The Role of AI in Driving Process Optimization Across Industries

Abstract

This study explores the role of Artificial Intelligence (AI) in driving process optimization across industries, focusing on its applications, challenges, and outcomes. A qualitative research design was employed, utilizing semi-structured interviews with 24 participants representing diverse industries, including manufacturing, healthcare, finance, and retail. Participants were recruited using purposive sampling and interviewed online to gather insights into their experiences with AI-driven process optimization. Data were analyzed through qualitative content analysis using NVivo software, with themes and subcategories identified until theoretical saturation was achieved. The study identified six key applications of AI in process optimization: predictive analytics, process automation, real-time monitoring, decision support, customer personalization, and quality assurance. These applications contributed to enhanced efficiency, improved accuracy, scalability, and innovation. However, challenges such as technical limitations, ethical and legal concerns, workforce adaptation, cost constraints, and external factors were also highlighted. Participants emphasized the transformative potential of AI while recognizing barriers to its effective implementation. The findings align with existing literature, demonstrating the critical role of AI in optimizing processes across various contexts. AI is a transformative technology that enhances process optimization across industries by improving operational efficiency, decision-making, and innovation. However, addressing challenges related to data quality, workforce adaptation, and ethical concerns is essential for maximizing its potential. Future research and practice should focus on developing robust frameworks and strategies to overcome these barriers and support sustainable AI integration.