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 *Amogh Kashyap, Research Scholar,  School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India; kashyapamogh10@gmail.com; ORCID: 0009-0000-2394-8046

Abstract

One potent use of artificial intelligence (AI) is deep learning (DL), it is revolutionizing the field of management by providing advanced tools for data analysis, predictive modeling, and automation. This paper investigates the transformative impact of DL on managerial practices, focusing on its applications in decision-making, operational efficiency, and strategic planning. Through a comprehensive analysis of case studies and real-world applications, this research highlights the significant benefits and challenges associated with integrating DL into management workflows.

The study explores how DL can improve decision-making by extracting insightful information from large, complicated data sets. By looking for trends in past data and assessing it, DL models can assist managers in making more informed and accurate decisions. Additionally, DL can optimize operational efficiency by automating repetitive tasks, improving resource allocation, and predicting potential disruptions. Moreover, this research examines the strategic implications of DL, including its potential to create competitive advantages, drive innovation, and foster new business models.

Although deep learning (DL) has a lot of potential, this study also discusses the issues and concerns related to its application. Bias and data privacy are two ethical issues that need to be properly considered. Practical difficulties must also be taken into account, such as the requirement for specific knowledge and computing power. Organizations can decide whether to include DL into their management procedures by knowing the advantages and disadvantages.

To sum up, this study highlights the revolutionary possibilities of deep learning in the field of management. Organizations may boost operational efficiency, gain a competitive edge, and improve decision-making by utilizing its data analysis, predictive modeling, and automation capabilities. For implementation to be successful, however, ethical and practical ramifications must be carefully considered. The impact that DL technology will likely have on management will only grow as it develops further.

Keywords: Deep Learning, Management, Decision-Making, Operational Efficiency, Artificial Intelligence, Predictive Analytics, Automation.

Citation of this paper: Kashyap, A. (2024). Leveraging deep learning in management: enhancing decision-making and operational efficiency. VLEARNY Journal of Business, 1(4), 24–32. https://doi.org/10.5281/zenodo.14268071

VLEARNY Journal of Business
1 (4) 2024, 24-32, https://vlearny.com/journal/ © VLERNY Technology LLP.

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