SPEAKING in Bangkok on October 14, IMF Managing Director Kristalina Georgieva warned that the rapid advance of AI could widen the gap between advanced and developing economies, particularly as development assistance declines. While AI-related investment is supporting economic growth and creating opportunities, she stressed the need to prepare for its disruptive effects on jobs and public finances, so that countries already lagging behind do not fall further behind.
Artificial intelligence is no longer merely a technological experiment. It is influencing international trade, investment decisions, business operations and the skills employers demand. Companies are using AI to process information, improve customer service, automate routine tasks and support decision-making. Governments and educational institutions are also exploring ways to use it to improve service delivery and learning.
Yet the benefits are unevenly distributed. Countries that manufacture advanced chips, develop sophisticated AI systems or attract large technology investments may gain directly from the current boom. Other countries may benefit primarily by adopting these technologies to improve productivity in their existing industries.
The World Bank’s October 6, 2026, East Asia and Pacific Economic Update, titled Riding the AI Wave, examines this distinction. East Asia is benefiting from the expansion of AI-related investment and exports, but the larger development challenge is to ensure that technological advances improve productivity across the wider economy and create better employment opportunities.
The IMF’s discussions at the Bangkok meetings add a global perspective. AI-related investment is supporting activity in parts of the world economy, while technological disruption, concentrated supply chains and the possibility of a correction in investment create risks. For developing countries, the objective should be to participate in the benefits of AI without becoming excessively dependent on a narrow set of industries or investment trends.
The central development question is therefore not simply how quickly countries adopt AI. It is whether they can convert technological progress into sustained productivity growth, better jobs and higher household incomes.
Why the Philippines has much at stake
The Philippines has a particular interest in how AI changes service-sector employment. Its business-process outsourcing industry, customer-service operations, shared-services centers and digitally delivered professional services have generated employment, export earnings and opportunities for graduates.
These industries need not be victims of technological change. AI can help companies handle routine tasks more efficiently, improve the quality of services and move into more sophisticated activities. Filipino workers who combine technical knowledge with communication, problem-solving, professional judgment and cultural understanding may find opportunities in higher-value roles.
However, the transition carries real risks. AI systems can increasingly perform some routine customer-support functions, transcription, basic accounting, document processing and standardized administrative tasks. If companies can automate these activities, demand for certain occupations may weaken or the number of workers needed for particular tasks may decline.
Young graduates could be especially vulnerable if the routine work through which they traditionally acquire experience becomes automated. The challenge is not only whether existing jobs disappear, but whether new entrants can find the first rung on the employment ladder.
This does not mean that the BPO industry is destined to collapse. AI can complement human workers as well as substitute for specific tasks. Businesses may expand into new services, and new occupations may emerge. The overall employment outcome will depend on the pace of adoption, the creation of new activities, workers’ ability to acquire relevant skills and the willingness of companies to invest in their workforce.
For the Philippines, the priority should be to help the industry move towards higher-value services while preparing workers for the occupations that are likely to expand.
Small AI, big development opportunities
One of the most relevant messages from the World Bank’s regional assessment is that developing countries do not necessarily need to build expensive frontier AI systems to benefit from the technology. Adopting and adapting affordable existing tools may offer a more practical starting point. The report’s emphasis on accessible applications makes AI relevant to countries whose immediate priority is improving productivity across established industries.
For the Philippines, the possibilities extend well beyond outsourcing.
Agriculture remains important to rural employment and household incomes. AI-enabled applications could help farmers interpret weather information, identify crop diseases, plan planting schedules and assess market conditions. Their usefulness, however, would depend on reliable local data, language accessibility, connectivity and the ability of farmers to act on the information provided.
Tourism operators could use AI to improve digital marketing, manage bookings and communicate with visitors in different languages. Small retailers could use it to monitor inventories, forecast demand, organize accounts and respond to customers. Logistics companies could improve delivery planning, while manufacturers could use AI-assisted systems to reduce waste and improve quality.
Healthcare and education offer further opportunities. Carefully supervised AI applications could assist with administrative work, provide educational support and help professionals process information. They should complement qualified teachers and healthcare workers, not replace professional judgment or remove accountability for consequential decisions.
These examples illustrate an important point: the economic value of AI does not depend exclusively on developing new technology. It can also arise from using existing technology to solve practical problems more efficiently.
Nevertheless, adoption is not automatic. Small and medium-sized enterprises may lack the money, technical expertise or confidence to introduce AI. Large companies are better placed to finance new systems and hire specialists, potentially widening the productivity gap between large and small businesses.
Affordable digital tools, accessible training, technical support and suitable financing could help smaller enterprises participate. Otherwise, AI may strengthen the competitiveness of established firms while leaving many local businesses behind.
Skills and education must keep pace
The success of AI adoption will depend heavily on the quality of the workforce. Technology cannot compensate for weak foundational education, inadequate infrastructure or a shortage of workers capable of interpreting information and applying it intelligently.
Schools and universities should therefore strengthen reading, writing, mathematics, critical thinking and problem-solving while integrating appropriate digital and AI literacy into their curricula. Students must learn not only how to use AI tools, but also how to verify their outputs, recognize errors, protect personal information and exercise independent judgment.
Technical-vocational institutions can play an equally important role. Short, practical courses designed with employers could help workers acquire skills relevant to changing occupations. Training should be accessible to people already in employment, including those who cannot afford to leave their jobs or pay substantial fees.
Employers also have a responsibility. If AI improves productivity, companies should consider how to retrain existing staff, redesign jobs and create pathways into higher-value work. Productivity gains should not be measured exclusively through lower labor costs. Higher-value services, improved quality and a more skilled workforce can strengthen long-term competitiveness.
The government, educational institutions and industry should also monitor changes in employment demand. Better information on occupations, vacancies, wages and emerging skill requirements would help policymakers identify where training is most urgently needed.
The digital divide could become an economic divide
Access to technology is another fundamental concern. AI applications may be inexpensive in isolation, but effective use requires dependable electricity, internet connectivity, appropriate devices and the ability to understand and apply the results.
Businesses and households with these advantages may benefit faster than those without them. Differences in digital access could therefore reinforce existing disparities between urban and rural communities, larger and smaller enterprises, and highly educated and less-skilled workers.
The Philippines needs to treat digital infrastructure as an essential component of development policy. Affordable connectivity, reliable power and accessible digital services can help broaden the reach of AI. Local-language applications and user-friendly tools are particularly important for people who cannot readily use English-language or technically demanding systems.
Public agencies could support the transition by helping smaller firms understand practical AI applications, encouraging responsible experimentation and making training opportunities available beyond major urban centers.
The objective should be to prevent the digital divide from becoming a deeper divide in productivity, earnings and economic opportunity.
Public policy, taxation and responsible AI
Governments can benefit from AI themselves. Philippine public agencies could use carefully tested applications to improve document processing, agricultural extension, public information and selected administrative services. Such uses could reduce delays and allow public employees to devote more time to tasks requiring human judgment.
However, efficiency must not come at the expense of accountability. Data privacy, cybersecurity, transparency, protection against discrimination and clear responsibility for errors must be integral to public-sector adoption. Decisions affecting access to essential services should retain appropriate human oversight and avenues for review.
The fiscal implications also deserve attention. If AI changes the balance between labor income and profits, the composition of tax revenues may change. The IMF’s discussions of taxation and the AI economy highlight the need for governments to consider how tax systems should adapt as production methods and employment structures evolve.
For the Philippines, this does not mean penalizing technological investment. It means maintaining a fair and effective tax system while encouraging innovation and preserving the revenue needed for education, infrastructure, retraining and social protection.
Workers facing displacement may need temporary income assistance, career counseling and support in moving into new occupations. Such measures should be designed to help people return to productive employment, rather than merely compensate them for economic change.
What the Philippines can learn from ASEAN
The regional dimension is important because ASEAN economies are approaching AI from different starting points.
Singapore has advanced technological capabilities and substantial institutional resources. Malaysia has been investing in digital infrastructure and technology-related activities. Vietnam has expanded its role in manufacturing and technology supply chains. The Philippines brings a different combination of strengths, including its service-sector workforce, English-language capabilities and established outsourcing industry.
The purpose of comparison should not be to copy another country’s model. It should be to identify practical lessons that fit Philippine conditions.
ASEAN cooperation could help countries share experience in workforce training, responsible AI standards, cybersecurity and digital infrastructure. Regional collaboration could also make it easier for smaller businesses to access technical expertise and participate in cross-border digital services.
The Philippines should seek to strengthen its existing comparative advantages while broadening the range of industries that can benefit from technology. That means combining service-sector upgrading with practical applications in agriculture, tourism, manufacturing, logistics and public services.
Making AI work for people
The World Bank–IMF discussions in Bangkok provide a timely reminder that technological progress does not automatically produce inclusive development. AI can improve productivity, stimulate investment and create new economic opportunities. It can also disrupt occupations, widen disparities between workers and businesses, and expose economies to concentrated investment and supply-chain risks.
For the Philippines, the central policy test is whether the country can move from adopting technology to building productive capabilities. This requires investment in people, reliable infrastructure, competitive small businesses, responsible regulation and support for workers navigating change.
The government cannot determine every future occupation, nor can education policy anticipate every technological development. But it can create the conditions that help workers adapt, firms innovate and the benefits of higher productivity spread more widely.
Ultimately, the success of the AI revolution should not be measured simply by the number of companies using AI or the speed at which new systems are introduced. It should be measured by whether Filipino workers become more productive, businesses become more competitive, public services improve and households experience higher incomes and better opportunities.
AI offers the Philippines a significant development opportunity. Turning that opportunity into broad-based prosperity will depend not on technology alone, but on the quality of the policies, institutions and investments that guide its use.