This special issue focuses on the application of advanced artificial intelligence methods—including deep learning, transformer models, and large language models—to forecasting problems across finance, accounting, management, and economics. The issue seeks to explore how these AI techniques can improve forecast accuracy and support decision-making while examining their theoretical foundations and practical implications.
The issue welcomes interdisciplinary research addressing both technical and ethical dimensions of AI forecasting, including fairness, reproducibility, interpretability, and regulatory considerations. Contributions comparing AI approaches with traditional econometric methods, developing hybrid strategies, or investigating how human judgment interacts with algorithmic predictions are particularly encouraged.