More than one in four Philippine jobs are now exposed to generative artificial intelligence, putting the country at the top of ASEAN economies with comparable data—and placing women squarely in the line of disruption.
A new research brief from the International Labour Organization (ILO) estimates that about 12.7 million Filipino workers face some degree of exposure to GenAI as the technology reshapes tasks, workflows, and skill demands across industries.
While the headline number is striking, the ILO is careful to draw a line between exposure and extinction.
“Exposure does not mean jobs will disappear overnight. Most will not,” said Khalin Hassan, director of the ILO Country Office for the Philippines. “But many will change, sometimes quickly, sometimes painfully — demanding new skills, better protection, and deliberate policy choices.”
The pressure point is the country’s information technology–business process management (IT-BPM) sector, where AI adoption is accelerating even as broader uptake remains uneven due to infrastructure gaps and skills mismatches.
Using a global occupation-based index, the ILO found that only 3.6 percent of Philippine jobs fall into the highest-risk category where displacement is likely. The real impact, the study suggests, will come from task automation, job redesign, productivity gains, and shifts in job quality.
The disruption, however, is far from evenly shared. Women face twice the rate of GenAI exposure as men, particularly young and educated women clustered in clerical, administrative, and service roles.
In economic hubs such as Metro Manila, Central Luzon, and Calabarzon — where digital and business services dominate — women shoulder a disproportionate share of the risk.
“GenAI vulnerability is not gender neutral,” the ILO warned, cautioning that without targeted interventions, AI could deepen existing inequalities affecting women and youth.
To counter that risk, the ILO is urging tripartite action among government, employers, and workers. Priorities include investments in digital and AI skills, early STEM education, transition support for displaced workers, and financing for women-led innovation — reframing women and young people not just as AI-adaptive workers, but as architects of the technology’s future.
