Who Might Be Left Behind in AI Adoption
==The people and places most likely to be left behind are those that have the least access to the infrastructure, skills, firm capabilities, and local adaptation needed to use AI productively.== [:cite[1]{ln=1}][:c...
==The people and places most likely to be left behind are those that have the least access to the infrastructure, skills, firm capabilities, and local adaptation needed to use AI productively.== [:cite[1]{ln=1}][:cite[1]{ln=2}][:cite[3]{ln=1}][:cite[2]{ln=5}][:cite[2]{ln=6}] Lower income and many developing countries risk being left behind because AI adoption is lower there, and the report says the productivity benefits of AI are expected to be more than twice as large in advanced economies as in developing countries if current adoption patterns persist.[:cite[4]{ln=1}][:cite[4]{ln=2}][:cite[4]{ln=3}] Countries without reliable electricity, internet, and devices are at particular risk, because the report says firms and workers cannot use AI productively unless these basic conditions are in place.[:cite[3]{ln=1}][:cite[3]{ln=3}][:cite[5]{ln=3}] Countries with weak local language support and limited digital access may also fall behind, because lower income economies report more constraints related to citizens’ and frontline workers’ skills, connectivity, and limited AI support for local languages.[:cite[6]{ln=1}][:cite[6]{ln=2}][:cite[7]{ln=2}] Smaller, less capable, and less productive firms are more likely to miss out, because AI benefits have tended to go to firms that were already stronger, and firms lacking managerial practices or absorptive capacity often cannot use AI well.[:cite[8]{ln=2}][:cite[8]{ln=3}][:cite[9]{ln=1}][:cite[9]{ln=4}] Firms in weaker business environments may be left behind because the report says complementary factors such as infrastructure, skills, institutions, finance, and competitive markets shape whether AI leads to broader entrepreneurial success.[:cite[8]{ln=3}][:cite[10]{ln=4}][:cite[10]{ln=5}] Medium and large firms in developing countries that lag in sophisticated AI use face especially large gaps, with the report’s figure showing the biggest cross country differences in AI sophistication for those firms.[:cite[11]{ln=3}][:cite[11]{ln=4}][:cite[11]{ln=5}] Workers who are highly exposed to AI but lack the capacity to use it well are especially vulnerable, and the report estimates that this group accounts for about 43 million workers in low and middle income countries.[:cite[12]{ln=1}][:cite[12]{ln=2}] Workers with weaker transferable skills are more at risk of negative employment effects, because the report says AI’s greatest negative effects are likely to fall on workers with fewer skills that can transfer to other jobs and a weaker ability to adapt.[:cite[12]{ln=3}] Women may be left behind unless support is targeted to them, because the report says women tend to use AI less than men and are more exposed to job loss through AI.[:cite[9]{ln=6}][:cite[9]{ln=7}] People without foundational literacy and digital skills are also at risk, because access to AI does not automatically translate into productive use, and the report stresses that foundational learning gaps remain large and unequal.[:cite[2]{ln=5}][:cite[2]{ln=6}][:cite[13]{ln=8}][:cite[13]{ln=9}] More broadly, people who cannot access front end AI tools widely and fairly may be left behind because the report warns that, without complementary investments to guarantee broad access, AI adoption can perpetuate the digital divide and preexisting inequities.[:cite[14]{ln=4}][:cite[14]{ln=5}]