AI-Driven Operational Excellence as a Catalyst for Sustainable Development in the Digital Economy

Description

Artificial intelligence (AI) has transformed the way businesses operate and formulate strategies across various sectors. AI is no longer merely a tool for simplifying processes, but has become a major driving force for continuous digital sustainability and development. This study aims to examine the role of AI-driven operational excellence in achieving sustainable digital transformation through a systematic literature review methodology. The reviewed studies encompass literature on artificial intelligence, operational excellence, sustainability, Industry 4.0, Industry 5.0, dynamic capabilities, and socio-technical systems. The analysis reveals that the implementation of AI can enhance operational efficiency, supply chain resilience, organizational adaptability, and innovation capability through intelligent automation, predictive analytics, and real-time operational monitoring. AI also contributes significantly to sustainability performance by optimizing energy consumption, reducing waste, improving resource efficiency, and supporting the circular economy. This study concludes that the successful implementation of AI depends on technological readiness, organizational culture, human resource competencies, and organizational agility in adapting to digital transformation. The findings emphasize that the integration of AI and operational excellence is essential for the sustainability and competitiveness of modern organizations.

Steps to reproduce

This dataset was developed using a Systematic Literature Review (SLR) approach to examine the role of AI-driven operational excellence in supporting sustainable digital transformation. The review process followed the PRISMA framework to ensure a structured identification, screening, eligibility assessment, and selection of relevant studies. Relevant articles were collected from several academic databases, including Scopus, ScienceDirect, Emerald Insight, Google Scholar, and IEEE Xplore. The search process used keywords such as “artificial intelligence,” “operational excellence,” “digital transformation,” “sustainability,” “Industry 4.0,” “Industry 5.0,” “dynamic capabilities,” and “socio-technical systems.” The inclusion criteria focused on peer-reviewed journal articles published between 2018 and 2026 that discuss artificial intelligence implementation, operational excellence, sustainability performance, supply chain resilience, and digital transformation. The selected studies were analyzed using thematic synthesis to identify major themes, including operational efficiency, intelligent automation, organizational adaptability, sustainability integration, and socio-technical transformation. The final dataset contains selected studies with extracted information related to authors, research objectives, methodologies, key findings, countries, and journal sources associated with AI-driven operational excellence and sustainable digital transformation.

Institutions

• Binus University

  Jakarta, Jakarta
• Tun Hussein Onn University of Malaysia

  Johor, Batu Pahat

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