A Quantitative Evaluation of Public–School Teachers’ Satisfaction with the Integration of Artificial Intelligence in Teacher Workload Management

The integration of artificial intelligence (AI) in education has emerged as a promising approach for supporting teachers in managing instructional and non-instructional responsibilities more efficiently. Public-school teachers commonly engage in lesson planning, grading, administrative documentation, and instructional material preparation, which may limit opportunities for instructional innovation and affect professional well-being. This study quantitatively examined public-school teachers’ satisfaction with AI-assisted workload management, focusing on their demographic profiles, levels of AI utilization, satisfaction across professional task domains, and the relationship between AI utilization and perceived satisfaction. A descriptive–correlational research design was employed involving 100 public-school teachers from public schools in the Philippines, selected through simple random sampling. Data were gathered using a structured survey questionnaire grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The instrument measured AI utilization and satisfaction in lesson planning, grading, administrative documentation, and instructional material preparation. Data were analyzed using SPSS, applying descriptive statistics, weighted mean scores, Pearson correlation analysis, and one-way ANOVA, with the level of significance set at p < 0.05. Results showed high levels of AI utilization, particularly in lesson planning (M = 4.1) and instructional material preparation (M = 3.9), alongside high overall teacher satisfaction (M = 4.0). A significant positive relationship was found between AI utilization and teacher satisfaction (r = 0.62, p = 0.001), indicating that greater engagement with AI tools is associated with higher perceived satisfaction. ANOVA results revealed that years of teaching experience, subject specialization, and familiarity with AI were significantly related to satisfaction levels, while age and gender showed no significant differences. The findings suggest that AI-assisted tools are associated with improved workload management and enhanced professional well-being among public-school teachers. These results highlight the importance of institutional support, accessible AI technologies, and targeted professional development initiatives to maximize the potential benefits of AI integration in educational practice.