QUANTUM COMPUTING APPLICATIONS AND AI STRATEGIES FOR OPTIMIZING RESOURCES

Abstract

This paper examines the potential of combining quantum computing and artificial intelligence to enhance resource management in various sectors. Quantum computing makes use of concepts such as entanglement and superposition to solve complex problems much faster than traditional approaches, whereas AI employs machine learning and reinforcement learning for predictive analysis and effective resource utilization. The research focus has been on hybrid systems of quantum computing and AI and their applications in the field of energy management, optimization of supply chains, portfolio management in finance, and smart urban development. The challenges include quantum noise, hardware limitation, and algorithm integration; all were described as solutions to scalable quantum hardware, error-tolerant algorithms and AI-assisted quantum error correction. The combination of these technologies can transform the industries by closing the gap of computational one and enhancing efficiency in the operation, creating adaptable and sustainable solutions. The important keywords are Quantum Computing or Artificial Intelligence or Quantum Error Correction or Hybrid Systems or Quantum -AI Integration