A Study on Effective Management and Financial Reporting Examines how Artificial Intelligence (AI) Affects Business Subfields

Authors

  • Kunwar Jee Sinha Research Scholar, Department of Management, RKDF University, Ranchi, Jharkhand, India
  • Shweta Sinha Research Scholar, Department of Economics, RKDF University, Ranchi, Jharkhand, India

Abstract

This study examines how artificial intelligence (AI) transforms many business domains, including strategy, operations, finance, and marketing, and evaluates how it affects corporate expansion. The main goal is to uncover the mediating functions of excellent financial reporting and effective business management following AI integration. The research highlights artificial intelligence's dominance in commercial decision-making, crediting it to its ability to handle historical data, manage uncertainty, and provide probabilistic forecasts. In particular, the study explores how Artificial Intelligence approaches might be applied to address various business problems, such as risk assessment, demand forecasting, customer segmentation, and organizational decision-making. In addition, the study looks into the effects of using AI approaches. A sample of secondary sources was used in terms of methodology, and extensive data were collected to examine how AI affected actual business situations. Using interesting case examples, the study's conclusions highlight the important ramifications of AI's rise in real-world commercial settings. In addition to discussing the benefits of using AI instead of more conventional statistical techniques, the article offers suggestions for anyone looking to incorporate AI into their commercial decision-making procedures. The theoretical framework may benefit marketing, operations, and strategy, which provides an overview of AI's involvement in several business subfields. The impact of artificial intelligence (AI) on management practices in many sectors is explained, emphasizing how AI is transforming operational dynamics and decision-making procedures. Managers are empowered to improve processes and strategic planning through data-driven decision-making, made possible by AI's quick gathering, processing, and analysis of enormous datasets. The paper highlights how artificial intelligence (AI) may help predict future trends and assist predictive analytics, which can help managers anticipate market dynamics and allocate resources more efficiently. It also clarifies some uses, including robotic process automation (RPA), which automates monotonous jobs to free up human resources for innovative projects. The paper notes that although AI integration encourages a culture of ongoing development inside businesses, prudent managerial attention is still necessary. A careful analysis of ethical issues, such as algorithmic prejudice and social effects, is essential. As organizations grow, overcoming these obstacles is crucial for the proper application of AI. The insightful information about the complex effects of artificial intelligence on companies, emphasizing effective management and financial reporting, provides a thorough roadmap for companies navigating the AI environment by highlighting the benefits of AI adoption and the moral issues of incorporating AI into management procedures.

References

Ahmed, A., Dabral, S., Bahuguna, D., Kaur, J., & Singh, B. (2023). Artificial Intelligence's Integration in Supply Chain Management: A Comprehensive Review. European Economic Letters, 13(3), 1512-1527. http://eelet.org.uk

Atwani, M., Hlyal, M., & Elalami, J. (2022). A Review of Artificial Intelligence applications in Supply Chain. ITM Web of Conferences, ICEAS'22, 46(003001).

Basha, M. (2023). Impact of artificial intelligence on marketing. East Asian Journal of Multidisciplinary Research (EAJMR), 2(2), 993-1004.

Benartzi, S. (2012). Save More Tomorrow: Practical Behavioral Finance Solutions to Improve 401(k) Plans. Penguin Publishing Group.

Davenport, T. H. (2019). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. Penguin Random House LLC.

Earley, S. (2020). The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. Wonderwell. Ghose, A. (2018). Tap: Unlocking the Mobile Economy. MIT Press.

Hidayah, N., Rahayu, A., Dirgantari, P. D., & Wibowo, L. A. (2023, November). AI-Based Decision-Making on Business Strategy: A Review. International Journal of Social Science Research and Review, 6(11), 26-36. http://dx.doi.org/10.47814/ijssrr.v6i11.1598 Introbooks. (2020). Artificial Intelligence in Banking. Independently Published.

Korb, K. B., & Nicholson, A. E. (2004). Bayesian artificial intelligence. Taylor & Francis. Kotler, P. (2012). Kotler On Marketing. Simon & Schuster UK.

Mariyana, A. L. D., Annaufal, A. I., & Roostika, R. (2024). The Impact of Artificial Intelligence on Small and Medium Enterprises in Yogyakarta. Emerald Publishing Limited. https://doi.org/10.1108/S1479-351220240000036031

Paksoy, T., Kochan, C. G., & Ali, S. S. (Eds.). (2020). Logistics 4.0: Digital Transformation of Supply Chain Management. CRC Press.

Sterne, J. (2017). Artificial Intelligence for Marketing: Practical Applications. Wiley.

Theuermann, K., Holzinger, A., & Chen, F. (2022, August). Effects of Fairness and Explanation on Trust in Ethical AI. ResearchGate, 51-67. DOI:10.1007/978-3-031-14463-9_4 .Understanding the impact of artificial intelligence on skills development. (2021). UNESCO Publishing.

Vaynerchuk, G. (2016). #AskGaryVee: One Entrepreneur's Take on Leadership, Social Media, and Self-Awareness. HarperCollins.

Venkatesan, R., Farris, P. W., & Wilcox, R. T. (2021). Marketing Analytics: Essential Tools for Data-Driven Decisions. University of Virginia Press.

Wamba Taguimdje, S. L., Wamba, S. F., Jean Robert, K. K., & WANKO Tchatchouang, C. E. (2020, March). Influence of Artificial Intelligence (AI) on Firm Performance: The Business Value of AI-based Transformation Projects. Business Process Management Journal.

Published

2024-06-13

Issue

Section

Articles