Harnessing NLP for Automation and Intelligence Across Sectors

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Notice

nThis is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.n

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Year : 2025 [if 2224 equals=””]12/09/2025 at 1:58 PM[/if 2224] | [if 1553 equals=””] Volume : 16 [else] Volume : 16[/if 1553] | [if 424 equals=”Regular Issue”]Issue : [/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02 | Page : 23 32

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    Ishika Garg, Ramandeep Kaur,

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  1. Student, Student, Department of Computer Applications, Baba Farid Group of Institutions, Bathinda, Department of Computer Applications, Baba Farid Group of Institutions, Bathinda, Punjab, Punjab, India, India

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Abstract

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nNatural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis of electronic health records (EHR), identification of cybersecurity incidents, and training. The study also recognizes recent advancements in NLP, particularly in its convergence with AI and machine learning models, that have significantly improved its accuracy and effectiveness. While NLP holds great promise in several domains, heterogeneity of data, language model bias, ethical considerations, and computational complexity are some of the challenges still arising. The conclusion suggests that NLP has the ability to revolutionize sectors like healthcare, education, finance, and cybersecurity to provide automated, intelligent, and scalable solutions. The study also addresses potential research areas in the future that are focused on making NLP models more inclusive, ethical, and efficient.nn

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Keywords: NLP (natural language processing), AI (artificial intelligence), deep learning, EHRs, BERT, GPT

n[if 424 equals=”Regular Issue”][This article belongs to Journal of Computer Technology & Applications ]

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How to cite this article:
nIshika Garg, Ramandeep Kaur. [if 2584 equals=”][226 wpautop=0 striphtml=1][else]Harnessing NLP for Automation and Intelligence Across Sectors[/if 2584]. Journal of Computer Technology & Applications. 07/08/2025; 16(02):23-32.

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How to cite this URL:
nIshika Garg, Ramandeep Kaur. [if 2584 equals=”][226 striphtml=1][else]Harnessing NLP for Automation and Intelligence Across Sectors[/if 2584]. Journal of Computer Technology & Applications. 07/08/2025; 16(02):23-32. Available from: https://journals.stmjournals.com/jocta/article=07/08/2025/view=0

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Review Article

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Volume 16
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02
Received 28/04/2025
Accepted 08/07/2025
Published 07/08/2025
Retracted
Publication Time 101 Days

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