## Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity

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### Executive summary — exposure and complementarity
- Occupation classification framework:
  - Based on Cazzaniga et al. (2024), Felten et al. (2021), and Pizzinelli et al. (2023); combines an AI exposure index and an AI complementarity score to classify occupations into: high exposure/high complementarity; high exposure/low complementarity; and low exposure.
  - Linked to Philippine Statistics Authority October 2022 Labor Force Survey microdata (183,602 observations of 52 variables; over 180,000 observations, 80,000 of which are tagged as “employed”).
- Key exposure and complementarity findings:
  - Around one third of occupations in the Philippines are highly exposed to AI.
  - Of highly exposed occupations, 61% are also rated as highly complementary.
  - 14% of the total workforce are in low complementarity jobs that are more susceptible to displacement by AI.
  - Overall labor-market exposure metrics:
    - 14 percent of jobs are classified to be at risk of displacement by AI.
    - 22 percent of jobs are likely to see the nature of their work change significantly as AI is rolled out.

### Demographic, sectoral, and BPO-specific findings
- Demographic and earnings patterns:
  - Workers most exposed to AI: college-educated, young, urban, female, and well-paid service-sector employees.
  - These characteristics also correlate with higher complementarity.
- Philippine labor market context and key statistics:
  - Services sector share of GDP in 2023: 62.3 percent of total Gross Domestic Product (GDP).
  - Services sector employment (April 2024): 61.4 percent of employment (PSA labor force survey).
  - Labor force participation by gender:
    - 75% of working age men are either working or looking for work.
    - 53% of working age women are either working or looking for work.
  - Unemployment and underemployment (as of April 2024):
    - Unemployment rate: 4.0%.
    - Underemployment: 10-15% of employed workers are looking for additional work or wanting longer hours.
  - Educational attainment:
    - Most working Filipinos’ highest educational degree is the (junior) high school diploma.
    - Just over a quarter hold a college degree.
  - Wage evolution (index labeling): Index, 2009=100; Average Daily Basic Pay; NCR Minimum Wage; Real Average Daily Basic Pay; Real NCR Minimum Wage.
- BPO sector scale and exposure:
  - BPO employees:
    - BPO employees make up about 3% of the total workforce (Executive Summary).
    - BPO employs 1.7 million Filipinos, equivalent to 3.4 percent of the total labor force as of 2023 (B section).
  - BPO revenues and macro significance:
    - BPO sector revenues accounted for 7.4% of GDP in 2023 (Executive Summary; noted as similar in magnitude to remittances).
    - B section reports BPO sector generated US$35.5 billion in revenues, an increase of 9 percent over the previous year, and states BPO revenues were equivalent to 8.1 percent of the country's total GDP (2023 figures).
  - Global market share and composition:
    - Philippines holds an estimated 15 percent of the global outsourcing market.
    - Presence of 788 BPO companies (reported by the Philippine Economic Zone Authority).
    - Majority of revenues generated by contact centers and back-office support services.
    - Market geography: North America 70 percent, Europe 15 percent, Asia-Pacific Region 15 percent.

### Infrastructure, skills, and adoption constraints
- Digital and physical infrastructure gaps:
  - Electricity and data-center intensity example: an AI chatbot handling 195 million queries needs data centers consuming power equivalent to 23,000 U.S. households.
  - Electricity access/reliability: about two million households still lack electricity; power interruptions remain common (PIDS, 2023).
  - Internet performance and affordability:
    - 2023 Worldwide Broadband Speed League: Philippines ranked 86th out of 220 countries with an average download speed of 43.36mbps, compared with the Asian average of 45.72mbps.
    - World Data Lab estimate: nearly 19 million Filipinos or 16.6 percent of the population cannot afford a minimum package of internet.
- Skills and human capital shortfalls:
  - Future of Jobs projection (WEF, 2023): 23 percent of the workforce will change within five years, with 60 percent needing training by 2027 centered on creative and analytical thinking, AI, and big data.
  - Despite high internet penetration, 90 percent of Filipinos lack basic ICT skills.
  - Philippines lags in international education assessments in mathematics, reading, science, and creative thinking.
  - Barriers to training: inadequate internet access, lack of time, high training costs, limited opportunities.
  - Industry projection: IBPAP expects the Philippine tech industry to generate 1.1 million new jobs by 2028.
- Adoption readiness and R&D spending:
  - Cisco survey of Philippine firms on AI readiness:
    - 17 percent are ready to deploy and use AI in business processes.
    - 44 percent are moderately ready.
    - 35 percent indicated minimal readiness.
    - 4 percent are not prepared to use AI.
  - R&D spending:
    - Philippines spending: less than 0.2 percent of GDP, equivalent to US$0.8bn.
    - Global benchmark cited: 1 percent of GDP or US$3.75bn.
    - Philippines is second last among Southeast Asian countries (DTI, 2021).
- Cost and adoption barriers:
  - Adoption barriers cited: limited comprehension of AI capabilities; hesitancy due to high fixed capital costs and high licensing costs (ILO, 2017).
  - High fixed and licensing costs noted as key roadblocks for smaller firms and MSMEs.

### Methodology note and cross-country comparability
- Methodological innovation:
  - Linking occupation-level AI exposure and complementarity classifications to Philippine microdata from the October 2022 Labor Force Survey for granular occupation impact analysis.
- Comparability caveat:
  - Cross-country comparisons use ILO employment-by-occupation data at the 2-digit level (43 occupations) for other Asian economies versus Philippine data at the 4-digit level (436 occupations); granularity affects complementarity measures and comparability.

### Policy implications and recommended priorities
- Regulatory and governance actions:
  - Develop comprehensive legal and governance framework to ensure ethical AI use and manage labor market transitions, drawing on global best practices.
  - Harmonize forthcoming legislation to manage AI risks: algorithmic transparency, cybersecurity, privacy, errors, biases, and labor protection.
  - Evolve data privacy and intellectual property laws alongside AI advancement.
- Invest in infrastructure and incentives:
  - Improve internet connectivity and expand electricity grids; ensure reliable access to power for increased data center and AI demand.
  - Support development of a robust digital economy and entrepreneurial ecosystem.
  - Provide fiscal incentives for private sector investment in AI, including research and development grants.
- Strengthen education, training, and lifelong learning:
  - Update education system to include AI and related subjects at multiple levels; introduce basic AI concepts in early education.
  - On tertiary level, focus AI education on specialized knowledge and applications.
  - Strengthen TVET to develop sector-specific skills; promote lifelong learning and upskilling initiatives.
  - Foster collaboration between academia, industry, and government.
- Social protection and labor-market transition support:
  - Reinforce social protection systems, including unemployment insurance and reskilling/upskilling programs.
  - Note: Philippine Social Security System allows claiming unemployment benefits in case of redundancy due to the “installation of labor-saving devices.”
  - Combine reskilling programs with strategies for businesses to responsibly integrate AI while supporting and training workers.
  - Budget for potential fiscal costs related to increased unemployment insurance claims and reskilling programs.
  - Over the medium term, consider recalibrating taxation of capital income if the income share of labor declines due to AI adoption.
- International cooperation:
  - Engage in international partnerships, peer learning, and support from organizations like the IMF to navigate AI integration challenges and enhance competitiveness.

_Italic: Source: IMF Working Paper WP/2025/043, "Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity." (content as provided in the source)._

### Executive Summary ......................................................................................................

### Executive Summary

### Overview
- This paper examines the potential impact of recent advancements in artificial intelligence (AI) on the labor market in the Philippines, with particular attention to the large business process outsourcing (BPO) sector.
- The analysis builds on the occupational classification framework proposed by Cazzaniga et al. (2024), itself based on Felten et al. (2021) and Pizzinelli et al. (2023), combining an AI exposure index and an AI complementarity score to categorize occupations into: high exposure/high complementarity; high exposure/low complementarity; and low exposure.
- The occupation-level classifications are merged with microdata from the Philippine Statistics Authority's October 2022 Labor Force Survey, comprising 183,602 observations of 52 variables (over 180,000 observations, 80,000 of which are tagged as “employed”).

### Key findings: exposure and complementarity
- Around one third of occupations in the Philippines are highly exposed to AI, meaning their tasks could now be performed by AI technologies.
- Of those highly exposed occupations, 61% are also rated as highly complementary, suggesting AI is likely to augment rather than replace these roles and potentially increase productivity.
- The remainder—low complementarity jobs—represent 14% of the total workforce and are more susceptible to displacement by AI.

### Demographic and sectoral patterns
- Workers who are college-educated, young, urban, female, and well-paid in the service sector are most exposed to AI.
- These same characteristics also correlate with higher complementarity, indicating these groups may be better positioned to leverage AI as the nature of work evolves.

### BPO sector specifics and macro considerations
- BPO workers are classified as highly exposed with low complementarity in the analysis.
- BPO employees make up about 3% of the total workforce.
- BPO sector revenues accounted for 7.4% of GDP in 2023, a magnitude similar to remittances; therefore, changes in the BPO sector are macro-critical and may have spillover effects not fully captured by the occupation-level analysis.

### Government strategy, regulatory context, and challenges
- The Philippine government has introduced a National AI Strategy Roadmap (first in 2021, updated in 2024) outlining a strategic vision to integrate AI across sectors, boost competitiveness, foster R&D collaboration, prepare the workforce, and ensure responsible AI governance.
- The Trabaho Para sa Bayan Act (Republic Act No. 11962) aims to align education with industry needs and generate employment amid technological change.
- Several bills are under consideration to establish regulatory and developmental bodies for AI.
- Key challenges include regulatory gaps, inadequate infrastructure, workforce reskilling needs, and limited AI adoption due to cost concerns.

### Policy implications and recommended priorities
- Address regulatory gaps by developing a comprehensive legal and governance framework to ensure ethical AI use and manage labor market transitions, drawing on global best practices.
- Invest in education and training programs focused on AI and digital skills to prepare the workforce for the future and mitigate displacement risks.
- Promote measures to increase AI adoption where beneficial, accounting for cost barriers and infrastructure needs.
- Use the paper’s granular occupation-level analysis to inform targeted strategies to mitigate negative consequences (e.g., displacement) and maximize positive outcomes (e.g., productivity gains and new job creation).

### Methodological note
- The paper’s primary innovation is linking AI exposure and complementarity occupational classifications to Philippine microdata from the October 2022 Labor Force Survey to provide a granular picture of occupations potentially affected by AI and to correlate AI exposure with demographic indicators.

*Executive Summary — Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity (IMF Working Paper).*

### introduction spurred the interest of the public and within two months, it reached 100 million users. In

### wpiea2025043-print-pdf - introduction spurred the interest of the public and within two months, it reached 100 million users. In

### II. Context — Overview
- The introduction of advanced generative AI models spurred rapid public interest; within two months a model reached 100 million users.
- Comparison to historical diffusion: the internet and mobile phone took twenty years to reach 80 percent of countries.
- Rapid AI product development has led to multiple competing GPT versions (examples listed in the source: Google’s Gemini, Microsoft’s Bing AI, and Meta’s Llama) and a dramatic increase in AI patents from 2015-2022.
- Source data for labor-market graphs: Philippine Statistics Authority (data, April 2024 vintage), Own calculations.

### A. The Philippine Labor Market — Key findings
- Sectoral employment:
  - Majority of the workforce works in the services sector.
  - The remainder is broadly evenly split between agriculture and industry.
- Labor force participation by gender:
  - 75% of working age men are either working or looking for work.
  - 53% of working age women are either working or looking for work.
- Educational attainment:
  - Most working Filipinos’ highest educational degree is the (junior) high school diploma.
  - Just over a quarter hold a college degree.
- Employment type distribution:
  - Most common employment is a salaried position (private company, government, or private household).
  - Followed by self-employment.
  - Then unpaid family worker.
- Long-running trends (not current-state only):
  - Share of employment in agriculture has seen steady declines.
  - Share in industry and particularly services has increased over time.
- COVID-19 labor market shock (Figure 2 summary):
  - During COVID-19, unemployment spiked and labor force participation rate dropped.
  - As of April 2024:
    - Unemployment rate was 4.0%.
    - Labor force participation rate has recovered to pre-pandemic levels (measurement arguably noisier in recent years).
  - Underemployment remains significant: 10-15% of employed workers are looking for additional work or wanting longer hours.
- Wage evolution over the past 15 years (Figure 3 summary):
  - NCR minimum wage kept pace with inflation until COVID-19 but fell behind during the post-pandemic surge in inflation.
  - Average daily basic pay rose faster than inflation, resulting in roughly 30% real wage increase since 2009.
  - Minimum wage did not make gains in real terms over this time frame, suggesting real wage gains concentrated in higher-pay jobs requiring specific skills or education.
- Wage index labeling (Figure 3):
  - Index, 2009=100
  - Lines identified: Average Daily Basic Pay; NCR Minimum Wage; Real Average Daily Basic Pay; Real NCR Minimum Wage.

### B. The BPO Industry — Structure and importance
- Macroeconomic shares:
  - In 2023, the services sector accounted for 62.3 percent of total Gross Domestic Product (GDP).
  - In April 2024, the services sector accounted for 61.4 percent of employment (PSA labor force survey).
- BPO sector history and impact:
  - The BPO industry started in 1992.
  - Offshore outsourcing yields 20-40 percent reduction in costs even factoring in additional costs such as business setup and infrastructure access (Marasigan, 2015).
- Industry scale and contribution (2023 figures):
  - The Philippines holds an estimated 15 percent of the global outsourcing market.
  - Presence of 788 BPO companies (reported by the Philippine Economic Zone Authority).
  - BPO sector generated US$35.5 billion in revenues, an increase of 9 percent over the previous year.
  - BPO revenues were equivalent to 8.1 percent of the country's total GDP.
  - BPO employs 1.7 million Filipinos, equivalent to 3.4 percent of the total labor force as of 2023.
- Economic spillovers and comparative scale:
  - Despite a relatively small share in the country's labor market, the industry generates positive spillovers to other sectors such as property and services.
  - BPO revenues are substantial and nearly as large as overseas remittances.
- Drivers of industry expansion:
  - Robust government support.
  - Low labor costs.
  - Abundant pool of service-oriented, English speaking and young workforce.
  - Conducive business environment.
- Industry composition:
  - Majority of revenues are generated by contact centers and back-office support services (Box 2 referenced in source).
- Market geography (IBPAP highlights):
  - North America holds a 70 percent share of the BPO industry market.
  - Europe holds 15 percent.
  - Asia-Pacific Region holds 15 percent.
  - North America dominance attributed to extensive English-speaking population, cost-effective labor, and close cultural ties with the United States.
  - Europe leverages distinctive talent specialization and cost efficiency.
  - Asia-Pacific leverages relative lack of onshore BPO centers for client markets, geographical proximity, and time zone overlap.

*Source: IMF Working Paper excerpt (Philippine labor market and BPO industry context, data and figures as provided in the source content).*

### Box 2. Types of BPO Services

### Box 2. Types of BPO Services

### Categories of BPO Services
- Contact Center - Consist of in-bound and outbound voice operation services for the purpose of sales, customer service, technical support, and others.
- Back Office - Service related to finance and accounting and human resource administration.
- Data Transcription - Provision of transcription services for interpreting oral dictation of health professionals, dictations during legal proceedings, and other data encoding services.
- Animation - Process of giving the illusion of movement to cinematographic drawings, models or inanimate objects through 2D, 3D, etc.
- Software Development - Analysis and design, prototyping, programming, and testing, customization, reengineering, and conversion, installation and maintenance, education and training of systems software, middleware and application software.
- Engineering Development - Includes engineering design for civil works, building and building components, ship building, and electronics.
- Digital Content - Creation of products that are available in digital form, such as music, information, and images that are available for download or distribution on electronic media.

### Source and References Cited in Box
- Source: Department of Trade and Industry (DTI), Locsin (2006), The Computer Language Company Inc. (2006)
- Footnoted links listed in the box:
  - https://www.magellan-solutions.com/blog/whats-the-number-analysis-of-the-latest-statistics-of-the-bpo-industry/
  - https://www.magellan-solutions.com/studies/call-center-benchmarking-report/

*Source: wpiea2025043-print-pdf - Box 2. Types of BPO Services (IMF Working Paper).*

### References to AI can also be found in other, broader, government strategies. The Philippine Development

### Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity

### References to AI in government strategies
- The Philippine Development Plan includes commitments to adopting AI in the following strategies:
  - Anticipate skills needs in priority sectors (Chapter 4, Outcome 2)
  - Increase access of MSMEs to capital, digital technologies, and startups (Chapter 7, Outcome 2)
  - Support globally competitive industries and an agile workforce (Chapter 8, Outcome 4)
  - Enhance monitoring and understanding of emerging technologies, markets, and business models (Chapter 10, Cross-Cutting Strategies)
  - Promote RegTech development (Chapter 11, Cross-Cutting Strategies)

### Identification of policy gaps and implementation challenges
- Regulatory and governance gaps:
  - National AI Strategy Roadmap and its update are promising but lack of legislation limits effectiveness.
  - A forthcoming harmonized legislation from proposed bills (as of January 2025, these include house bills 7396, 9448, 7913, 7983) is expected to manage AI risks such as algorithmic transparency, cybersecurity, privacy, errors, biases, and labor protection.
  - Data privacy and intellectual property laws must evolve alongside rapid AI advancement.
  - Examples of external developments: United Kingdom and European Union guidelines for ethical AI use; the UN adopted a resolution for safe AI in March 2024.
- Physical and digital infrastructure gaps:
  - Example load: an AI chatbot handling 195 million queries needs data centers consuming power equivalent to 23,000 U.S. households.
  - Data centers’ electricity consumption is expected to increase, straining grids (countries cited: US and Ireland).
  - Existing Philippine electricity access and reliability gaps: about two million households still lack electricity; power interruptions remain common (PIDS, 2023).
  - Internet performance and affordability:
    - 2023 Worldwide Broadband Speed League: Philippines ranked 86th out of 220 countries with an average download speed of 43.36mbps, compared with the Asian average of 45.72mbps.
    - World Data Lab estimate: nearly 19 million Filipinos or 16.6 percent of the population cannot afford a minimum package of internet.
  - Digital infrastructure quality affects households and firms, particularly MSMEs facing capacity, cost, and access challenges.
- Skills and human capital gaps:
  - The Future of Jobs report: 23 percent of the workforce will change within five years, with 60 percent needing training by 2027 centered on creative and analytical thinking, AI, and big data (WEF, 2023).
  - Despite high internet penetration, 90 percent of Filipinos lack basic ICT skills.
  - The Philippines lags in international education assessments in mathematics, reading, science, and creative thinking.
  - Workers lack soft skills: adaptability, problem-solving, and collaboration (PIDS, 2023).
  - Barriers to skill enhancement include inadequate internet access, lack of time, high training costs, and limited opportunities (Economist, 2023).
  - Government responses: multiple training initiatives underway, industry-backed reskilling; updating education curriculum and reskilling educators.
  - Industry projection: IBPAP noted the Philippine tech industry is expected to generate 1.1 million new jobs by 2028, requiring a steady supply of skilled workers.
- Use cases and cost of adoption:
  - Adoption barriers: limited comprehension of AI capabilities and limitations among some firms; hesitancy due to high costs and unclear returns.
  - Key roadblocks: high fixed capital costs and high licensing costs (ILO, 2017).
  - Cisco survey of Philippine firms on AI readiness:
    - 17 percent are ready to deploy and use AI in business processes
    - 44 percent are moderately ready
    - 35 percent indicated minimal readiness
    - 4 percent are not prepared to use AI
  - Research and development spending:
    - Philippines spending: less than 0.2 percent of GDP, equivalent to US$0.8bn
    - Global benchmark: 1 percent of GDP or US$3.75bn
    - Philippines is second last among Southeast Asian countries (DTI, 2021)

### Key findings on labor-market exposure and complementarity
- Overall exposure and displacement risk:
  - 14 percent of jobs are classified to be at risk of displacement by AI.
  - 22 percent of jobs are likely to see the nature of their work change significantly as AI is rolled out.
- Sectoral focus:
  - BPO sector:
    - BPO employees make up about 3 percent of the total workforce.
    - BPO revenues represent 7.4 percent of GDP (similar in magnitude to all remittances).
    - The BPO sector is the most exposed sector and generates large potential spillovers to other parts of the economy.
- Cross-country comparison caveat:
  - Exposure and complementarity shares for other Asian economies use ILO employment-by-occupation data at the 2-digit level (43 occupations), compared with Philippine data at the 4-digit level (436 occupations); granularity affects complementarity measures and comparability.

### Quantitative examples and comparative shares (from Table 2)
- High exposure, high complementarity example occupations (Philippines shares):
  - ILO: 10%
  - PSA: 22%
  - Other Asian EMDEs: 9%
  - Asian AEs: 24%
  - Example occupations: General and Operations Managers, First-Line Supervisors, Teachers and Teaching Assistants, Lawyers, Civil Engineers, Counselors
- High exposure, low complementarity example occupations (Philippines shares):
  - ILO: 27%
  - PSA: 14%
  - Other Asian EMDEs: 18%
  - Asian AEs: 26%
  - Example occupations: Customer Service Representatives, Telemarketers, Accountants, Auditors, Secretaries, Administrative Clerks
- Low exposure example occupations (Philippines shares):
  - ILO: 63%
  - PSA: 64%
  - Other Asian EMDEs: 73%
  - Asian AEs: 50%
  - Example occupations: Farmworkers, Construction Laborers, Janitors, Maids and Cleaners, Waiters, Textile workers, Food Preparation Workers
- Sample countries:
  - AE = AUS, SGP, JPN
  - EMDE = BGD, BRN, BTN, IDN, IND, KHM, KIR, LAO, LKA, MDV, MNG, PHL, PNG, THA, TLS, TUV, VNM, WSM

### Policy recommendations to foster AI adoption and mitigate risks
- Invest in digital and physical infrastructure:
  - Improve internet connectivity and expand electricity grids.
  - Ensure reliable access to power to accommodate increased data center and AI-related demand.
  - Support development of a robust digital economy and entrepreneurial ecosystem to foster innovation and AI deployment.
  - Provide fiscal incentives for private sector investment in AI, including research and development grants.
- Enhance human capital and education:
  - Update the education system to include AI and related subjects at multiple levels.
  - Introduce basic AI concepts in early education to build foundational understanding and critical thinking.
  - On the tertiary level, focus AI education on specialized knowledge and applications for advanced roles.
  - Strengthen TVET to develop sector-specific skills, adapt curricula to industry needs, and provide lifelong learning opportunities.
  - Promote lifelong learning and upskilling initiatives and foster collaboration between academia, industry, and government to bridge the skills gap.
- Strengthen social protection and labor-market transition support:
  - Reinforce social protection systems, including unemployment insurance and reskilling/upskilling programs.
  - Note: the Philippine Social Security System allows claiming unemployment benefits in the case of redundancy due to the “installation of labor-saving devices.”
  - Combine reskilling programs with strategies for businesses to responsibly integrate AI while supporting and training workers.
  - Budget for potential fiscal costs related to increased unemployment insurance claims and reskilling programs.
  - Over the medium term, consider recalibrating taxation of capital income if the income share of labor declines due to AI adoption (see Cazzaniga et al. (2024) for in-depth discussion).
- Leverage international cooperation:
  - Engage in international partnerships, peer learning, and support from organizations like the IMF to navigate AI integration challenges and enhance competitiveness in the global digital economy.

*Source: IMF Working Paper WP/2025/043, "Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity."*

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_Source: https://www.imf.org/-/media/files/publications/wp/2025/english/wpiea2025043-print-pdf.pdf_