A Multilayer Cloud–AI Framework for Intelligent Process Automation in Salesforce-Centric Digital Enterprises
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I3P112Keywords:
Cloud Computing, Artificial Intelligence, Intelligent Process Automation, Salesforce Ecosystem, Enterprise Automation, Machine Learning, Workflow OrchestrationAbstract
The rapid digital transformation of enterprises has significantly increased the demand for intelligent automation systems capable of managing complex customer relationship management (CRM) processes and large-scale enterprise data. Cloud-based CRM applications like Salesforce offer scaled-out infrastructure on which business operations can be run but, conventional workflow automation on these applications is usually based on fixed rule-of-thumb mechanisms, which are not adaptable and predictive. In order to overcome these shortcomings, the current paper offers a multilayer Cloud-AI framework that will facilitate intelligent process automation of Salesforce-oriented digital companies. The suggested architecture combines the cloud computing infrastructure, artificial intelligence services, and enterprise workflow orchestration mechanisms in order to facilitate scalable and data-driven automation. The architecture is divided into several functional layers, one of which is the data acquisition and integration layer, cloud data management layer, AI and analytics layer, automation and workflow orchestration layer, and Salesforce application layer. All these layers allow processing real-time data, predictive analytics, and automated decision-making in all business processes. Analytics of enterprise data, the creation of actionable insights, and automation of CRM activities lead management, customer service operation, and sales forecasting are all achieved using machine learning models and natural language processing techniques. In addition, the framework uses Salesforce APIs, microservices based on the cloud, and scalable data pipelines to facilitate smooth interoperability between cloud services and enterprise systems. Experimental analysis indicates that there are better process automation performance, operational performance, and system scalability. The suggested architecture offers a solid platform upon which the development of intelligent automation strategies can be adopted to facilitate the digital change and data-driven decision-making in contemporary enterprise settings.
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