THE IMPACT OF ARTIFICIAL INTELLIGENCE ON BUSINESS OPERATION: CURRENT STATE, FUTURE OPPORTUNITIES AND CHALLENGES
Keywords:
Artificial Intelligence (AI), Organization Development, Business Performance, Current State, Opportunities And ChallengesAbstract
The purpose of this study is to analyse the current state and future implications of artificial intelligence (AI) technologies in various aspects of business operations. This study investigates the impact of AI on organizational development, exploring its effects on business operations, decision-making, customer experience, and supply chain management. Moreover, AI-driven innovation enables organizations to develop new products, services, and business models, driving growth and competitiveness. These innovations include enhanced decision-making through augmented intelligence, real-time analytics, and hyper-personalization of customer experiences. Advanced automation will lead to more autonomous operations and the integration of AI with Internet of Things (IoT) devices. Additionally, AI-driven innovation in product development, smart services, and cyber security will offer businesses new avenues for growth and competitive advantage. This literature review aims to provide a comprehensive understanding of how AI influences different aspects of business operations and the current state and opportunities it presents. The paper concludes that embracing AI and investing in its development will be crucial for businesses aiming to thrive in an increasingly digital and data-driven world. Companies that leverage AI effectively will be better positioned to enhance efficiency, drive innovation, and achieve sustainable growth in the evolving market landscape.
References
Deloitte (2020) “Thriving in the era of pervasive AI: Deloitte’s state of AI in the enterprise, 3rd edition,” https://www2.deloitte.com/us/en/insights/focus/cognitive-technologies/state-of-ai-and-intelligent-automation-in-business-survey.html
Barton, D., & Court, D. (2021). How AI is transforming the retail industry. McKinsey Quarterly.
Brynjolfsson, E., & McElheran, K. (2016). Data-Driven Decision Making: The Role of Big Data and AI in Business Performance. MIT Sloan Management Review.
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior.
Choi, T.-M., Wallace, S. W., & Wang, Y. (2021). Big Data Analytics in Operations Management. Springer.
Chui, M., Manyika, J., & Miremadi, M. (2018). The AI frontier: The AI-powered business. McKinsey & Company.
Huang, G. Q., & Rust, R. T. (2021). Robotic Process Automation: Implications for Service Operations. Journal of Service Research.
Luo, X., Zhang, J., & Duan, L. (2023). Chatbots in Customer Service: Enhancing Customer Experience with AI. Journal of Service Research.
Pereira, J., Silva, C., & Oliveira, J. (2022). Logistics Optimization through AI: A Review. Transportation Research Part E.
Zeng, M., Li, J., & Zhang, H. (2021). Data Privacy in AI Applications. IEEE Transactions on Knowledge and Data Engineering.
Barocas, S., Hardt, M., & Narayanan, A. (2019). Fairness and Machine Learning. Fairness and Machine Learning.
Barton, D., & Court, D. (2021). How AI is transforming the retail industry. McKinsey Quarterly.
Brown, T., Mann, B., Ryder, N., et al. (2020). Language Models are Few-Shot Learners. arXiv preprint.
Brynjolfsson, E., & McElheran, K. (2016). Data-Driven Decision Making: The Role of Big Data and AI in Business Performance. MIT Sloan Management Review.
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior.
Choi, T.-M., Wallace, S. W., & Wang, Y. (2021). Big Data Analytics in Operations Management. Springer.
Chui, M., Manyika, J., & Miremadi, M. (2018). The AI frontier: The AI-powered business. McKinsey & Company.
Dastin, J. (2020). AI in Recruitment: Revolutionizing Talent Acquisition. Reuters.
Grewal, D., Roggeveen, A. L., & Nordfält, J. (2022). The Role of AI in Personalization of Marketing. Journal of Marketing.
Hess, T., Matt, C., & Benlian, A. (2016). Digital Transformation: Challenges and Opportunities. Business & Information Systems Engineering.
Huang, G. Q., & Rust, R. T. (2021). Robotic Process Automation: Implications for Service Operations. Journal of Service Research.
Huang, Y., Zhang, X., & Jin, H. (2022). AI in Cyber security: Advances and Challenges. IEEE Access.
Kerr, J., & Ding, D. (2020). Real-Time Data Processing and Decision-Making. Information Systems Journal.
Luo, X., Zhang, J., & Duan, L. (2023). Chatbots in Customer Service: Enhancing Customer Experience with AI. Journal of Service Research.
Miller, K. (2022). AI Talent Shortage: Addressing the Skills Gap. Harvard Business Review.
Davenport, T. H. (2018). The AI advantage: How to put the artificial intelligence revolution to work. MIT Press.
Pereira, J., Silva, C., & Oliveira, J. (2022). Logistics Optimization through AI: A Review. Transportation Research Part E.
Soni, P., Singh, R., & Garg, H. (2021). AI and IoT Integration: Opportunities and Challenges. IEEE Internet of Things Journal.
Zeng, M., Li, J., & Zhang, H. (2021). Data Privacy in AI Applications. IEEE Transactions on Knowledge and Data Engineering.
Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review, 95(1), 59-66.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
Chui, M., Manyika, J., & Miremadi, M. (2016). Where machines could replace humans—and where they can't (yet). McKinsey Quarterly. Retrieved
Westerman, G., Bonnet, D., & McAfee, A. (2014). The nine elements of digital transformation. MIT Sloan Management Review, 55(3), 1-8.
Lee, J., Kim, M., & Kang, J. (2019). The impact of artificial intelligence on business performance: Evidence from a large-scale survey. Journal of Management Information Systems, 36(4), 1174-1204.
Accenture. (2017). Artificial intelligence is the future of growth. Retrieved from https://www.accenture.com/us-en/insight-artificial-intelligence future-growth
World Economic Forum. (2018). The impact of artificial intelligence on the future of work. Retrieved from http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf
Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.
Davenport, T. H., & Harris, J. (2017). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.
Gartner. (2021). Predicts 2021: Artificial Intelligence and Its Impact on People and Society. Gartner Research.
Brynjolfsson, E., & McAfee, A. (2017). The Business of Artificial Intelligence. Harvard Business Review.
Smith,J.(2018).The Role of Emotional Intelligence in Leadership Effectiveness Journal of Organizational Behaviour, 39(2),245-259.doi:10.1002/job.2301
Hongo, J. (16 April 2015). Robotic Customer Service? In This Japanese Store, That’s the Point. The Wall Street Journal News Paper, Japan Real Time. http://blogs.wsj.com/japanrealtime/2015/04/16/toshiba-humanoid-robot-to-debut-in-tokyo-departmentstore/? Mod=WSJAsia_hpp_LEFTTopStories
Keller, G. (1 March 1983). Academic Strategy: The Management Revolution in American Higher Education. The John Hopkins University Press, Education - 211 pages.
Rich, E. (1985). Artificial intelligence and the humanities. Computers and the Humanities, 19(2), 117-122.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Ataullah Siddiqui (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
