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Generative AI: Transforming the Landscape of Creativity and Automation
Open accessAbstract
Generative AI represents a transformative paradigm in artificial intelligence, enabling machines to autonomously create text, images, music, and other forms of content with remarkable fidelity.Unlike traditional AI systems designed to analyze or predict, generative AI systems focus on the synthesis of novel data that mimics human creativity.This technology is powered by advanced deep learning architectures such as Generative Adversarial Networks (GANs), transformers, and diffusion models.Applications of generative AI extend across numerous industries, including entertainment, healthcare, education, and finance, where it is redefining workflows and enhancing productivity.Furthermore, generative AI has the potential to address complex challenges in fields like drug discovery and personalized education.However, alongside its promises, it also raises significant ethical and societal concerns, such as bias, misinformation, and intellectual property disputes.This manuscript delves into the foundational principles of generative AI, its leading models, its profound applications, and the associated ethical and technical challenges.Through detailed diagrams and tables, this work aims to provide a comprehensive overview of generative AI and its transformative potential for the future.
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“The dynamic development of generative artificial intelligence (GenAI) has significantly transformed the labor market in recent years, particularly in sectors heavily reliant on knowledge and creativity [1, 2].”
From The Entry of Autistic University Graduates into the Labor Market in the Era of Generative AI: Their Concerns and Strategies Regarding the Technology. Research in Progress: The Entry of Autistic Graduates into the Labor Market in the Era of GenAI (2026) · cites this paper as [2]
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“This technology works very well as a support for creative work [13, 2].”
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Research works printed but not linked: 18
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Cited by
Sorted by citations
Matulewski, J., Sikorski, Ł., & Baczała, D. (2026) · Proceedings of the 63rd ACM Conference on Computers and People Research · doi:10.1145/3768310.3807803
Metadata
- Authors
- Pandy, G., Pugazhenthi, V. J., & Murugan, A.
- Venue
- International Journal of Computer Applications
- Publisher
- Foundation of Computer Science
- Published
- 2025-01-31
- Volume
- 186
- Issue
- 63
- Pages
- 7-13
- ISSN
- 0975-8887 (ISSN-L)
- OpenAlex
- W4407142762
- Cited by
- 18
- References
- 0
- Citations by year
- 2026: 6 · 2025: 12
- FWCI
- 5.45
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- International Journal of Computer Applications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, creativity, automation, generative adversarial networks, transformer models, diffusion models, content creation, drug discovery, personalized education, ethical considerations, bias, misinformation, intellectual property
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