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The research investigates the effects of AI-driven process automation on efficiency and cost-effectiveness within the manufacturing business administration field 1. The potential of AI to improve operations and utilize resources is examined using both qualitative interviews and quantitative surveys. Previous research demonstrates the positive impact of AI on process efficiency and cost reduction in various industries. There search focus narrows down to the manufacturing sector 1, with a case study showcasing the effectiveness of AI- powered predictive maintenance in reducing downtime 1-5. The research also acknowledges the lack of exploration in ethical considerations and challenges specific to this sector. The qualitative analysis, utilizing thematic coding, provides detailed insights into the specific context, which complements the quantitative findings 1-5. These quantitative results, presented through descriptive and inferential statistics, demonstrate the operational efficiency improvements and cost reductions achieved through AI driven processes in manufacturing businesses 5. The research emphasizes the interdisciplinary importance of AI driven automation and its implications for manufacturing business administration 1-5, while also promoting a comprehensive understanding of its impact.
Deepak Gavade (Tue,) studied this question.