Amid the Philippines’ digitalization push, artificial intelligence (AI) readiness has yet to take hold at the local level, with local government units (LGUs) showing limited preparedness for adoption, according to state-run policy think tank Philippine Institute for Development Studies (PIDS).

In a Dec. 23 discussion paper titled “How Ready Are LGUs for AI Adoption?” researchers from PIDS highlighted that the AI Readiness Index shows LGUs have low to moderate preparedness for AI adoption, with scores around 30 to 35 out of a possible 100, reflecting constraints in infrastructure, skills, institutions, and funding.

The report, authored by Francis Mark A. Quimba, Christopher Ed C. Caboverde, and Alliah Mae C. Salazar, noted that LGUs struggle to balance the delivery of essential public services—which provide immediate political benefits—with the longer-term challenge of implementing AI for local governance.

Key bottlenecks to AI adoption identified by PIDS include a shortage of information and communications technology (ICT) and AI-related skills, weak last-mile internet connectivity, and limited funding for digital initiatives.

Income level is also a major factor in AI readiness, PIDS noted, with first-class LGUs scoring higher. However, strong leadership and policy focus allow some lower-income LGUs to outperform wealthier counterparts.

The report also highlighted regional inequalities in AI readiness. While National Capital Region (NCR) posts the highest readiness, regions such as Bangsamoro Autonomous Region in Muslim Mindanao (BARMM), Eastern Visayas, Cordillera Administrative Region (CAR), and Mindoro, Marinduque, Romblon, and Palawan (MIMAROPA) lag significantly. PIDS warned that without targeted interventions, these gaps could deepen existing regional inequalities, leaving peripheral areas further behind.

To address these challenges, PIDS called for coordinated, multi-level efforts that align infrastructure investment, skills development, governance reforms, and funding allocation.

PIDS urged the removal of regulatory barriers to infrastructure deployment. It recommended eliminating legislative franchise requirements for connectivity service providers, data centers, and cloud service providers to lower entry barriers, boost competition, and attract private investment.

The think tank emphasized integrating AI and data literacy into education curricula. Building on the Philippine Digital Workforce Competitiveness Act under Republic Act (RA) No. 11927, PIDS urged the inclusion of AI concepts, critical thinking, numeracy, and problem-solving skills in K-12 education starting in 2026.

It also called for establishing a unified national AI strategy with clear institutional leadership. This includes formalizing a comprehensive plan through an executive order (EO), designating a lead agency to oversee implementation, and building on existing efforts by the Department of Information and Communications Technology (DICT), the Department of Trade and Industry (DTI), and the Department of Science and Technology (DOST), while incorporating input from multiple stakeholders.

PIDS stressed the importance of clarifying agency roles—the DOST for AI research, the Department of Health (DOH) for healthcare AI safety, and the Department of Education (DepEd) for AI literacy—while allowing sectors flexibility to address their unique risks and opportunities.

The think tank also proposed mandating a minimum ICT budget allocation with enforcement measures, requiring all LGUs to dedicate at least two percent of their total budget to ICT by 2026, rising to three percent by 2028, through ring-fenced funding to support digital and AI adoption.

It further called for establishing a comprehensive national data governance framework under the Philippine Statistics Authority (PSA), supported by the Department of Budget and Management (DBM), National Privacy Commission (NPC), and the DICT, to set standards for data generation, collection, storage, processing, and sharing across public and private sectors.

PIDS recommended creating a national LGU AI Readiness Fund with an equity-based allocation, providing grants for AI infrastructure, systems, and capacity building, with a funding formula that prioritizes lower-income municipalities.

Finally, PIDS urged promoting inter-LGU collaboration and resource-sharing, encouraging the formation of LGU clusters or provincial-municipal partnerships for shared AI infrastructure and services, and providing additional funding incentives for such cooperative arrangements.

The think tank also stressed the need for sustainable AI adoption by measuring energy use and carbon emissions, ensuring equity and inclusion so AI does not widen inequalities, and establishing a monitoring and evaluation (M&E) framework to track AI readiness over time.