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Cross-Industry Applications of AI-Enhanced Business Process Optimization: A Comparative Study of AI-Enabled Process Redesign Across Retail, Social Media, and Consumer Electronics

Rui Zhao, Orufa Sindy Ipalimo

Abstract

This study examines the implementation and impact of artificial intelligence (AI) technologies in business process optimization across three distinct industries: retail, social media, and consumer electronics. Through a comprehensive comparative analysis, we investigate how AI tools including chatbots, automation pipelines, and triage dashboards enhance operational efficiency, scalability, and cost reduction. Our research employs a mixed-methods approach, combining quantitative performance metrics with qualitative stakeholder interviews across 45 organizations. Results demonstrate significant improvements in process efficiency (32-48% reduction in processing time), cost savings (15-35% operational cost reduction), and customer satisfaction scores (18-42% improvement) across all three industries. The study reveals that while AI implementation strategies vary by industry context, common success factors include executive support, employee training, and phased deployment approaches. These findings contribute to the growing body of knowledge on AI-driven business transformation and provide practical frameworks for organizations seeking to optimize their processes through intelligent automation.

Keywords

Artificial IntelligenceBusiness Process OptimizationAutomationChatbotsDigital TransformationCross-Industry AnalysisOperational Efficiency

References

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