Authors: Jessica Allen, Nicole Green, Eric Campbell, Justin Perez, Chaitanya Srinivas, Sai Nishil
Abstract: Large Language Models (LLMs) are revolutionizing Customer Relationship Management (CRM) by enabling intelligent, context-aware, and human-like conversational interactions within enterprise platforms such as Salesforce. This research investigates the integration of LLM-driven conversational experiences into Salesforce environments to enhance customer engagement, streamline service operations, and support data-driven decision-making. By leveraging advanced natural language processing, generative AI, and real-time CRM data, conversational systems can provide personalized customer support, automate routine inquiries, assist sales and marketing teams, and improve overall customer experience. The study examines the architectural framework, implementation methodologies, and business value associated with embedding LLM capabilities into Salesforce applications. It also explores critical challenges including data privacy, security, regulatory compliance, model governance, scalability, and responsible AI deployment. Through an analysis of current enterprise practices and emerging technological trends, the research highlights how LLM-powered conversational interfaces improve operational efficiency, increase employee productivity, enhance customer satisfaction, and enable intelligent relationship management. The findings demonstrate that the adoption of generative AI within Salesforce represents a significant step toward next-generation CRM systems that deliver personalized, proactive, and highly responsive customer interactions while supporting organizational growth and digital transformation initiatives.
DOI: http://doi.org/10.5281/zenodo.21187231
