The Transformative Impact of Generative AI Across Industries: A Comprehensive Systematic Review.
Publication Date: 04/08/2025
Author(s): Stephen W. Bulus, Folasade Y. Ayankoya, Oluwabamise J. Adeniyi.
Volume/Issue: Volume 5, Issue 2 (2025)
Page No: 43-57
Journal: Advanced Journal of Science, Technology and Engineering (AJSTE)
Abstract:
Generative Artificial Intelligence (GAI) has emerged as a transformative technology with profound implications across various industries. This systematic review examines the applications, challenges, and ethical considerations of generative AI technologies across diverse sectors including healthcare, education, business, and creative industries. Following PRISMA guidelines, we analyzed 10 relevant studies published between 2010 and 2025, focusing on the implementation and impact of generative AI models such as ChatGPT, GANs, and Large Language Models (LLMs). Our findings indicate that generative AI is significantly enhancing efficiency, personalization, and innovation across industries, while simultaneously raising concerns regarding data privacy, bias, employment implications, and ethical considerations. In healthcare, GAI is revolutionizing medical diagnostics, personalized treatment plans, and drug discovery. In education, it supports personalized learning experiences and teaching resource development. In business sectors, it transforms customer service, operational workflows, and innovation processes. However, challenges related to bias, privacy, transparency, and technical limitations persist across all domains. This review contributes to the ongoing dialogue on responsible AI deployment and provides valuable insights for researchers, practitioners, and policymakers navigating the evolving landscape of generative AI technologies. The findings underscore the need to balance innovation with ethical considerations and regulatory frameworks to maximize the benefits of generative AI while mitigating potential risks.
Keywords:
Generative Artificial Intelligence (GAI), Large Language Models (LLMs), Healthcare Applications, Educational Technology, Systematic Review, Ethical Implications, Industry Transformation.
