• Annoo
• Saurabh Chaturvedi

Artificial Intelligence (AI) has emerged as a transformative technology across multiple engineering disciplines, driving innovation in design, optimization, predictive maintenance, simulation, materials discovery, and education. This paper presents a comprehensive review of recent advancements in AI applications in engineering, highlighting practical implementations in power electronics, digital twins, process systems, and materials engineering. We also analyze the role of generative AI, reinforcement learning, and explainable AI in addressing complex engineering problems. Finally, challenges such as trustworthiness, ethical concerns, data scarcity, and integration with legacy systems are discussed, along with potential research directions.

Artificial Intelligence, Engineering Applications, Digital Twin, Reinforcement Learning, Generative AI, Predictive Maintenance, Materials Discovery

"Artificial Intelligence Applications in Engineering: Trends, Opportunities, and Challenges", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 10, page no.c295-c296, October-2025, Available :http://www.jetir.org/papers/JETIR2510242.pdf

"Artificial Intelligence Applications in Engineering: Trends, Opportunities, and Challenges", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 10, page no. ppc295-c296, October-2025, Available at : http://www.jetir.org/papers/JETIR2510242.pdf