Authors :
K. Ragavi
Volume/Issue :
ICMST-2025
Google Scholar :
https://tinyurl.com/5x7x7xcn
Scribd :
https://tinyurl.com/53z3yyxf
DOI :
https://doi.org/10.38124/ijisrt/25nov747
Abstract :
Artificial Intelligence (AI) has emerged as a transformative force across industries, research, and society, enabling
systems that can perceive, learn, reason, and act autonomously. Over the past decade, AI has transitioned from narrow,
rule-based systems to general-purpose models capable of understanding natural language, vision, and multimodal inputs.
This paper provides a comprehensive study of the advancements in artificial intelligence, focusing on major trends, emerging
technologies, challenges, and future directions. It explores breakthroughs in deep learning, reinforcement learning,
generative modeling, and AI-driven automation, along with challenges such as bias, explainability, ethical dilemmas, and
sustainability. The study emphasizes the need for transparent, reliable, and human-aligned AI systems. Finally, the paper
outlines future research pathways including neurosymbolic reasoning, edge intelligence, green AI, and global governance
frameworks for safe and responsible deployment.
Keywords :
Artificial Intelligence, Deep Learning, Generative AI, Trends, Challenges, Future Directions, Ethics, Responsible AI.
Artificial Intelligence (AI) has emerged as a transformative force across industries, research, and society, enabling
systems that can perceive, learn, reason, and act autonomously. Over the past decade, AI has transitioned from narrow,
rule-based systems to general-purpose models capable of understanding natural language, vision, and multimodal inputs.
This paper provides a comprehensive study of the advancements in artificial intelligence, focusing on major trends, emerging
technologies, challenges, and future directions. It explores breakthroughs in deep learning, reinforcement learning,
generative modeling, and AI-driven automation, along with challenges such as bias, explainability, ethical dilemmas, and
sustainability. The study emphasizes the need for transparent, reliable, and human-aligned AI systems. Finally, the paper
outlines future research pathways including neurosymbolic reasoning, edge intelligence, green AI, and global governance
frameworks for safe and responsible deployment.
Keywords :
Artificial Intelligence, Deep Learning, Generative AI, Trends, Challenges, Future Directions, Ethics, Responsible AI.
