Abstract
As Thailand navigates the challenges of the digital economy, higher education institutions are increasingly compelled to undertake systemic transformation to prepare graduates for employment in AI-integrated environments. This study proposes an AI-driven institutional transformation model specifically tailored to the context of Thai universities. The study was conducted with three main objectives: (1) to synthesize the core components of the model, (2) to develop and validate the proposed model, and (3) to assess its applicability level. A mixed-methods research design was employed to ensure both conceptual rigor and contextual relevance. The research procedure comprised three phases: (1) model synthesis, (2) model development and validation, and (3) model evaluation. The findings revealed that the 3D-POD Model integrates three dimensions: 1) Strategic domains—People, Pedagogy, Process, Platform, and Pathway; 2) Operational phases—Origin, Operation, Output, Outcome, and Optimization; and 3) Digital maturity—Digital Passive, Digitization, Digitalization, Digital Transition, and Digital Transformation. Collectively, these dimensions form a structured matrix (5 Strategic × 5 Operational × 5 Maturity Levels) that provides a practical lens for diagnosing, developing, and enhancing AI-driven transformation in higher education. Quantitative validation confirmed the model’s high content validity and practical applicability. The 3D-POD Model offers a strategic pathway for AI-driven institutional transformation and enhanced graduate employability in Thailand. The model may also serve as a reference for future digital intervention initiatives led by key stakeholders.
Keywords
- AI
- Generative AI
- Data-Driven Decision Making
- Digital Intervention
- Digital Leadership
- Higher Education
- Graduate Employability
Sararuch, S., Buabangplu, P., Nittayathammakul, V., Wannapiroon, P., and Nilsook, P. (2025) The 3D-POD Model for AI-Driven Institutional Transformation and Graduate Employment Readiness in Thailand in Digital Era. Lecture Notes in Computer Science Conference Paper2025.
https://doi.org/10.1007/978-981-96-8430-4_3