AI-Powered Service Quality Management for Next-Generation Industrial IoT in Indonesia

This study explores the integration of AI-powered service quality management in next-generation Industrial Internet of Things (IIoT) environments in Indonesia using a qualitative research approach. Drawing insights from five informants across diverse industries, the study investigates perceptions, challenges, organizational readiness, and the impact of AI technologies. Findings reveal that AI significantly enhances service quality through real-time monitoring, predictive analytics, and automation, leading to improved operational efficiency and customer satisfaction. However, challenges such as inadequate infrastructure, skill gaps, and data privacy concerns hinder widespread adoption, especially for small and medium enterprises (SMEs). The study emphasizes the importance of digital infrastructure development, workforce upskilling, and robust data security frameworks to fully realize the benefits of AI in IIoT environments. These findings contribute valuable insights for policymakers, industry practitioners, and researchers, providing a foundation for addressing contextual challenges and optimizing AI-driven service quality management in Indonesia.

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Publication Details

Journal
West Science Nature and Technology
Published
2025-03-28
DOI
https://doi.org/10.58812/j0q44416
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Service Quality Management for Next-Generation Industrial IoT in Indonesia

Mohammad Gifari Sono, Jadiaman Parhusip, Loso Judijanto
West Science Nature and Technology
IoT and Edge/Fog Computing
article

AI-Powered Service Quality Management for Next-Generation Industrial IoT in Indonesia

Mohammad Gifari Sono, Jadiaman Parhusip, Loso Judijanto
article en

Abstract

This study explores the integration of AI-powered service quality management in next-generation Industrial Internet of Things (IIoT) environments in Indonesia using a qualitative research approach. Drawing insights from five informants across diverse industries, the study investigates perceptions, challenges, organizational readiness, and the impact of AI technologies. Findings reveal that AI significantly enhances service quality through real-time monitoring, predictive analytics, and automation, leading to improved operational efficiency and customer satisfaction. However, challenges such as inadequate infrastructure, skill gaps, and data privacy concerns hinder widespread adoption, especially for small and medium enterprises (SMEs). The study emphasizes the importance of digital infrastructure development, workforce upskilling, and robust data security frameworks to fully realize the benefits of AI in IIoT environments. These findings contribute valuable insights for policymakers, industry practitioners, and researchers, providing a foundation for addressing contextual challenges and optimizing AI-driven service quality management in Indonesia.

West Science Nature and TechnologyVol. 3(01)
University of Palangka Raya (ID), Universitas Muhammadiyah Luwuk Banggai (ID)
Openalex Percentile: Top 93%
IoT and Edge/Fog Computing
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