Industry Perspectives on Electrical Competencies and Artificial Intelligence Readiness for Workforce Development in the Zamboanga Peninsula, Philippines

Authors

  • Erwin F. Delos Reyes College of Engineering and Technology, Zamboanga Peninsula Polytechnic State University, Zamboanga City 7000, Philippines

DOI:

https://doi.org/10.70917/ijcisim-2026-3368

Keywords:

electrical competencies, artificial intelligence readiness, workforce development, Industry 4.0, engineering education

Abstract

The rapid advancement of Industry 4.0 has increased the demand for electrical professionals who possess both strong technical competencies and artificial intelligence (AI) readiness. This study explored industry perspectives on the electrical competencies and AI readiness required for workforce development in the Zamboanga Peninsula, Philippines. A qualitative descriptive research design was employed involving purposively selected industry stakeholders from the electrical, manufacturing, energy, utilities, and industrial sectors. Data were collected through semi-structured interviews and analyzed using reflexive thematic analysis. Six themes emerged: Technical Competence, Professional Attributes, AI Transformation, Digital Readiness, Curriculum Enhancement, and Industry Collaboration. The findings revealed that industries continue to prioritize strong engineering fundamentals while increasingly expecting graduates to develop AI literacy, digital competencies, analytical skills, and adaptability to meet evolving workforce demands. Participants likewise emphasized the importance of curriculum modernization and stronger industry-academe partnerships to ensure workforce readiness. The study underscores the need for competency-based engineering education that aligns with Industry 4.0 and emerging AI technologies.

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Published

2026-07-18

How to Cite

Erwin F. Delos Reyes. (2026). Industry Perspectives on Electrical Competencies and Artificial Intelligence Readiness for Workforce Development in the Zamboanga Peninsula, Philippines. International Journal of Computer Information Systems and Industrial Management Applications, 18(8s), 1168–1175. https://doi.org/10.70917/ijcisim-2026-3368

Issue

Section

Original Articles