THE TRANSFORMATIVE IMPACT OF INTEGRATED DATA MANAGEMENT AND AI SOLUTIONS: A CROSS-INDUSTRY ANALYSIS OF SALESFORCE PLATFORMS
Keywords:
Integrated Data Management, Artificial Intelligence In Business, Cross-Industry Digital Transformation, Precision Agriculture, Healthcare Data AnalyticsAbstract
This article presents a comprehensive cross-industry analysis of the transformative impact of integrated data management and AI solutions, focusing on the implementation of Salesforce Data Cloud and Agent Force in the healthcare, retail, and agricultural sectors. Through a rigorous methodology combining case studies, stakeholder interviews, and quantitative analysis, the research explores the unique challenges and opportunities faced by each industry in adopting these technologies. The article reveals significant improvements in operational efficiency, customer experience, and data-driven decision-making across all sectors. Key findings include the creation of unified patient profiles in healthcare, enhanced omnichannel integration in retail, and the advancement of precision farming techniques in agriculture. The article also highlights common benefits such as improved scalability, increased stakeholder engagement, and optimized resource allocation. Looking ahead, the article discusses emerging technological trends and potential integration opportunities with technologies like edge computing, blockchain, and extended reality. This comprehensive article analysis provides valuable insights for organizations considering the adoption of integrated data management and AI solutions, while also identifying areas for future research and development in this rapidly evolving field.
References
Grand View Research. (2022). “Big Data Market Size, Share & Trends Analysis Report By Product, By Technology (Analytics, Database, Visualization, Distribution Tools, Others), By Service, By End-use, By Region, And Segment Forecasts, 2024 - 2030”. [Online] Available: https://www.grandviewresearch.com/industry-analysis/big-data-industry
Gartner. (2023). “Forecast Analysis: Artificial Intelligence Software, Worldwide”. [Online] Available: https://www.gartner.com/en/documents/4007140
Yin, R. K. (2021). “Case Study Research and Applications: Design and Methods”. SAGE Publications, Inc. [Online] Available: https://us.sagepub.com/en-us/nam/case-study-research-and-applications/book250150
Davenport, T., & Kalakota, R. (2019). “The potential for artificial intelligence in healthcare”. Future Healthcare Journal, 6(2), 94-98. [Online] Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181/
Grewal, D., Roggeveen, A. L., & Nordfält, J. (2017). “The Future of Retailing”. Journal of Retailing, 93(1), 1-6. [Online] Available: https://www.sciencedirect.com/science/article/pii/S0022435916300872
Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). “Machine Learning in Agriculture: A Review”. Sensors, 18(8), 2674. [Online] Available: https://www.mdpi.com/1424-8220/18/8/2674
Bohr, A., & Memarzadeh, K. (2020). “The rise of artificial intelligence in healthcare applications”. Artificial Intelligence in Healthcare, 25. [Online] Available: https://doi.org/10.1016/B978-0-12-818438-7.00002-2
Bradlow, E. T., Gangwar, M., Kopalle, P., & Voleti, S. (2017). “The Role of Big Data and Predictive Analytics in Retailing”. Journal of Retailing, 93(1), 79-95. [Online] Available: https://www.sciencedirect.com/science/article/abs/pii/S0022435916300835
Vinuesa, R., Azizpour, H., Leite, I. et al. (2020). “The role of artificial intelligence in achieving the Sustainable Development Goals”. Nature Communications, 11, 233. [Online] Available: https://www.nature.com/articles/s41467-019-14108-y
Published
Issue
Section
License
Copyright (c) 2025 ShivaKrishna Deepak Veeravalli (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
