AI-Augmented Decision-Making in Management Using Quantum Networks

Authors

  • Kishore Mullangi Staff Site Reliability Engineer, Visa Inc., Austin, TX, USA
  • Niravkumar Dhameliya Software Engineer, Therapy Brands, Birmingham, AL, USA
  • Sunil Kumar Reddy Anumandla System Analyst, Texas Municipal League Intergovernmental Risk Pool (TMLIRP), Texas, Austin, USA
  • Vamsi Krishna Yarlagadda SAP Architect, Seattle School District, John Stanford Center for Educational Excellence, USA
  • Dipakkumar Kanubhai Sachani Business Analyst, Arth Energy Corporation, Pittsburgh, Pennsylvania, USA
  • Sai Charan Reddy Vennapusa Sr. Functional Analyst, Costco Wholesale, 3905 Dallas Pkwy, Plano, TX 75093, USA
  • Sai Sirisha Maddula Front End Developer, Delta Airlines, Atlanta, Georgia, USA
  • Bhavik Patel ERP Developer, Teleworld Solutions, Chantilly, VA, USA

DOI:

https://doi.org/10.18034/abr.v13i2.718

Keywords:

Quantum Networks, Artificial Intelligence, Augmented Decision-Making, Quantum Computing, Business Intelligence, Strategic Management

Abstract

Combining artificial intelligence (AI) and quantum networks can revolutionize management decision-making. This study delves into the implications of AI-augmented decision-making using quantum networks, focusing on its primary objectives, methodology, significant findings, and policy implications. By thoroughly examining the latest research, analyzing case studies, and exploring future possibilities, this study investigates the potential of combining AI and quantum computing to improve strategic decision-making, streamline operations, and foster innovation in management. The methodology entails thoroughly analyzing existing literature, carefully examining real-world case studies and a forward-looking forecast of future trends in AI-quantum integration. Significant discoveries emphasize the remarkable computational power and efficiency, enhanced decision-making abilities, and the potential for groundbreaking innovation and disruption that AI-augmented decision-making using quantum networks brings. Nevertheless, the study highlights various constraints and policy implications that need to be considered, such as technical hurdles, ethical concerns, and regulatory structures, to guarantee a responsible and ethical implementation. This study enhances our understanding of the potential impact of AI-augmented decision-making in management, particularly when combined with quantum networks. It emphasizes the need for proactive policy measures to ensure that the benefits of this technology are maximized while risks are minimized.

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Published

2023-08-31

How to Cite

Mullangi, K., Dhameliya, N., Anumandla, S. K. R., Yarlagadda, V. K., Sachani, D. K., Vennapusa, S. C. R., Maddula, S. S., & Patel, B. (2023). AI-Augmented Decision-Making in Management Using Quantum Networks. Asian Business Review, 13(2), 73-86. https://doi.org/10.18034/abr.v13i2.718

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