The Philippines’ digital economy continues to expand rapidly, reaching an estimated USD 31 billion in gross merchandise value (GMV) in 2024, with projections to double by the end of the decade. This growth has been fuelled by increased mobile penetration, the adoption of digital payments, and the rise of e-commerce and platform-based work.
Yet, alongside this progress, structural challenges persist in ensuring the responsible and inclusive adoption of emerging technologies, particularly artificial intelligence (AI). Gaps in digital infrastructure limit connectivity in rural areas, while a widening digital skills gap prevents micro, small, and medium enterprises (MSMEs) from fully harnessing AI-driven opportunities. Current mandates for AI governance are fragmented across multiple agencies, highlighting the need to integrate siloed programmes into a coherent national development strategy. In addition, challenges in data governance and responsible data-sharing policies constrain the research and development of localised solutions tailored to the country’s unique needs.
Against this backdrop, the Tech for Good Institute had the privilege of participating in the plenary panel on “Reimagining Governance in the Age of AI” at the Philippine Institute of Development Studies’ 11th Annual Public Policy Conference. The panel convened diverse voices from both regional and local contexts to explore what adaptive AI governance could look like for the Philippines. The discussion also underscored how AI can enhance public service delivery by drawing lessons from global practice while remaining attuned to local realities.
Moderator and Panelists
- Keith Detros, Programme Manager, Tech For Good Institute
- Christopher Lamont, Professor International Relations, Tokyo International University
- Naoto Kanehira, Senior Digital Development Specialist, The World Bank
- Mary Grace Mirandilla-Santos, ICT Policy Analyst, Secure Connections and AI4PH
- Arifah Sharifuddin, Institute Director, Tech For Good Institute
Key Takeaways
1. AI governance must reflect the Philippines’ unique realities and interests
Model AI frameworks from countries such as the European Union (EU), United States (US), and China can serve as reference points for the Philippines’ strategy towards AI. But rather than wholly replicating these models, the Philippines should develop its own model of governance which better reflects its national interests and unique realities. For instance, AI strategies can be crafted to address the nation’s structural developmental challenges in areas such as disaster management, agriculture and education. To this end, establishment of cross-sectoral bodies such as the National Innovation Council, the Private Sector Advisory Council, and the Philippine AI Council, which brings together government, industry, and civil society, is a positive step in shaping locally relevant and trusted AI frameworks. Cross-sectoral consultative bodies, potentially modeled on multi-stakeholder councils in the energy or ICT sectors, could be institutionalised to ensure balanced perspectives guide policymaking. Frameworks must also be operationalised to ensure that AI adoption supports inclusive economic growth, job creation, and public service delivery.
2. Infrastructure and investments are necessary for inclusive adoption
The potential of AI in the Philippines is constrained by gaps in digital readiness. Connectivity remains uneven: only around 33% of Filipino households have access to fixed internet, with rural and geographically isolated areas most affected. Addressing the connectivity divide is a priority to ensure that AI tools for public service delivery including digital payments, telemedicine, and education are made accessible to the most vulnerable communities. Moreover, the education system and workforce training programs must evolve to equip the workforce with the competencies needed for future industries .National initiatives such as the DICT’s Digital Jobs PH and partnerships with private sector skilling programs must be scaled up, with stronger alignment to future AI needs like data science, machine learning, and cybersecurity. MSMEs, which represents 99% of Philippine businesses, also require targeted support to adopt AI tools for productivity and competitiveness, as they often lack the capital and technical expertise.
3. Foundational policies must be strengthened to support AI governance
Before AI governance can be meaningfully discussed, it is essential to ensure that the broader digital ecosystem is supported by updated and responsive policies. With the advent of AI, it is worth examining whether these laws require revision to address emerging risks and realities. For example, the Data Privacy Act and the Cybercrime Prevention Act were enacted in 2012. Moreover, the Philippines still lacks a comprehensive cybersecurity law that would establish clear standards for public and private entities in protecting networks, data and systems.
That said, recent policy innovations signal progress. In 2023, the Internet Transactions Act was passed to protect consumers in the e-commerce space, while the Anti-Financial Account Scamming Act was introduced in 2024 to mitigate risks linked to emerging technologies. Earlier in 2025, the Konektadong Pinoy Act was also enacted to enhance competition, expand data access and promote an open access model for data transmission. These developments are critical steps in ensuring that foundational policies are in place. They help create the regulatory environment necessary for AI governance to take root on a solid and responsive foundation.
4. Secure data sharing and effective data governance are essential for developing trustworthy, locally relevant AI solutions.
Building effective AI systems depends above all on the availability of reliable, secure and high-quality data. Without robust data governance, efforts to establish AI governance risk being premature and ineffective. In the Philippines, data fragmentation poses a major challenge. Government agencies often operate in silos, and structured data-sharing arrangements with the private sector are limited. This restricts access to representative, high-quality datasets and undermines the development of locally relevant tools.
To overcome these bottlenecks, robust data-sharing frameworks must be established as a foundation for AI innovation. Alongside this, whole-of-government digitisation should continue, including the conversion of legacy records into digital form, to ensure that AI solutions reflect real conditions on the ground.
Strengthening data security is equally critical. With growing risks of cyberattacks and breaches affecting both government and private sector systems, policies that protect critical information infrastructure are essential. For example, personally identifiable information including health records and the national ID database should be safeguarded with utmost priority. Building this trust and resilience in data governance is not optional but a prerequisite for meaningful and sustainable AI governance for public service delivery.
