, more than 50% of employment could be highly exposed in the near future.
In this regard, in the real estate, information and communication, professional and scientific activities, and financial and insurance services sectors, the proportion of exposed workers could exceed 80%, while only a few sectors, such as construction, accommodation and agriculture, do not seem to face significant changes due to generative AI.
"In all three sectors, less than a quarter of workers could be highly exposed to AI in the future," the report's authors note, noting that the common factor is the more limited use of information technology (IT). In fact, the agricultural sector is expected to have only 7% of its workers highly exposed to generative AI.
On the other hand, the study finds that, in the countries of the European Union, workers in cities are significantly more exposed than in other places.
Specifically, in the EU, more than 36% of jobs in cities are exposed to generative AI, while in rural areas, it is only 21%.
In some countries, such as Poland, Hungary or Greece, the proportion of employment exposed to generative AI is at least twice as high in cities compared to rural areas.
In any case, he warns that the gap between rural areas and cities in terms of exposure to AI varies significantly by country and, in the near future, could vary from just under 8% in Belgium to close to 35% in Romania, with Luxembourg being the only country in which rural areas are more exposed than cities.
"While the exact effects of generative AI on the geography of job creation and displacement remain to be seen, there is little evidence that technology-driven automation leads to mass job destruction," the report says, noting that instead, automation processes led to regional productivity growth.
In this regard, it is recalled that, in the last decade, a small but significant number of OECD regions have experienced a displacement of jobs due to automation, although this displacement of jobs was outweighed by the creation of new jobs.
However, he acknowledges that "there is no guarantee that these new jobs have gone to workers who lost their jobs" and that they could instead have been filled by new workers entering the workforce.
On the other hand, it points out that AI technologies could offer OECD regions a strategic tool to address economic and labour market challenges, such as labour shortages, stagnant productivity or workforce inclusion.
The OECD also points to risks for workers related to the impact of AI on the quality of work, concerns about privacy and possible biases in AI systems, noting that collaboration with social partners and the establishment of clear and transparent guidelines for the use of AI will be important to protect workers' rights.
