Impact of AI on Enterprise Cloud-Based Integrations and Automation
DOI:
https://doi.org/10.32628/CSEIT241061180Keywords:
Enterprise AI Integration, Cloud Automation, AI Infrastructure, Business Performance Optimization, Digital Transformation ChallengesAbstract
Artificial Intelligence has transformed enterprise cloud-based integrations and automation, revolutionizing how businesses manage data, workflows, and applications across distributed environments. This comprehensive article explores the impact of AI on enterprise systems, examining key areas, including intelligent data integration, automated workflow optimization, and enhanced security measures. The article delves into technical implementation considerations, discussing infrastructure requirements and integration architectures while highlighting the substantial business benefits in operational efficiency, cost optimization, and strategic advantages. Additionally, it addresses the critical challenges organizations face in technical and organizational dimensions when implementing AI solutions, providing insights into successful adoption strategies and future considerations for enterprise AI integration.
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References
McKinsey & Company, "The state of AI in early 2024: Gen AI adoption spikes and starts to generate value," May 30, 2024. [Online]. Available: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
Asin Tavakoli, Holger Harreis, Kayvaun Rowshankish, and Michael Bogobowicz, "Charting a path to the data- and AI-driven enterprise of 2030," McKinsey Digital, September 5, 2024. [Online]. Available: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/charting-a-path-to-the-data-and-ai-driven-enterprise-of-2030
Rakibul Hasan Chowdhury, "AI-driven business analytics for operational efficiency," World Journal of Advanced Engineering Technology and Sciences, 2024, 12(02), 535–543. [Online]. Available: https://wjaets.com/sites/default/files/WJAETS-2024-0329.pdf
Ravi Kumar, Neha Thakur, Ahmad Saeed, Chandra Jaiswal, "Enhancing Data Analytics Using AI-Driven Approaches in Cloud Computing Environments," Software Engineering, Oct. 14, 2024. [Online]. Available: http://article.sapub.org/10.5923.j.se.20241102.01.html
Lauren McMillan, Liz Varga, "A review of the use of artificial intelligence methods in infrastructure systems," Engineering Applications of Artificial Intelligence, Volume 116, November 2022, 105472. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0952197622004626
Deborah Theseira, "Understanding Integration Architecture: A Comprehensive Guide," Ardoq, 9 Sep 2024. [Online]. Available: https://www.ardoq.com/knowledge-hub/integration-architecture
Teradata, "Maximize the business value of enterprise AI." [Online]. Available: https://www.teradata.com/insights/ai-and-machine-learning/maximize-the-business-value-of-enterprise-ai
Amit Hiremath, "AI Integration for Business Growth: Costs, Benefits, and ROI," Clarion Technologies. [Online]. Available: https://www.clariontech.com/blog/ai-integration-for-business-growth
Kanerika, "Enterprise Artificial Intelligence: The Ultimate Guide to Scaling," October 30, 2023. [Online]. Available: https://kanerika.com/blogs/enterprise-artificial-intelligence/
Psico, "The Impact of AI on Organizational Performance Measurement Tools," August 28, 2024. [Online]. Available: https://psico-smart.com/en/blogs/blog-the-impact-of-ai-on-organizational-performance-measurement-tools-170847
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