Integration of Artificial Intelligence in Social Media Content Production Workflow to Improve Efficiency and Productivity: A Case Study of the Publication Team at SMP Islam Al Azhar 12 Rawamangun - Arrum Dara Efda; Ropik; Izzaty Zephaniah; Feri Johansah (International Journal of Science and Environment (IJSE), 2026)
The integration of Artificial Intelligence (AI) into the social media management of educational institutions has become critical amid limited human resources (HR) and increasingly high content-volume demands. This study aims to analyze the integration of AI into the content production workflow, measure its effectiveness on time efficiency and productivity, identify technical and non-technical obstacles, formulate optimization strategies, and recommend an automation system for the critical New Student Admission (PMB) period. Using a qualitative approach with a case study design at SMP Islam Al Azhar 12 Rawamangun, data were collected through in-depth interviews with five key informants (purposive sampling), participant observation, and documentation study. The results show that a five-member publication team with a multidisciplinary background (Mechanical Engineering Education, Fashion Design Education, Sociology, and Communication Science) manages six digital platforms with a workload of at least 20–25 pieces of content per week. The use of AI tools such as Gemini, ChatGPT, Claude, Canva, CapCut, and Wix Studio has proven to ease workload, accelerate the acquisition of visual assets, and improve the aesthetic quality of content. Nevertheless, conventional time savings remain relatively moderate (15–30 minutes per piece of content) because manual finishing (human-in-the-loop) is still required. The main obstacles encountered include AI daily-quota limitations, content spikes when school activities coincide (content bottlenecks), and the absence of a fully automated workflow system. This study recommends an AI-CRM-based automation architecture to optimize the school's social media performance, particularly during the PMB period.