AI readiness gaps in LGUs risk more inequalities, PIDS warns
Artificial intelligence (AI) adoption may widen long-standing development gaps among Philippine local governments, as capacities to implement the technology vary across regions, a state-run think tank said.
A study by the Philippine Institute for Development Studies (PIDS) showed that AI readiness among local government units (LGUs) reflects existing disparities in infrastructure, skills, and governance capacity.
“Regional and Island-group patterns reveal persistent inequalities that align with broader development disparities,” PIDS said. “Without deliberate interventions, AI readiness gaps may reinforce existing regional inequalities, as better-resourced areas advance while peripheral regions fall further behind.”
The National Capital Region (NCR) topped AI readiness with an index above 60, supported by its advanced digital infrastructure, skilled workforce, concentration of national government offices, and strong presence in tech-driven service sectors.
It was followed by the Calabarzon region, which scored 42.
In contrast, the Bangsamoro Autonomous Region of Muslim Mindanao (BARMM), Eastern Visayas, Cordillera Administrative Region (CAR), and MIMAROPA all scored below 30.
Potential not the issue
The index measured AI readiness across six pillars: innovation, economic foundations, data readiness, governance, skills, and infrastructure.
According to PIDS, most LGUs scored highest in innovation, which averaged 40.6, but lagged in other areas.
“These results indicate that the principal bottlenecks to AI readiness lie not in the absence of innovation potential, but in institutional and human capital constraints,” the study noted.
Other gaps identified include network infrastructure, resource constraints, weak governance in medium-term planning, and limited information and communications technology (ICT) budget allocation.
Across all regions, less than 1 percent of LGU budgets is allocated to ICT network infrastructure.
“The universal nature of these gaps implies systematic infrastructure challenges requiring national-level policy interventions,” PIDS added.
On the income side, PIDS noted that financial resources are not the only critical factor in AI readiness.
The think tank noted that some lower-income LGUs have outperformed wealthier counterparts through stronger leadership, clear policy prioritization, and strategic capacity.
“This suggests that non-income factors such as leadership, policy prioritization, and strategic capacity can partially compensate for fiscal constraints, though economic limitations remain a fundamental barrier for most lower-income municipalities,” PIDS said.
“Nevertheless, the overall pattern emphasizes the need for targeted fiscal and capacity-building support for lower-income LGUs to prevent AI readiness gaps from reinforcing existing regional and socioeconomic inequalities,” it added.
Zooming out, Philippine LGUs generally lag in preparedness for AI adoption, with overall scores ranging only from 30 to 35 out of 100.
“This observation reflects not just the absence of capability but also a complex interplay of infrastructural, human capital, institutional, and economic constraints that systematically limit readiness across multiple dimensions,” PIDS said.
At the national level, the Philippines recently ranked 49th out of 195 countries in the Government AI Readiness Index by Oxford Insights, scoring 57.76, which is above the regional average of 49.11 and the global average of 41.4.
Despite this relatively strong national ranking, the country scored low in AI infrastructure and development.
