TIM-7074 v1

Dwivedi, Y. K., Sharma, A., Rana, N. P., Giannakis, M., Goel, P., & Dutot, V. (2023). Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions. Technological Forecasting and Social Change, 192, 122579. https://doi.org/10.1016/j.techfore.2023.122579

• This study analyzes the evolution of AI research using structural topic modeling to identify key themes and trends, highlighting the growing influence of AI across business, society, and environmental domain.

How, M.-L., & Cheah, S.-M. (2024). Forging the Future: Strategic Approaches to Quantum AI Integration for Industry Transformation. AI, 5 (1), 290-323. https://doi.org/10.3390/ai5010015

• This article highlights how the integration of quantum computing and artificial intelligence is set to transform Industry 4.0, emphasizing the need for proactive change management, strategic foresight, and interdisciplinary collaboration to navigate its complex opportunities and challenges.

Rashid, A. B., & Kausik, M. A. K. (2024). AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications. Hybrid Advances, 7, 100277. https://doi.org/10.1016/j.hybadv.2024.100277

• This comprehensive review examines how artificial intelligence is transforming a wide range of industries globally, while also addressing the technologies, future trends, and ethical and policy implications involved in its implementation.

Shirole, V., Shahade, A. K., & Deshmukh, P. V. (2025). A comprehensive review on data-driven driver behaviour scoring in vehicles: technologies, challenges and future directions. Discover Artificial Intelligence, 5 (26). https://doi.org/10.1007/s44163-025-00244-6

• This article reviews how emerging AI technologies, including generative AI and predictive analytics, are transforming driver behavior analysis and vehicle performance in the automotive industry while addressing privacy, monitoring, and integration challenges.