TBC News

Non-traditional, working, and remote students face the highest risk of falling behind as Philippine education shifts from basic technology adoption to institutional enablement, according to a study released by Instructure and local research firm The Fourth Wall.

Titled The Great Divide of AI in Lifelong Learning, the research shows that the country’s emerging AI divide is no longer defined by simple access to technology. Instead, the gap is widening between learners who receive structured institutional backing and those left to navigate AI independently.

Unveiled at CanvasCon Philippines 2026 at Conrad Manila before over 500 educators, the survey gathered insights from 207 education practitioners across higher education and technical-vocational institutions in Metro Manila, Metro Cebu, and Metro Davao.

The Support Divide for Working and Remote Learners

Educators expressed low confidence that working, part-time, and remote students will receive equal support during the AI transition, rating institutional readiness for these groups at just 2.66 on a 5-point scale.

While AI promises greater academic flexibility, the learners who need it most encounter significant structural hurdles. Practitioners identified primary barriers to lifelong learning, including:

• Work and livelihood responsibilities (67%)
• Cost constraints (65%)

The study warns that AI could either alleviate or worsen these friction points depending on whether institutional backing evolves alongside the technology.

“AI adoption is already underway, but institutionalization has yet to catch up. Encouragement isn’t the same as structure, clarity, and guidance. If AI isn’t connected to a coherent learning strategy, both learners and educators will be left floundering, creating a clear divide between supported and unsupported learners,” said Darren Read, Managing Director, APAC at Instructure.

Institutions also struggle to measure whether AI tools are reaching students equitably, with educators scoring institutional tracking of resource distribution at 2.74 out of 5.

“Equity is not only an access problem; it is also a measurement problem. Institutions cannot meaningfully address an AI divide if they cannot see who has access, who is participating, and who is actually benefiting,” said John Brylle L. Bae, Research Director at The Fourth Wall.

Adoption Outpaces Strategy and Training

AI deployment is accelerating beyond the initial exploration phase in Philippine higher education. Current deployment metrics across surveyed institutions show:

• 50% offer AI literacy or digital-skills programs for students
• 41% deploy staff-facing AI systems for teaching and course design
• 40% integrate AI tools directly into course delivery
• 38% utilize AI-powered tutoring assistants

Only 18% of institutions report remaining in the exploration phase without a formal strategy.

However, organizational strategy and staff preparation lag behind tool integration. Confidence in having a clear AI strategy within lifelong-learning pathways scored 3.08 out of 5, while confidence in faculty and staff training reached only 2.87 out of 5.

Key operational barriers reported by respondents include limited access to devices or paid tools (43%) and a lack of formal training and guidance (38%).

Regional Hurdles and Regulatory Pressures

Resource bottlenecks vary across major urban hubs:

• Metro Manila: Technology and digital infrastructure stand out as the top bottleneck (46%).
• Metro Cebu: Funding constraints (45%) and faculty training (36%) represent primary concerns.
• Metro Davao: Funding constraints serve as the leading barrier (55%).

To address these regional and institutional gaps, the report outlines five priority areas: expanding physical access to devices and tools, establishing rules for ethical use, building faculty and learner capabilities, integrating AI into lifelong learning curricula, and tracking equity metrics.

These implementation gaps come into focus following new Commission on Higher Education (CHED) guidelines for responsible AI usage. The national policy mandates transparency in student AI use and requires human oversight in key areas such as grading, admissions, scholarships, student progression, and faculty evaluation.

The study reflects the perceptions of education practitioners across Metro Manila, Metro Cebu, and Metro Davao to provide an indicative overview of institutional readiness and priorities.