Vol: 12, Issue: 1 2022

Page: 288-297

Developing Artificial Intelligence By Exploring The Employability Of Enterprise Business Management Analysis Framework

Amardeep Singh Bhullar

Received Date: 2022-02-20

Accepted Date: 2022-03-24

Published Date: 2022-03-28

http://doi.org/10.37648/ijtbm.v12i01.016

The rapid evolution of Artificial Intelligence (AI) has ushered in a new era in enterprise business management, fundamentally reshaping how organizations operate and compete in the global market. With AI technologies becoming more sophisticated and accessible, enterprises across industries are increasingly leveraging these tools to automate routine tasks, enhance decision-making processes, and boost overall organizational performance. This paradigm shift is not merely about adopting new technology; it represents a strategic transformation that integrates AI into the core of business management functions, driving efficiency, innovation, and agility.

References

• Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Harvard Business Review Press.
• Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., Henke, N., & Trench, M. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey Global Institute.
• Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
• Doshi-Velez, F., & Kim, B. (2017). Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608. https://arxiv.org/abs/170 2.08608
• European Commission. (2019). Ethics guidelines for trustworthy AI. https://ec.europa.eu/futurium/en/aialliance-consultation/guidelines
• Gentsch, P. (2019). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Springer. https://doi.org/10.1007/978- 3-319-89957-2
• Lacity, M., & Willcocks, L. (2016). Robotic process automation and cognitive automation: The next phase. SB Publishing.
• Marinos, L. (2020). Challenges of legacy system integration. Journal of Enterprise Integration, 12(3), 45– 53. https://doi.org/10.1016/j.jei.2020.04.002
• Pyle, D. W. J. (1999). Data preparation for data mining. Morgan Kaufmann.
• Teece, D. J. (2009). Dynamic capabilities and strategic management: Organizing for innovation and growth. Oxford University Press.
• Weske, M. (2019). Business process management: Concepts, languages, architectures (3rd ed.). Springer. https://doi.org/10.1007/978-3-662- 59432-2