Author
Abstract
This comprehensive article investigates the transformative impact of AI-enhanced SAP S/4HANA Finance across healthcare, manufacturing, scientific research, auto, food & Oil &Gas sectors, focusing on human-AI collaboration patterns and implementation outcomes. Through a mixed-methods approach analyzing 15 organizations over 18 months, the research examines how AI integration transforms traditional ERP functionalities into intelligent financial management systems. The article collected data from 450 end-users and 45 key stakeholders, employing both quantitative metrics and qualitative assessments to evaluate implementation patterns, challenges, and success factors. The findings reveal significant improvements across all sectors: healthcare organizations achieved 40% reduction in billing processing time and 15% improvement in collection rates; manufacturing entities realized 35% reduction in unplanned downtime and 22% decrease in working capital requirements; while research institutions demonstrated 45% faster grant processing and 35% improved budget forecasting accuracy. The article introduces the Adaptive Financial Intelligence Framework (AFIF) for conceptualizing human-AI collaboration in financial management, contributing to both theoretical understanding and practical implementation strategies. The article concludes that successful AI integration depends on industry-specific adaptations, comprehensive training programs, and robust governance frameworks while highlighting the critical role of human expertise in maximizing system benefits. These findings provide valuable insights for organizations pursuing AI-enhanced financial management solutions while offering a roadmap for future developments in human-AI collaboration within enterprise systems.
Suggested Citation
Poornachandar Pokala, 2024.
"Artificial Intelligence in SAP S/4HANA: Transforming Enterprise Resource Planning through Intelligent Automation,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(6), pages 191-201, November.
Handle:
RePEc:jbh:ijsrcs:v10:y2024:i6:id:408
DOI: 10.32628/CSEIT24106169
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24106169
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