Transforming Customer Relationship Management with Distributed Quantum Computing Opportunities and Challenges

This paper explores the potential of distributed quantum computing (DQC) to transform customer relationship management (CRM) systems in the education sector. This study looks at how distributed quantum computing (DQC) could change customer relationship management (CRM) systems in education. It examines current research, suggests new ideas, and compares different ways to put these ideas into practice, presenting a mixed model that uses Quantum as a Service (QaaS) to add quantum features to regular CRM systems in a flexible way. The mixed model combines quantum algorithms with traditional data processing to improve the system’s performance. The mixed model combines quantum algorithms with classical data processing workflows to enhance overall system performance. The results demonstrate that DQC significantly improves analytical accuracy, data security, and system adaptability through the application of algorithms such as Grover’s search, quantum key distribution (QKD), and the quantum approximate optimization algorithm (QAOA). The proposed solution addresses critical requirements, including dynamic personalization, real-time data processing, and advanced data protection. Despite technological barriers, such as limited quantum hardware access and the need for specialized expertise, the analysis confirms a strong alignment between the operational needs of academic institutions and the functionalities offered by quantum resources. Practical guidelines for pilot implementation are outlined, and the paper discusses future prospects for developing next-generation intelligent learning platforms supported by distributed quantum infrastructures.