• Vybhav Reddy Kammireddy Changalreddy
• Anand Singh

The integration of Generative Artificial Intelligence (GenAI) in customer relationship management (CRM) systems offers transformative potential for enhancing customer understanding and improving decision-making processes. By leveraging GenAI, businesses can gain deeper insights into customer behaviors, preferences, and interactions, enabling more personalized and data-driven strategies. This paper explores how GenAI can be applied to augment CRM systems, focusing on its ability to analyze vast datasets and generate contextually relevant recommendations that are tailored to individual customers. Furthermore, the study delves into the role of GenAI in decision explanation, emphasizing its capacity to offer transparent, interpretable, and coherent rationales behind automated recommendations. This capability is crucial in fostering customer trust, as it bridges the gap between machine-driven decisions and human understanding. By integrating GenAI with CRM platforms, organizations can create more effective customer engagement strategies that are not only efficient but also empathetic to the needs of each customer. The paper highlights real-world use cases where GenAI-powered CRM systems have been implemented to deliver better customer service, predict future behaviors, and enhance product recommendations. Additionally, challenges such as data privacy concerns, model bias, and the need for continuous model training are discussed, providing a comprehensive view of the opportunities and obstacles associated with integrating GenAI in CRM. The research concludes by outlining the future potential of GenAI to revolutionize customer-centric decision-making and create a more intuitive, responsive, and transparent CRM ecosystem.

Generative Artificial Intelligence, Customer Relationship Management, Personalized Recommendations, Decision Explanation, Customer Insights, Data-Driven Strategies, Transparent Decision-Making, CRM Systems, Machine Learning, Customer Engagement, Predictive Analytics, Model Interpretability, AI-driven Recommendations, Customer Trust, Data Privacy.

"Integration of GenAI for Enhanced Customer Understanding and Decision Explanation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 1, page no.h443-h464, January-2025, Available :http://www.jetir.org/papers/JETIR2501742.pdf

"Integration of GenAI for Enhanced Customer Understanding and Decision Explanation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 1, page no. pph443-h464, January-2025, Available at : http://www.jetir.org/papers/JETIR2501742.pdf