Abstract
Artificial intelligence is a technology that represents the ability of a computer to perform activities with human-like intelligence that until recently were performed by humans. Artificial intelligence software programs are predicted to surpass human capabilities in the near future. In modern society, this technology finds its useful value in many areas, and there is more and more evidence that it will also improve the prospects of the global economy. Thanks to high-level algorithms, through the process of extraction and analysis, this technology enables the prediction of data, which can help companies make better business decisions. Better and more accurate decisions reduce business risks and costs, shorten time to market, enable optimization of inventory management, predict trends and consumer behavior, i.e. contribute to a comprehensive increase in productivity and business efficiency. These technologies are also applied to predict gross domestic product, unemployment rates, and inflation. They have a role in promoting the demand for intelligent and green products, which contributes to the sustainable development of companies, as well. Artificial intelligence in production processes is mostly used in repetitive tasks, which reduces the need for human labor. Although this technology is still in development, its enormous potential to optimize the industrial structure and increase high-quality economic growth is undeniable. However, in order for its capabilities to be used to the maximum in the global economy, workers will need additional training and retraining due to the new requirements of working in synergy with artificial intelligence.
Publisher
Centre for Evaluation in Education and Science (CEON/CEES)
Reference46 articles.
1. Agrawal, A., Gans, J., & Goldfarb, A. (2018): Prediction machines: The simple economics of artificial intelligence. Harvard Business Press;
2. Alam, H., Ramadoss, T. S. & Ramakrishna, S. (2018): Artificial Intelligence and Internet of Things enabled Circular economy. The International Journal of Engineering and Science (IJES). Vol. 7 (9) Ver.III, p.p. 55-63;
3. Ali, M., Khan, D. M. Alshanbari, H. M. & El-Bagoury, A. A. H. (2023): Prediction of complex stock market data using an improved hybrid emd-lstm model. Applied Sciences (Switzerland), 13, no. 3: 1429;
4. Arrow, K J. (1962): The economic implications of learning by doing [J]. Review of Economic Study, 29(3):155-173;
5. Awan U., Kanwal N., Alawi S., Huiskonen J., Dahanayake A. (2021): Artificial Intelligence for Supply Chain Success in the Era of Data Analytics. In: Hamdan A., Hassanien A.E., Razzaque A., Alareeni B. (eds) The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success. Studies in Computational Intelligence, vol 935. Springer, Cham;
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Students’ Attitudes on The Role of Artificial Intelligence (Ai) In Personalized Learning;International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE);2024-08-31