Generative AI: Concepts, Challenges, and Research Opportunities

Anh Tran, Ojo Folake, Karthik Srinivasan

Cite: Tran, A.; Folake, O.; Srivasan, K. Generative AI: Concepts, Challenges, and Research Opportunities. JDS, 7(2), (2025). https://doi.org/10.33847/2686-8296.7.2_1

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Abstract. This article examines the landscape of generative artificial intelligence (GenAI), a rapidly evolving segment of technology characterized by its capacity to produce various forms of original content, such as text, images, and music, through deep neural network models. The rising popularity of tools like ChatGPT, which reached over 100 million users within months of its release in November 2022, signifies a paradigm shift in enterprise AI adoption, provoking organizations to realign their strategic objectives with digital transformation. While the immense potential of GenAI promises enhancements in productivity and personalized services across industries, it simultaneously presents critical challenges, including ethical concerns surrounding bias, accountability, and human-centric decision-making. This study highlights the need for effective testing frameworks that ensure GenAI systems enhance, rather than detract from, human cognition. This paper contributes to the discourse on GenAI by outlining its foundational mechanisms, implications for various sectors, and the interplay of opportunities and risks posed by its widespread implementation.
Keywords: Generative AI (GenAI), Foundation Models, Large Language Models (LLMs), Generative Pre-trained Transformers (GPT), Ethics in AI, Explainability and Interpretability. 

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Published online 30.12.2025