Event-Driven AI Architectures for Next-Generation CRM Platforms
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V7I1P108Keywords:
Event-Driven Architecture, Artificial Intelligence, Crm Platforms, Real-Time Analytics, Microservices, Streaming Data, Intelligent Automation, Crm, Customer Relationship Management, AIAbstract
Customer Relationship Management (CRM) platforms are undergoing a significant transformation driven by real-time data demands, artificial intelligence (AI), and the need for highly responsive customer engagement. Traditional CRM systems, which rely heavily on batch processing and synchronous request response models, struggle to meet modern expectations of immediacy, personalization, and scalability. Event-driven architecture (EDA), when combined with AI, provides a robust foundation for building next-generation CRM platforms capable of processing continuous streams of customer interactions in real time. This paper explores the architectural principles, system components, AI integration strategies, and enterprise use cases of event-driven AI architectures in modern CRM ecosystems. It also examines implementation challenges, performance considerations, and future research directions.
References
1. J. Singh, “Event-Driven Architecture for Real-Time Analytics in Cloud CRM Platforms,” European Journal of Computer Science and Information Technology, vol. 13, no. 42, pp. 24–34, Jun. 2025. DOI: https://doi.org/10.37745/ejcsit.2013/vol13n422434.
2. Salesforce, “Event-Driven Architecture (Decision Guide),” Salesforce Architect Developer Guide, 2025. [Online]. Available: https://architect.salesforce.com/decision-guides/event-driven.
3. Microsoft Azure Architecture Center, “Event-Driven Architecture Style,” Microsoft Docs, Aug. 14, 2025. [Online]. Available: https://learn.microsoft.com/azure/architecture/guide/architecture-styles/event-driven.
4. SAP SE, “What Is Event-Driven Architecture (EDA)?,” SAP Official Documentation, 2025. [Online]. Available: https://www.sap.com/products/technology-platform/what-is-event-driven-architecture.html.
5. M. A. Kumar, “AI-Driven CRM: How Salesforce Einstein Is Revolutionizing Customer Relationship Management,” PhilPapers, 2023.
6. S. D. Veeravalli, “Integrating IoT and CRM Data Streams: Utilizing Salesforce Data Cloud for Unified Real-Time Customer Insights,” International Journal of Computer Science (QITP-IJCS), vol. 4, no. 1, pp. 1–16, Nov. 2024. DOI: https://doi.org/10.63374/QITP-IJCS_04_01_001.
7. S. B. Mannapur, “Event-Driven Architectures: A Technical Deep Dive into Scalable AI and Data Workflows,” International Journal of Computer Engineering and Technology (IJCET), vol. 16, no. 1, pp. 316–328, Jan.–Feb. 2025.
8. Dynamics 365 Reference Architectures, Microsoft Docs, 2025. [Online]. Available: https://learn.microsoft.com/dynamics365/guidance/reference-architectures/.
9. M. Fowler, “Event Sourcing,” 2005. (Foundational work on event-driven patterns and EDA principles.)
10. B. Michelson, “Event-Driven Architecture Overview,” Patricia Seybold Group, 2006. (Classic primer on events and streaming.)
11. Confluent, “Scaling AI with Data Streaming and Event-Driven Design,” Confluent Blog, Dec. 23, 2024. [Online]. Available: https://www.confluent.io/blog/generative-ai-meets-data-streaming-part-3/.
12. Fig 4.2 : https://www.aviso.com/blog/real-time-streaming-architecture-for-sales
13. Fig 4.1 : https://seanfalconer.medium.com/the-future-of-ai-agents-is-event-driven-9e25124060d6
