Quantum AI agents in smart cities, healthcare, and logistics
Mohammad Shahnawaz Shaikh, Deepak Sharma, Akshay Patidar +3 more
The city, healthcare, and global logistical systems are becoming increasingly complex and data-heavy. The legacy approaches of artificial intelligence can be challenging to scale for large-scale optimization, uncertainty, and real-time decision-making needs. This chapter proposes the quantum AI (QAI) agents, where quantum computing is combined with autonomous agent designs. It describes the basic concepts of quantum information, agent-based decision models, learning in the hybrid quantum–classical approach, and quantum information. The chapter also discusses some of the applications of QAI agents in traffic management, energy grid balancing, precision medicine, automated hospital workflow, supply chain optimization, fleet routing, and autonomous warehouse systems. The mechanisms of optimization, learning, and control are clarified through mathematical formulations and system models. The combination of QAI agents with 6G networks, Edge AI, IoT, and cyber-physical systems is also mentioned to demonstrate the opportunities for real-time deployment. To be responsibly adopted, security concerns, ethical considerations, and quantum-safe systems of governance are evaluated. There is early-stage advancement with emerging prototypes and global initiatives, and the future course of research presents challenges related to scalability, hardware reliability, and algorithmic stability. The chapter contains an organized roadmap for using quantum-enhanced intelligence in next-generation digital infrastructures.
CRC Press eBooks•Oct 21, 2026•0 citations