Leveraging artificial intelligence for competitive advantage: a case study of Samsung
DOI:
https://doi.org/10.34140/bjbv6n4-064Palavras-chave:
artificial intelligence, competitive advantage, SamsungResumo
The author examines how it is possible to use artificial intelligence to the advantage of an organization that operates in the technology industry. The main focus of the research was to identify how effectively and in what ways Samsung used AI technologies in its smart phones and home appliance product segments to improve functionality and usability as well as operational effectiveness. This was to have been achieved through the use of Artificial Intelligence in manufacturing processes as well as in various ways to deliver unique customized services to customer unlike the rival companies. This work also shows how Bixby, Samsung’s own AI assistant or smart IoT solutions all help towards creating a smarter environment, thereby building goodwill for the brand and generating additional revenue streams. The study further shows how Samsung supports that the application of AI can enhance a firm’s competitive position by pushing product differentiation, monitoring and anticipating equipment wear and tear and making better decisions from analyzed data.
Referências
Acemoglu, D., & Restrepo, P. (2017). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 125(6), 2188-2244.
- Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Harvard Business Review Press.
- Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.
- Davenport, T., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.
- Jurafsky, D., & Martin, J. H. (2009). Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition. Pearson Education.
- Kshetri, N. (2020). Artificial intelligence in supply chain management: A systematic literature review, synthesis, and research agenda. International Journal of Production Research, 58(7), 2220-2241.
- Mitchell, T. M. (1997). Machine learning. McGraw-hill.
- Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. Free Press.
- Porter, M. E. (2008). The five competitive forces that shape strategy. Harvard Business Review, 86(1), 78-93.
- Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited.
- Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into business transformation. Harvard Business Review Press
- Samsung. (2021). Samsung AI. Retrieved from https://www.samsung.com/global/ai/
- IDC. (2021). Worldwide Artificial Intelligence Spending Guide. Retrieved from https://www.idc.com/getdoc.jsp?containerId=prUS48127321
- Samsung. (2021). Samsung AI. Retrieved from https://www.samsung.com/global/ai/
- Kim, S., & Park, H. (2021). AI-driven supply chain management: A comprehensive review. Journal of Business Logistics, 42(2), 123-145.
- Lee, J. (2022). The role of AI in smart manufacturing. Journal of Intelligent Manufacturing, 33(4), 987-1005.
- Samsung. (2023). Galaxy S23 Ultra features. Samsung Newsroom. https://news.samsung.com/us/
