Authors: Professor Nicholas Parker, Assistant Professor Natalie Morris, Associate Professor Chloe Reed, Professor Adam Russell, Chaitanya Srinivas, Sai Nishil
Abstract: Customer Relationship Management (CRM) systems are undergoing significant transformation with the integration of Generative Artificial Intelligence (Generative AI), enabling organizations to deliver more intelligent, personalized, and efficient customer experiences. This research explores the role of Generative AI in transforming CRM workflows and customer interaction by integrating large language models, conversational AI, intelligent automation, and predictive analytics into enterprise CRM platforms. The study examines how AI-powered capabilities such as automated content generation, personalized customer communication, intelligent chatbots, sales assistance, workflow optimization, knowledge management, and real-time decision support improve operational efficiency and strengthen customer engagement across sales, marketing, and customer service functions. It further discusses cloud-native CRM architectures, API-driven integrations, data governance, security, privacy, and ethical AI considerations that support scalable enterprise implementation. The paper also analyzes key challenges associated with adopting Generative AI, including data quality, model transparency, regulatory compliance, organizational readiness, and system interoperability. By leveraging Generative AI within CRM ecosystems, organizations can automate repetitive business processes, enhance customer satisfaction through personalized interactions, accelerate response times, improve employee productivity, and generate actionable business insights for strategic decision-making. The study concludes that Generative AI represents a transformative technology for next-generation CRM systems, enabling intelligent workflow automation, data-driven customer engagement, continuous business innovation, and sustainable competitive advantage in an increasingly digital and customer-centric business environment.
International Journal of Science, Engineering and Technology