The industry that changed the Philippines is changing again
At eleven at night the office towers of Metro Manila are lit floor by floor, and rows of agents in headsets are working the American afternoon. The scene repeats in Cebu and Cagayan de Oro, in buildings that did not exist a generation ago. Behind every chair is a household: a tuition paid on time, a parent's maintenance medicine, a small business started on a thirteenth-month bonus.
The IT-BPM sector employed 1.9 million Filipinos and earned US$40 billion in export revenues in 2025, according to IBPAP figures reported in July. AMRO puts the previous year's US$38 billion in revenue at 8.2% of GDP and its 1.8 million workers at 3.8% of all employment.
It is also the sector most exposed to the defining technology of this decade. That is a threat, and only half the picture.
The Philippines does not merely face the possibility of AI replacing outsourced work. It also has the opportunity to become one of the countries that supplies the human intelligence behind AI.
This article is about the second sentence. We argue that the next boom will come from organising Filipino judgment at industrial scale: the labelling, evaluation, red-teaming and safety oversight every serious AI system depends on. We call that Human Intelligence Outsourcing.
Is Philippine BPO really falling?
The anxiety is older than ChatGPT. In 2018 then Trade Secretary Ramon Lopez said AI was "estimated to affect half of the 1.3 million jobs in the sector". Eight years later the sector has added roughly six hundred thousand jobs.
The numbers still point up. Export revenues exceeded US$40 billion in 2025, 5% growth on 2024. The contact-center segment alone added more than 60,000 jobs to reach 1.68 million. IBPAP's guidance for 2026 is about 1.96 to 1.97 million employees and US$42 to 42.3 billion [7]. None of that looks like a collapse.
The honest reading is less comfortable. In July 2026 IBPAP cut its 2028 roadmap targets from the original 2.5 million jobs and US$59 billion to 1.85 to 2.14 million jobs and US$43.3 to 50.5 billion. Jack Madrid of IBPAP: "We need to review where we are and be honest about what we can achieve realistically." The new goal is two million "AI-enabled Digital Filipino Workers" by 2028, and "the most important word there is AI-enabled."
What the exposure studies actually say
The studies agree on the shape of the problem and disagree on its size. An IMF working paper finds around one third of Filipino workers highly exposed to AI, with around sixty percent of those also rated highly complementary, meaning it is likelier to raise their output than replace them, though BPO has the highest proportion of jobs at risk. The ILO puts more than a quarter of Philippine employment, 12.7 million jobs, in the exposed category, but only 3.6% in the highest tier, and expects "transformation, not replacement". The World Bank's 2026 World Development Report puts 4.5% of existing jobs in low- and middle-income countries at risk of automation, against 14.2% in high-income countries.
Which tasks go first
The work most exposed first is the work that was already scripted: basic inquiries and account look-ups, scripted voice support, routine email and chat handling, transcription, simple content moderation, repetitive back-office processing, basic data entry and rule-based quality checks.
Complex, regulated, relationship-heavy work is different. Healthcare, finance, technical support and anything where a wrong answer carries liability gets transformed rather than eliminated, because someone still has to own the judgment. A study of 5,179 support agents found an AI assistant raised issues resolved per hour by 14% on average and 34% for novices, with minimal impact on experienced agents. It closed the gap between a new hire and a veteran. It did not remove the veteran.
Payroll data says the same. Stanford's Digital Economy Lab finds employment of 22- to 25-year-olds in the most AI-exposed US occupations about 19% below where it would otherwise be, yet no widespread displacement: the declines sit where AI automates tasks, while employment is flat or rising where it complements workers. DEPDev Secretary Arsenio Balisacan says fears of losing a substantial part of the industry "appear to be exaggerated", and about 67% of Philippine IT-BPM firms already deploy AI. This is a structural transition, and the question is which side of that line Filipino workers are standing on.
This is a structural transition, and the question is which side of that line Filipino workers are standing on.
From BPO to HIO: the call center becomes an intelligence center
We propose a name for the work on the right side of that line. Human Intelligence Outsourcing (HIO) is the organized delivery of human judgment, domain expertise, cultural understanding, quality control, and safety oversight required to train, evaluate, improve, and operate artificial intelligence systems.
The contrast is the whole point. Traditional BPO outsources repeatable business processes. Human Intelligence Outsourcing delivers the human judgment needed to develop, test, supervise, and improve intelligent systems.
We could find no prior use of the phrase as a named category. Neighbouring terms ("human-in-the-loop" outsourcing, "AI data services", "expert data", IBPAP's "AI-enabled Digital Filipino Workers") describe pieces. HIO names the industry they add up to, and industries, unlike pieces, get roadmaps, associations, curricula and policy.
Look at the building. A call center is organised around handling time: a queue cleared, a script delivered warmly, a satisfaction score. An intelligence center is organised around judgment: a system to be trained, tested and supervised, a worker skilled at calibrated evaluation, a metric of agreement with expert reviewers. Same workforce, same towers, different product.
| Traditional BPO | Human Intelligence Outsourcing | |
|---|---|---|
| Primary client need | A repeatable business process handled at lower cost | An AI system trained, evaluated, supervised and improved |
| Nature of the work | Scripted handling of calls, tickets and back-office queues | Labelling, comparing, grading, red-teaming, reviewing model output and exceptions |
| Worker skills | Language fluency, empathy, process adherence, speed | Domain knowledge, calibrated judgment, structured writing, tool literacy, security discipline |
| Deliverables | Closed calls, processed transactions, resolved tickets | Datasets, preference rankings, evaluation reports, safety findings, managed human-in-the-loop operations |
| Pricing model | Per seat, per hour, per transaction | Per task, per expert hour, per dedicated team, per evaluation cycle, outcome-based |
| Quality measurement | Handle time, satisfaction scores, volume | Accuracy, inter-rater agreement, expert audit pass rate, safety incident rate |
| Technology requirements | Telephony, CRM, workforce management | Secure annotation and evaluation platforms, access-controlled environments, audit logs, model sandboxes |
| Potential value per worker | Bounded by the seat price; margin comes from labour-cost arbitrage | Priced on scarce expertise and accountability; Mercor, an expert-data marketplace, reports its contributors earning an average of US$85+ per hour [17] |
What HIO could deliver
The demand stopped being hypothetical last year. Meta took a 49% stake in Scale AI for a reported US$14.3 billion at a US$29 billion valuation; Scale itself says only "over $29 billion". Mercor raised US$350 million at a US$10 billion valuation in October 2025 with more than 30,000 experts on its books. Turing, which supplies OpenAI, Google, Anthropic and Meta, reached profitability in 2024 on about US$300 million of annualised revenue. The money is there. The question is who does the work, on what terms.
We see seven service pillars, from most commoditised to most valuable:
- Training data. Labelling and annotating text, speech, image and video, including Filipino and regional-language data nobody else can produce.
- RLHF and human feedback. Ranking and rewriting model responses, writing rationales, grading against rubrics.
- Expert data. Nurses, accountants, lawyers and engineers producing and reviewing domain examples.
- AI evaluation. Structured testing of models and agents against benchmarks, edge cases and real workflows.
- Red teaming and AI safety. Adversarial testing for harmful output, jailbreaks, bias and misuse.
- Applied AI operations. Human-in-the-loop supervision of deployed systems: exceptions, escalation, correction.
- Public-sector and sovereign AI services. Evaluation, data governance and oversight for government systems.
The last pillar includes defence and security uses, which in our view a Philippine HIO company should take only under lawful use, democratic oversight, data-protection law, human-rights due diligence, strong security controls and responsible procurement.
| Service category | Worker profile | Client deliverable |
|---|---|---|
| Training data | Trained annotators with language and cultural range; provincial delivery viable | Labelled datasets with documented guidelines and agreement scores |
| RLHF and human feedback | Strong writers with calibrated judgment, often from contact-center QA | Preference rankings, rationales, rubric scores, rewritten responses |
| Expert data | Licensed or degreed domain professionals | Verified domain examples, expert review logs, error taxonomies |
| AI evaluation | Analysts with test-design and reporting skills | Evaluation reports, failure analyses, benchmark results |
| Red teaming and AI safety | Adversarial thinkers with policy and security literacy | Vulnerability findings, jailbreak catalogues, mitigation recommendations |
| Applied AI operations | Former agents and team leads retrained for exception handling | Managed human-in-the-loop service with agreed accuracy and escalation levels |
| Public-sector and sovereign AI | Cleared staff in secure facilities | Audited evaluations, governance documentation, oversight reporting |
Why the Philippines could win
The country is the world's second-largest services hub after India, with an estimated 16 to 18% of global IT-BPM employment. It ranks 28th in the world on the EF English Proficiency Index with a "High" rating, second in Asia behind Malaysia, with India at 74th.
Less visible strengths matter more for HIO. Nearly nine in ten workers in the industry sit in contact-center work [2]: a very large pool of people who have spent years being scored against rubrics and calibrated by quality analysts. That is evaluation culture, which is exactly what human-feedback work demands. Delivery is already provincial: more than 10,000 residents of Cagayan de Oro were trained on Scale's Remotasks platform, and more than two million Filipinos do some form of crowdwork. And the IMF's profile of the most exposed worker, college-educated, young and urban [9], is also the profile of the ideal HIO recruit.
Now the weaknesses, because a strategy that ignores them is a brochure. India's technology industry is roughly seven times larger, at US$282.6 billion in revenue and 5.8 million employees. The Philippines hosts around 200 global capability centers, adding roughly ten a year against a target of twenty to thirty. Power costs ₱12.43 per kilowatt-hour, the highest in Southeast Asia. And PIDS has warned of an oversupply of IT graduates alongside a STEM shortage.
Why empathy and English are not enough
Empathy and English got the Philippines into the room. They will not, on their own, keep it there. Buyers of human intelligence pay for analytical reasoning, technical literacy, domain expertise, structured writing, data-security discipline, fluency with AI tools, critical thinking and, above all, calibrated judgment: giving the answer an expert panel would give, consistently, and explaining why. None of those is a personality trait. All can be taught.
Empathy and English got the Philippines into the room. They will not, on their own, keep it there.
The business model: how an intelligence center makes money
An HIO company runs a loop, not a queue. The nine steps are in the diagram below; the one that matters most is the last: errors and edge cases go back into the client's development cycle, and the loop runs again, because yesterday's guideline is today's blind spot.
Commercial forms follow the work: per-task pricing for annotation; hourly expert rates; dedicated teams contracted to one lab; outcome-based contracts tied to model performance; evaluation subscriptions, a standing human test bench run on every release; secure delivery centers for regulated data; and curated expert networks.
Cheap labour does not make any of this defensible; anyone can be undercut. What does is client relationships, secure technology, proprietary workflows and guideline libraries, assessments that prove a contributor is calibrated, a specialised talent pool, a quality system, a compliance posture and accumulated knowledge of how a given lab wants its data.
Turning BPO workers into AI-era professionals
Retraining is where this either happens or does not. The intelligence center's org chart maps onto the contact center's with surprising fidelity: ten roles, where each comes from, what changes, and what the first ninety days contain. This is a forecast, not a job board.
| Today's role | New role | What changes | First ninety days |
|---|---|---|---|
| Team leader | Human-in-the-Loop Team Lead | Coaches judgment and calibration instead of handle time; owns escalation between model and human | Calibration sessions, guideline ownership, a first managed queue with accuracy targets |
| Workforce or operations analyst | RLHF Operations Specialist | Runs preference-data pipelines: task design, throughput, agreement monitoring | Learn the lab's rubric system, ship a first ranked dataset, track inter-rater agreement |
| Call-center agent | Model Evaluation Analyst (Conversational-AI Evaluator) | Grades AI conversations instead of having them; writes the reason for every score | Rubric training, supervised grading against a calibration panel, first solo evaluation set |
| Quality analyst | AI Quality & Safety Analyst | Audits model output and human labels; owns the error taxonomy and safety flags | Build the project's error taxonomy, run the first audit cycle, report findings to the client |
| Content moderator | Trust-and-Safety Evaluator | Moves from deleting posts to testing policies: red-team prompts, harm classification, policy feedback | Policy training, adversarial-testing methods, mental-health protocol onboarding |
| Technical-support specialist | Software/Coding Evaluator | Reviews AI-generated code and agent traces for correctness, security and style | Language refresh, code-review standards, first graded coding-evaluation batch |
| Healthcare BPO specialist | Medical-AI Data Specialist | Applies clinical coding and documentation knowledge to label, verify and evaluate medical AI output | Clinical-AI guidelines, health-data privacy handling, supervised clinical evaluation work |
| Finance and accounting associate | Financial-Model Validation Specialist | Tests AI on reconciliations, KYC, fraud and reporting; documents failure modes | Domain rubric design, regulatory-context training, first validation report |
| Recruitment or workforce-management specialist | Contributor Marketplace Operator | Sources, assesses, pays and retains expert contributors on the company's platform | Assessment design, onboarding flow, payment-integrity controls |
| Trainer or learning specialist | AI-Training Curriculum Designer | Builds the courses and calibration exercises every other role depends on | Author the foundation module, run a pilot cohort, measure calibration gains |
None of this is a seminar. Moving an agent into evaluation work takes months of structured education, an assessment with a real failure rate, supervised production work under a calibration panel, and continuing certification as models change. A two-day workshop sold as a career transition is a certificate, not a career.
The institutions are moving, unevenly. TESDA offers free online courses on AI concepts, responsible AI use and practical applications. IBPAP has committed at least US$25 million a year to future-proof the workforce, as the Manila Times reports it, and ₱740 million to Project UNLAD. These are foundations. The intelligence center's curriculum still has to be written, mostly by the companies that will hire from it.
Risks and ethical questions
The record of AI data work so far is not flattering. The risks are specific: piecework pay below the minimum wage, projects that vanish without notice, misclassification of employees as contractors, hidden subcontracting chains, intrusive monitoring, exposure to disturbing content, confidentiality rules that silence workers, weak grievance channels, data leakage, bias baked into guidelines, inconsistent quality, and the sharpest one, trainers displaced by the systems they train.
The evidence is Philippine as much as global. A Washington Post investigation, summarised by the Business & Human Rights Resource Centre, found at least 10,000 Filipinos working on Remotasks, some paid less than one cent per task, and 34 of 36 workers interviewed reporting delayed, reduced or cancelled payments; Scale called such delays "exceedingly rare". A European trade-union study found pay per microtask had halved since 2022, with one Cagayan de Oro worker averaging about six euros for an eight-to-ten-hour day. Scale has agreed to pay US$12.5 million to settle a California misclassification suit whose allegations included screenshots of workers' screens and docked pay. Oxford's Fairwork project, rating platforms out of ten in 2023, gave Appen 3, Remotasks 1 and Amazon Mechanical Turk 0; none met minimum standards.
The content-moderation precedent is darker: moderators in Manila, making several hundred decisions a day, described "nightmares, paranoia and obsessive ruminations". Nor is the BPO baseline comfortable. A union survey of 394 workers across 56 companies found 65% earning below the family living wage of ₱27,196 a month, in what BIEN's Mylene Cabalona calls "a non-unionized industry". Renso Bajala of BIEN put it simply: "AI should serve humanity and uplift the dignity of work, not further deepen exploitation."
A responsible Philippine HIO company differentiates on exactly these points, treating them as product specification rather than compliance burden: transparent terms before work is accepted; fair, predictable pay above the local minimum wage; mental-health protection with rotation limits and clinical support; confidentiality that protects client data without gagging workers; whistleblower protection with an outside channel; audited security controls; auditable quality, so pay rests on measured accuracy; appeals for rejected work; visible skills progression; and profit-sharing tied to project outcomes.
Do not present exploitative labour arbitrage as innovation. The country has seen that film before.
A Philippine opportunity, not merely a subcontracting opportunity
There are two ways this can go. In the first, Filipinos supply anonymous labour to foreign platforms: rated by an algorithm, paid per task, invisible in the supply chain, replaceable the moment a cheaper country comes online. Scale's network was described as approximately 240,000 independent workers across southern countries.
In the second, Philippine companies own the customer relationship, the technology, the quality system, the intellectual property in their guidelines and assessments, the workforce and the delivery. They partner with global labs as vendors of record, the way Turing and Mercor do, not as an unnamed crowd behind someone else's dashboard. Supplying anonymous labour to a foreign platform is a subcontracting opportunity. Owning the platform is a national one.
Policy can tilt the outcome. The national AI strategy approved in May 2025 lists workforce and data governance among its five drivers, and bills to create a Philippine Council on Artificial Intelligence and a Bureau of Artificial Intelligence Systems are pending in committee. An HIO industry strategy belongs inside that framework, with IBPAP and CXAP at the table, measured by how much of the value chain stays onshore.
Supplying anonymous labour to a foreign platform is a subcontracting opportunity. Owning the platform is a national one.
Train Filipino talent to power AI
The night shift is not ending. It is changing what it produces. The future of Philippine outsourcing should not be measured only by how many calls Filipinos can answer. It should be measured by how much trusted human intelligence the country can contribute to the systems reshaping the global economy.
That takes companies that build intelligence centers rather than rent seats, institutions that write a real curriculum, a government that treats the industry as strategic, and honesty about who gets displaced in the meantime and what they are owed.
Don't let Filipino talent be displaced by AI. Build the institutions, companies, and skills that allow Filipino talent to power AI.
A note on the term
Sources and further reading
- Newsbytes (reporting IBPAP), Converge, IBPAP team up on AI upskilling for BPO workers, 2026-07-03. newsbytes.ph/2026/07/03/converge-ibpap-team-up-on-ai-upskilling-for/
- AMRO (ASEAN+3 Macroeconomic Research Office), Can the Philippines IT-BPM Industry Stay Ahead Amid the AI Wave?, 2025-12-10. amro-asia.org/can-the-philippines-it-bpm-industry-stay-ahead-amid-the-ai-wave
- Inquirer Technology, AI vs AI: PH gov't uses job security threat to train BPO workers, 2018-05-24. technology.inquirer.net/76052/ai-vs-ai-ph-govt-uses-job-security-threat-train-bpo-workers-bpo-dti-call-centers-artificial-intelligence-employment-jobless-it
- Philippine Daily Inquirer (reporting IBPAP), IT-business process management revenues top $40B in 2025, 2026-01-29. business.inquirer.net/571179/it-bpm-revenues-top-40b
- Philstar / The Freeman (reporting CXAP), Philippines contact center industry braces for AI-driven future, 2026-05-29. www.philstar.com/the-freeman/cebu-business/2026/05/29/2531292/philippines-contact-center-industry-braces-ai-driven-future
- Newsbytes (reporting IBPAP), IBPAP sets skills-focused agenda for 2026 as AI reshapes IT-BPM industry, 2026-01-30. newsbytes.ph/2026/01/30/ibpap-sets-skills-focused-agenda-for-2026-as-ai-reshapes-it-bpm-industry/
- BusinessMirror (reporting IBPAP), IT-BPM cuts 2028 targets, but keeps 2026 growth intact, 2026-07-15. businessmirror.com.ph/2026/07/15/it-bpm-cuts-2028-targets-but-keeps-2026-growth-intact/
- Manila Bulletin (reporting IBPAP), IBPAP launches industry pride campaign to reach 2.5-M jobs by 2028, 2024-03-06. mb.com.ph/2024/3/6/ibpap-launches-industry-pride-campaign-to-reach-2-5-m-jobs-by-2028
- IMF, Cucio & Hennig (abstract via RePEc), Artificial Intelligence and the Philippine Labor Market: Mapping Occupational Exposure and Complementarity (WP/2025/043), 2025-02. ideas.repec.org/p/imf/imfwpa/2025-043.html
- ILO, Phu Huynh, Generative AI and jobs in the Philippines: Labour market exposure and policy implications, 2026-02-05. www.ilo.org/publications/generative-ai-and-jobs-philippines-labour-market-exposure-and-policy
- ILO, One in four jobs at risk of being transformed by GenAI, new ILO–NASK global index shows, 2025-05-20. www.ilo.org/resource/news/one-four-jobs-risk-being-transformed-genai-new-ilo%E2%80%93nask-global-index-shows
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- NBER, Brynjolfsson, Li & Raymond (published in the Quarterly Journal of Economics, 2025), Generative AI at Work (Working Paper 31161), 2023-04. www.nber.org/papers/w31161
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- U.S. International Trade Administration, Philippines – Strategic Technologies (Country Commercial Guide), 2025-12. www.trade.gov/country-commercial-guides/philippines-strategic-technologies
- TechCrunch, Mercor quintuples valuation to $10B with $350M Series C, 2025-10-27. techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/
- TechCrunch, Scale AI confirms 'significant' investment from Meta, says CEO Alexandr Wang is leaving, 2025-06-13. techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/
- Scale AI, Founder, Alexandr Wang, Joins Meta to Work on AI Efforts, 2025-06-12. scale.com/blog/scale-ai-announces-next-phase-of-company-evolution
- Sacra (company-reported figures), Turing revenue, funding & news, 2025-03. sacra.com/c/turing/
- EF Education First, EF English Proficiency Index 2025: Philippines, 2025-11. www.ef.com/wwen/epi/regions/asia/philippines/
- Human Resources Online, 2025 ranking: English proficiency levels around Asia, 2026-02-04. www.humanresourcesonline.net/2025-ranking-english-proficiency-levels-around-asia
- transform! europe (republishing Théophile Simon, ETUI HesaMag), The Filipino workers at the sharp end of AI, 2026-06-17. transform-network.net/blog/analysis/the-filipino-workers-at-the-sharp-end-of-ai/
- Business & Human Rights Resource Centre (summarising The Washington Post), Philippines: Scale AI creating 'race to the bottom' as outsourced workers face poor conditions in digital sweatshops, 2023-08-30. www.business-humanrights.org/en/latest-news/philippines-scale-ai-creating-race-to-the-bottom-as-outsourced-workers-face-poor-conditions-in-digital-sweatshops-incl-low-wages-withheld-payments/
- Business Today (reporting Nasscom Strategic Review 2025), Indian tech industry to reach $300 billion revenue milestone in FY26: Nasscom, 2025-02-24. www.businesstoday.in/technology/news/story/indian-tech-industry-to-reach-300-billion-revenue-milestone-in-fy26-nasscom-465747-2025-02-24
- Philstar (reporting the Department of Energy), DOE: Philippines power rates now highest in SEA, 2026-07-21. www.philstar.com/headlines/2026/07/21/2543545/doe-philippines-power-rates-now-highest-sea
- Philippine Institute for Development Studies, Philippines facing oversupply in IT graduates, STEM shortage, 2021-02-26. www.pids.gov.ph/details/philippines-facing-oversupply-in-it-graduates-stem-shortage
- PhilSTAR Life (reporting TESDA), TESDA offers courses on digital skills, AI for free, 2026-06-01. philstarlife.com/geeky/347531-tesda-offers-ai-digital-skills-courses
- The Manila Times, Sheila Lobien, The AI Reckoning: What artificial intelligence means for Philippine jobs, BPO, and real estate, 2026-06-30. www.manilatimes.net/2026/06/30/the-manila-times-500/the-ai-reckoning-what-artificial-intelligence-means-for-philippine-jobs-bpo-and-real-estate/2379588
- King & Siegel LLP, Scale AI Pays $12.5 Million Over Claims It Built Its AI Pipeline on Misclassified Workers, 2026-08-04. www.kingsiegel.com/blog/scale-ai-misclassification-settlement-california-class-action/
- Oxford Internet Institute (Fairwork Cloudwork Ratings 2023), New Oxford Report Sheds Light on Labour Malpractices in the Remote Work and AI Booms, 2023-07-20. www.oii.ox.ac.uk/news-events/new-oxford-report-sheds-light-on-labour-malpractices-in-the-remote-work-and-ai-booms/
- Business & Human Rights Resource Centre (summarising The Washington Post), Philippines: Report highlights psychological distress outsourced social media content moderators experience, 2019-07-29. www.business-humanrights.org/en/latest-news/philippines-report-highlights-psychological-distress-outsourced-social-media-content-moderators-experience/
- PhilSTAR Life, Renso Bajala (BIEN), We trained the AI that replaced us, 2026-07-27. philstarlife.com/news-and-views/410656-workers-push-back-against-ai-in-the-bpo-industry
- GMA News, Lacking job security, Filipino call center workers face AI threat, 2024-12-03. www.gmanetwork.com/news/money/companies/928904/lacking-job-security-filipino-call-center-workers-face-ai-threat/story/
- Newsbytes (reporting DOST and the Presidential Communications Office), Marcos Jr. approves national AI strategy to position PH as regional AI leader, 2025-05-23. newsbytes.ph/2025/05/23/marcos-jr-approves-national-ai-strategy-to-position-ph-as-regional-ai-leader/
- Foundation for Media Alternatives, Regulating Risk: The 20th Congress of the Philippines Response to Artificial Intelligence, 2026-05-28. fma.ph/regulating-risk-the-20th-congress-of-the-philippines-response-to-artificial-intelligence/
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