Artificial Intelligence-Based Teacher Workforce Planning to Address the Shortage of Educators in Indonesia’s 3T Regions: A Systematic Review - Syafa'at Ariful Huda Huda; Jaenudin Jaenudin; Alexius Dwi Widiatna; Cynthia Mayang Sari; Fawzul Arifin (S&Co Publishing, 2026)
Teacher shortages and unequal educator distribution remain major challenges in Indonesia’s disadvantaged, frontier, and outermost (3T) regions. Conventional teacher workforce planning, which relies on administrative reporting, has been unable to provide accurate and responsive information to address dynamic educational needs. This study analyses the role of artificial intelligence (AI) in supporting teacher workforce planning and educational governance in 3T regions. A Systematic Literature Review (SLR) based on the PRISMA 2020 guidelines was conducted. A total of 180 articles published between 2023 and 2025 were identified through Google Scholar and educational publications. After a systematic screening process, 9 articles met the inclusion criteria and were analyzed using thematic analyses supported by NVivo 15. The findings indicate that predictive analytics and intelligent governance systems significantly improve the accuracy of teacher workforce mapping, educational data integration, and policy responsiveness in 3T regions. AI also promotes data-driven educational governance, although its implementation faces challenges, including digital inequality, infrastructure limitations, algorithmic dependency, and ethical concerns. This study confirms that AI is not only a learning technology but also a strategic instrument for strengthening teacher workforce planning and achieving more adaptive, equitable, and sustainable education in Indonesia’s 3T regions.