Strategies for developing artificial intelligence utilization competencies of local government personnel in Mueang District, Maha Sarakham Province

Ntapat Worapongpat

ผู้แต่ง

Ntapat Worapongpat Eastern Institute of Technology Suvarnabhumi (EIT)

คำสำคัญ:

artificial intelligence, utilization competencies, local government personnel, digital governance, skill development, public administration, digital era

บทคัดย่อ

This study aimed to: (1) examine the level of artificial intelligence (AI) utilization competencies among local government personnel in Mueang District, Maha Sarakham Province; (2) analyze personal and organizational factors influencing such competencies; and (3) develop evidence-based recommendations for enhancing AI utilization in the local government context. A quantitative research design was employed. A total of 300 respondents were selected from a population of 1,311 local government personnel using stratified random sampling. Data were collected באמצעות a structured questionnaire with established reliability and validity, and analyzed using descriptive and inferential statistical techniques. The findings revealed that the overall level of AI utilization competencies was relatively high (mean = 4.11). Among the dimensions, personal attributes received the highest ratings. Personal factors specifically age and years of service had a statistically significant influence on AI competencies, whereas gender, educational background, job position, and prior training experience showed no significant differences. Organizational factors, including organizational structure, strategic orientation, and work systems, were also found to have a strong and significant effect. Despite the overall high competency level, variations across competency dimensions and personnel groups suggest the need for targeted development interventions. Based on the empirical findings, the study proposes eight practical recommendations to support AI competency development. These recommendations focus on enhancing applied AI skills, strengthening foundational digital knowledge, aligning organizational systems, improving collaborative processes, promoting data analytics capabilities, establishing continuous assessment mechanisms, encouraging appropriate AI adoption in public service delivery, and designing targeted training programs for specific personnel groups. The study contributes to the understanding of AI capacity development in local government settings and offers practical implications for improving administrative efficiency and supporting digital governance. However, the findings should be interpreted within the contextual limitations of the study area, which may affect their generalizability.

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