Optimizing Business Operations With Quantum AI

CMA Paritosh Basu

Matthias Klusch, Jörg Lässig, Frank K. Wilhelm

Aidin Salamzadeh, Léo‐Paul Dana, Morteza Hadizadeh +1 more

This research integrates quantum-driven artificial intelligence with innovative entrepreneurial strategies to design an adaptive decision-making model for tourism businesses. The model leverages principles of quantum uncertainty and artificial intelligence to address operational complexity and uncertainty, advancing personalized traveler experiences and sustainable tourism entrepreneurship. Through theoretical synthesis and simulations using twelve qubits, the study models key variables—including tourist preferences, real-time conditions, economic and health indices, social media trends, and resource capacities—to optimize tourism management and entrepreneurial decision-making. Results illustrate enhanced adaptability, resilience, and business innovation by supporting entrepreneurial actions such as personalized travel planning, supply chain optimization, crisis response, and business opportunity prediction. The findings propose quantum-AI integration as a disruptive force within tourism entrepreneurship, promoting both sustainable business models and global industry transformation.

Matthias Klusch, Jörg Lässig, Frank K. Wilhelm

Pranali Dhawas, Pranali Faye, Pooja Pimpalshende +3 more

This chapter explores the transformative potential of Quantum Artificial Intelligence (QAI) in driving significant cost savings across various business operations. As organizations face increasing pressure to optimize resources and enhance operational efficiency, traditional computational methods often fall short in addressing complex, large-scale problems. Quantum AI, which synergizes the computational power of quantum computing with advanced machine learning techniques, presents a promising solution. This chapter delves into the theoretical underpinnings of QAI, showcases real-world applications in logistics, supply chain, finance, and manufacturing, and provides a comparative analysis of cost efficiencies achieved through QAI-driven optimizations. Case studies and empirical evidence highlight how QAI not only accelerates decision-making but also minimizes operational redundancies, ultimately leading to substantial financial benefits. The chapter concludes with future directions and challenges in the adoption of QAI technologies in mainstream business practices.