The Philippines has developed one of the world’s most successful outsourcing industries over the past two decades, with multinational corporations establishing major operations in Manila and other cities to provide business process outsourcing services ranging from call centers to software development. The sector currently employs approximately 1.9 million people and generates $40 billion in annual revenues, accounting for roughly 10% of the country’s economy. However, experts warn that this industry faces disproportionate vulnerability to artificial intelligence automation.
According to the International Labour Organization, more than 12.7 million Filipinos—representing more than one in four workers—are employed in occupations exposed to generative AI, the highest proportion in Southeast Asia. The BBC interviewed several former outsourcing workers who reported being made redundant after their skills were used to train AI systems that ultimately replaced them. Industry leaders acknowledge that more than two-thirds of members of the IT and Business Process Association of the Philippines are running AI pilots, with some roles already automated. While company representatives argue that AI will primarily augment rather than replace workers, moving them to more complex tasks, critics note the companies face significant pressure from global clients to implement cost-cutting AI solutions.
The challenge is compounded by the Philippines’ non-unionized outsourcing workforce and employment laws that offer limited guidance on how companies should introduce AI or consult employees. The government has committed to upskilling more than 300,000 outsourcing workers and acknowledged that the Philippines may need to rethink its economic model. Officials suggest adapting existing labor and privacy laws through regulatory guidance rather than implementing sweeping new legislation, while emphasizing the importance of developing local AI companies capable of creating higher-value jobs. Observers caution that some companies may use AI as justification for layoffs driven by weaker demand, making it difficult to isolate the technology’s true impact on employment.
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