This paper provides an overview of the existing literature on the use of artificial intelligence (AI) in various fields, including economics, finance, mining, manufacturing, and innovation. The paper identifies the drivers and effects of AI deployment in the context of innovation and highlights the challenges and opportunities that arise from the use of AI. The studies reviewed in this paper cover various topics related to forecasting, including the impact of AI on professional skills, hybrid forecasting techniques for predicting commodity prices, and novel deep reinforcement learning algorithms for crude oil price forecasting. The paper’s contribution lies in its systematic and comprehensive approach to reviewing the literature, which allows for a better understanding of the impact of AI on various fields and the identification of strategies to address the challenges that arise from its deployment.
Damasevicius, R. Artificial Intelligence Techniques in Economic Analysis. Economic Analysis Letters, 2023, 2, 25. https://doi.org/10.58567/eal02020007
Damasevicius R. Artificial Intelligence Techniques in Economic Analysis. Economic Analysis Letters; 2023, 2(2):25. https://doi.org/10.58567/eal02020007
Damasevicius, Robertas 2023. "Artificial Intelligence Techniques in Economic Analysis" Economic Analysis Letters 2, no.2: 25. https://doi.org/10.58567/eal02020007
Damasevicius, R. (2023). Artificial Intelligence Techniques in Economic Analysis. Economic Analysis Letters, 2(2), 25. https://doi.org/10.58567/eal02020007
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