Navigating the Future: Exploring the Strategic Integration of Artificial Intelligence in Contemporary Management Practices

Dixit, Anuranjita

Assistant Professor, Shri Jai Narain Mishra PG College, Lucknow

Abstract

In today’s rapidly evolving business landscape, artificial intelligence (AI) has emerged as a transformative force, reshaping traditional management practices across industries. This research paper delves into the strategic integration of AI in contemporary management, aiming to provide insights into the challenges, opportunities, and implications faced by organizations navigating this transformative journey. Through a comprehensive analysis of case studies, industry trends, and expert opinions, this study explores the ways in which AI is influencing decision-making, efficiency, innovation, and sustainability within organizations. Furthermore, it examines the ethical considerations and change management strategies required to ensure responsible and effective AI adoption. The findings of this research offer a roadmap for organizations seeking to harness the potential of AI while addressing the complexities of its integration into management practices.

Keywords: Artificial Intelligence (AI), Management Practices, Strategic Integration, Decision Making, Efficiency.

Impact Statement

Artificial intelligence refers to a type of programming that powers most of the “smart” technologies with which people tend to interact today. Standard computer programs are built around set rules, filters and exceptions that allow them to appear intelligent. But none of these programs rely on true intelligence; each of them is just following the rules. In contrast, artificial intelligence enables computer systems to crunch large sets of data and gives them the ability to learn and change their own behavior based on past experience. Because of its reliance on large sets of data, artificial intelligence is especially useful for pattern-recognition tasks like categorization and prediction. The implications of artificial intelligence are broad. Perhaps you’ve heard of the concepts of “neural networks” and “deep learning,” which are algorithms created to mimic the responses of neurons in the human brain. So, in the same way that the human brain is made up of about 100 billion neuron “switches” that fire in response to certain stimuli, data scientists create synthetic neurons in computer code that respond likewise, creating visual recognition systems that mimic the way human beings actually use their sense of vision to navigate the world of objects.

About Author

Dr. Anuranjita Dixit      

Gold Medalist in BBA & MBA  

Area of Competence: International Business (International Marketing, International Logistic, Export Import Policies and Procedure, Origination Behaviour, Production Management, Entrepreneurship)

• Personality Development/ Interview preparation Coach

• Active Participant in various Export promotion councils Seminar and webinar (National and International)

• Research Paper / Research Article Publish in various National Journal 

• Presented Research Paper in various National and International Conferences/ seminars 

Book Published Export Import Management (Polices and Procedure/ Marketing of Services /INTERNATIONA TARDE (STRATEGY, THEORY AND PRACTICES) Courses Content for MIBM GLOBAL: – Pioneers and Leaders in Online Management Education

Awardee of Narisashaktikaran award of Women Empowerment and Entrepreneur Development.

References

1. Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review, 95(1), 20–30.

2. Chui, M., Manyika, J., & Mehdi, M. (2016). Where machines could replace humans—And where they can’t (yet). The McKinsey Quarterly. https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet.

3. Singh, V. P., & Ram, S. (2024). Impact of artificial intelligence on teacher education. Shodh Sari-An International Multidisciplinary Journal, 03(1), 243–266. https://doi.org/10.59231/SARI7669

4. Chaudhary, S. (2024). Artificial intelligence and its impact on economic growth. Shodh Sari-An International Multidisciplinary Journal, 03(1), 356–368. https://doi.org/10.59231/SARI7676

5. Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P., & Marrs, A. (2017). Artificial intelligence: The next digital frontier? https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/artificial-intelligence-the-next-digital-frontier. McKinsey Global Institute.

6. Maji, M. (2024). Role of artificial intelligence in education. Edumania-An International Multidisciplinary Journal, 02(1), 33–38. https://doi.org/10.59231/edumania/9016

7. Teece, D. J. (2018). Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world. Research Policy, 47(8), 1367–1387. https://doi.org/10.1016/j.respol.2017.01.015

8. Boudreau, K. J., & Lakhani, K. R. (2018). Using the crowd as an innovation partner. Harvard Business Review, 96(4), 60–69.

9. Agarwal, R. (2023). Use of technology by higher education students. Shodh Sari-An International Multidisciplinary Journal, 02(4), 152–161. https://doi.org/10.59231/SARI7631

10. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2019). The ethics of algorithms: Mapping the debate. Big Data and Society, 6(2), 205395171667967.

11. Ferreira, A., Trkman, P., & van Aken, J. E. (2020). Design thinking in innovation: Mapping the literature through a bibliometric analysis. European Journal of Innovation Management, 23(1), 18–54.