Generative AI and Large Language Models: Applications, Opportunities, and Ethical Concerns

Abstract

AI, particularly generative Artificial Intelligence (AI) or large language models (LLMs), has quickly become a game-changer that has significant implications for industry, academia, and society. This paper offers an overview of how far LLM development has progressed to date, covering their architecture, training methods, and implementation in various fields such as healthcare, education, software development, law, and creative industries. We systematically consider the opportunities offered by these models (such as better HCI, task automation, knowledge democratisation among others), as well as other critical ethical concerns (hallucination, amplification of bias, misinformation production, privacy breaches, environmental issues etc.). We present here structured taxonomies of LLM applications and ethical issues, illustrated with comparative benchmarking data based on a survey of more than 200 recent publications (2018 – 2025). Our analysis pointed to three main points: First, LLMs present unparalleled opportunities for human capability enhancement but come with significant responsibility that involves effective governance mechanisms. Second, the deployment of LLMs entails technical safeguards like retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF). And third, the successful deployment of LLMs depends on interdisciplinary collaboration. Finally, a research agenda is provided recognizing priority areas in advancing capability and safety of generative AI systems.