{"id":3833,"date":"2026-02-12T10:56:14","date_gmt":"2026-02-12T10:56:14","guid":{"rendered":"https:\/\/birpub.org\/ijois\/?post_type=journal_article&#038;p=3833"},"modified":"2026-02-13T10:13:33","modified_gmt":"2026-02-13T10:13:33","slug":"impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state","status":"publish","type":"journal_article","link":"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/","title":{"rendered":"Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State"},"content":{"rendered":"\n<p><strong>Iheagwam, Peggy Nwamaka<sup> 1<\/sup>, Professor Fred O. Eze<sup>2<\/sup>\u00a0 &amp;\u00a0 Mbah, Paulinus Chigozie, Ph.D.<sup>3<\/sup><\/strong><\/p>\n\n\n\n<p><strong>Abstract<\/strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><em>The study evaluated the Impact of Artificial Intelligence on workforce management of Nigeria National Petroleum Corporation (NNPC). The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire.&nbsp; A total population of 5042staff was used. The adequate sample size of 357, using Freund and William&#8217;s statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z &#8211; test.&nbsp; The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). The study recommended among others that Nigeria National Petroleum Corporation (NNPC) should invest in the adoption and integration of <strong>machine learning<\/strong> tools to enhance data-driven decision-making, predictive maintenance, and workforce performance analytics<\/em><em><\/em><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong><\/strong><strong><em>Keywords:&nbsp; <\/em><\/strong><em>Artificial Intelligence, Machine Learning, Natural Language Processing, Workforce Management, Organizational Performance, Oil and Gas Industry.<\/em><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/birpub.org\/ijois\/wp-content\/uploads\/sites\/6\/2026\/02\/IJOIS_4135-55.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of IJOIS_41,35-55.\"><\/object><a id=\"wp-block-file--media-7689ac24-04b4-4b61-8872-6b8d0105de45\" href=\"https:\/\/birpub.org\/ijois\/wp-content\/uploads\/sites\/6\/2026\/02\/IJOIS_4135-55.pdf\">IJOIS_41,35-55<\/a><a href=\"https:\/\/birpub.org\/ijois\/wp-content\/uploads\/sites\/6\/2026\/02\/IJOIS_4135-55.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-7689ac24-04b4-4b61-8872-6b8d0105de45\">Download<\/a><\/div>\n","protected":false},"author":1,"template":"","journal_article_cats":[236],"class_list":["post-3833","journal_article","type-journal_article","status-publish","hentry","journal_article_cat-vol-4-no-1"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.1 (Yoast SEO v26.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State - International Journal of Organizational Intelligence and Systems (IJOIS)<\/title>\n<meta name=\"description\" content=\"The study evaluated the Impact of Artificial Intelligence on workforce management of Nigeria National Petroleum Corporation (NNPC). The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. A total population of 5042staff was used. The adequate sample size of 357, using Freund and William&#039;s statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z - test. The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). The study recommended among others that Nigeria National Petroleum Corporation (NNPC) should invest in the adoption and integration of machine learning tools to enhance data-driven decision-making, predictive maintenance, and workforce performance analytics\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State\" \/>\n<meta property=\"og:description\" content=\"The study evaluated the Impact of Artificial Intelligence on workforce management of Nigeria National Petroleum Corporation (NNPC). The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. A total population of 5042staff was used. The adequate sample size of 357, using Freund and William&#039;s statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z - test. The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). The study recommended among others that Nigeria National Petroleum Corporation (NNPC) should invest in the adoption and integration of machine learning tools to enhance data-driven decision-making, predictive maintenance, and workforce performance analytics\" \/>\n<meta property=\"og:url\" content=\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/\" \/>\n<meta property=\"og:site_name\" content=\"International Journal of Organizational Intelligence and Systems (IJOIS)\" \/>\n<meta property=\"article:modified_time\" content=\"2026-02-13T10:13:33+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/\",\"url\":\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/\",\"name\":\"Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State - International Journal of Organizational Intelligence and Systems (IJOIS)\",\"isPartOf\":{\"@id\":\"https:\/\/birpub.org\/ijois\/#website\"},\"datePublished\":\"2026-02-12T10:56:14+00:00\",\"dateModified\":\"2026-02-13T10:13:33+00:00\",\"description\":\"The study evaluated the Impact of Artificial Intelligence on workforce management of Nigeria National Petroleum Corporation (NNPC). The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. A total population of 5042staff was used. The adequate sample size of 357, using Freund and William's statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z - test. The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). The study recommended among others that Nigeria National Petroleum Corporation (NNPC) should invest in the adoption and integration of machine learning tools to enhance data-driven decision-making, predictive maintenance, and workforce performance analytics\",\"breadcrumb\":{\"@id\":\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/birpub.org\/ijois\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/birpub.org\/ijois\/#website\",\"url\":\"https:\/\/birpub.org\/ijois\/\",\"name\":\"International Journal of Organizational Intelligence and Systems (IJOIS)\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/birpub.org\/ijois\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State - International Journal of Organizational Intelligence and Systems (IJOIS)","description":"The study evaluated the Impact of Artificial Intelligence on workforce management of Nigeria National Petroleum Corporation (NNPC). The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. A total population of 5042staff was used. The adequate sample size of 357, using Freund and William's statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z - test. The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). The study recommended among others that Nigeria National Petroleum Corporation (NNPC) should invest in the adoption and integration of machine learning tools to enhance data-driven decision-making, predictive maintenance, and workforce performance analytics","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/birpub.org\/ijois\/journal_article\/impact-of-artificial-intelligence-on-workforce-management-of-nigeria-national-petroleum-corporation-nnpc-rivers-state\/","og_locale":"en_US","og_type":"article","og_title":"Impact of Artificial Intelligence on Workforce Management of Nigeria National Petroleum Corporation (NNPC), Rivers State","og_description":"The study evaluated the Impact of Artificial Intelligence on workforce management of Nigeria National Petroleum Corporation (NNPC). The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. A total population of 5042staff was used. The adequate sample size of 357, using Freund and William's statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z - test. The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). 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The specific objectives are to: Evaluate the impact of machine learning on output and Examine the impact of Natural language processing (NLP) on tracking work hours of Nigeria National Petroleum Corporation (NNPC). The area of the study was Nigeria National Petroleum Corporation (NNPC)Rivers state. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. A total population of 5042staff was used. The adequate sample size of 357, using Freund and William's statistic formula at 5 percent margin of error was used. 281 staff returned the questionnaire and accurately filled. Data was presented and analyzed using Likert Scale and the hypotheses was tested using Z - test. The findings indicated Machine learning had significant positive impact on output. Z = 10.738, P. = 0.05 and Natural language processing (NLP) had significant positive impact on Tracking work hours of Nigeria National Petroleum Corporation (NNPC). Z = 11.737, P. = 0.05. The study concluded that Machine learning and Natural language processing (NLP) had significant positive impact on output and Tracking work hours of Nigeria National Petroleum Corporation (NNPC). 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