A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions

<p dir="ltr">Generative Artificial Intelligence (Gen-AI) is a new advancement that has revolutionized the concepts of Natural Language Processing (NLP) and Large Language Model (LLM). This change impacts various aspects of life, stimulating industry, education, and healthcare progres...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Mueen Uddin (4903510) (author)
مؤلفون آخرون: Shams Ul Arfeen (17541462) (author), Fuhid Alanazi (22466728) (author), Saddam Hussain (3144783) (author), Tehseen Mazhar (19332663) (author), Md. Arafatur Rahman (22996318) (author)
منشور في: 2025
الموضوعات:
الوسوم: إضافة وسم
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author Mueen Uddin (4903510)
author2 Shams Ul Arfeen (17541462)
Fuhid Alanazi (22466728)
Saddam Hussain (3144783)
Tehseen Mazhar (19332663)
Md. Arafatur Rahman (22996318)
author2_role author
author
author
author
author
author_facet Mueen Uddin (4903510)
Shams Ul Arfeen (17541462)
Fuhid Alanazi (22466728)
Saddam Hussain (3144783)
Tehseen Mazhar (19332663)
Md. Arafatur Rahman (22996318)
author_role author
dc.creator.none.fl_str_mv Mueen Uddin (4903510)
Shams Ul Arfeen (17541462)
Fuhid Alanazi (22466728)
Saddam Hussain (3144783)
Tehseen Mazhar (19332663)
Md. Arafatur Rahman (22996318)
dc.date.none.fl_str_mv 2025-09-08T03:00:00Z
dc.identifier.none.fl_str_mv 10.1007/s11831-025-10355-z
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/A_Critical_Analysis_of_Generative_AI_Challenges_Opportunities_and_Future_Research_Directions/31289251
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Human society
Policy and administration
Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Generative artificial intelligence
Chat-GPT AND GANs
Transformer models
Autoregressive models of Gen-AI architectures
Variational autoencoders (VAEs)
Misinformation and deepfake
Applications of Gen-AI
dc.title.none.fl_str_mv A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Generative Artificial Intelligence (Gen-AI) is a new advancement that has revolutionized the concepts of Natural Language Processing (NLP) and Large Language Model (LLM). This change impacts various aspects of life, stimulating industry, education, and healthcare progression. This survey presents the potential applications of Gen-AI across various sectors, highlighting the risks and opportunities. Some of the most pressing challenges include ethical consideration, the rise of disinformation (including deepfakes), concerns over Intellectual Property (IP) rights, cybersecurity risks, bias and discrimination. The survey also covers the fundamental models of Gen-AI, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers. These frameworks are extremely important in various sectors, including medical imaging, drug discovery, and personalized medicine, and offer valuable insights into the future of technological advancements in the scientific community. The study contributes substantially by exploring positive elements and addressing the challenges of adequately deploying Gen-AI models. Using these insights, we hope to provide a comprehensive knowledge of the potential challenges and complexities associated with the widespread implementation of artificial intelligence technologies.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Archives of Computational Methods in Engineering<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s11831-025-10355-z" target="_blank">https://dx.doi.org/10.1007/s11831-025-10355-z</a></p>
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identifier_str_mv 10.1007/s11831-025-10355-z
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/31289251
publishDate 2025
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spelling A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research DirectionsMueen Uddin (4903510)Shams Ul Arfeen (17541462)Fuhid Alanazi (22466728)Saddam Hussain (3144783)Tehseen Mazhar (19332663)Md. Arafatur Rahman (22996318)Human societyPolicy and administrationInformation and computing sciencesArtificial intelligenceCybersecurity and privacyGenerative artificial intelligenceChat-GPT AND GANsTransformer modelsAutoregressive models of Gen-AI architecturesVariational autoencoders (VAEs)Misinformation and deepfakeApplications of Gen-AI<p dir="ltr">Generative Artificial Intelligence (Gen-AI) is a new advancement that has revolutionized the concepts of Natural Language Processing (NLP) and Large Language Model (LLM). This change impacts various aspects of life, stimulating industry, education, and healthcare progression. This survey presents the potential applications of Gen-AI across various sectors, highlighting the risks and opportunities. Some of the most pressing challenges include ethical consideration, the rise of disinformation (including deepfakes), concerns over Intellectual Property (IP) rights, cybersecurity risks, bias and discrimination. The survey also covers the fundamental models of Gen-AI, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers. These frameworks are extremely important in various sectors, including medical imaging, drug discovery, and personalized medicine, and offer valuable insights into the future of technological advancements in the scientific community. The study contributes substantially by exploring positive elements and addressing the challenges of adequately deploying Gen-AI models. Using these insights, we hope to provide a comprehensive knowledge of the potential challenges and complexities associated with the widespread implementation of artificial intelligence technologies.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Archives of Computational Methods in Engineering<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s11831-025-10355-z" target="_blank">https://dx.doi.org/10.1007/s11831-025-10355-z</a></p>2025-09-08T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s11831-025-10355-zhttps://figshare.com/articles/journal_contribution/A_Critical_Analysis_of_Generative_AI_Challenges_Opportunities_and_Future_Research_Directions/31289251CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/312892512025-09-08T03:00:00Z
spellingShingle A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
Mueen Uddin (4903510)
Human society
Policy and administration
Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Generative artificial intelligence
Chat-GPT AND GANs
Transformer models
Autoregressive models of Gen-AI architectures
Variational autoencoders (VAEs)
Misinformation and deepfake
Applications of Gen-AI
status_str publishedVersion
title A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
title_full A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
title_fullStr A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
title_full_unstemmed A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
title_short A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
title_sort A Critical Analysis of Generative AI: Challenges, Opportunities, and Future Research Directions
topic Human society
Policy and administration
Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Generative artificial intelligence
Chat-GPT AND GANs
Transformer models
Autoregressive models of Gen-AI architectures
Variational autoencoders (VAEs)
Misinformation and deepfake
Applications of Gen-AI