{"id":22460,"date":"2025-10-27T07:34:16","date_gmt":"2025-10-27T07:34:16","guid":{"rendered":"https:\/\/journals.amssr.org\/grjbm\/?p=22460"},"modified":"2025-10-27T07:34:23","modified_gmt":"2025-10-27T07:34:23","slug":"integration-of-artificial-intelligence-in-cost-accounting-for-real-time-decision-making-at-innoson-nigeria-limited-plc","status":"publish","type":"post","link":"https:\/\/journals.amssr.org\/grjbm\/2025\/10\/27\/integration-of-artificial-intelligence-in-cost-accounting-for-real-time-decision-making-at-innoson-nigeria-limited-plc\/","title":{"rendered":"INTEGRATION OF ARTIFICIAL INTELLIGENCE IN COST ACCOUNTING FOR REAL-TIME DECISION MAKING AT INNOSON NIGERIA LIMITED PLC"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Download PDF<\/h2>\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:\/\/journals.amssr.org\/grjbm\/wp-content\/uploads\/sites\/3\/2025\/10\/INTEGRATION-OF-ARTIFICIAL-INTELLIGENCE-IN-COST-ACCOUNTING-FOR-REAL-TIME-DECISION-MAKING-AT-INNOSON-NIGERIA-LIMITED-PLC.-GRJBM-AMSSRN.docx.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of INTEGRATION OF ARTIFICIAL INTELLIGENCE IN COST ACCOUNTING FOR REAL-TIME DECISION MAKING AT INNOSON NIGERIA LIMITED PLC. GRJBM AMSSRN.docx.\"><\/object><a id=\"wp-block-file--media-6d9ba2dc-b8fe-42b2-bb1c-08b57c711e0e\" href=\"https:\/\/journals.amssr.org\/grjbm\/wp-content\/uploads\/sites\/3\/2025\/10\/INTEGRATION-OF-ARTIFICIAL-INTELLIGENCE-IN-COST-ACCOUNTING-FOR-REAL-TIME-DECISION-MAKING-AT-INNOSON-NIGERIA-LIMITED-PLC.-GRJBM-AMSSRN.docx.pdf\">INTEGRATION OF ARTIFICIAL INTELLIGENCE IN COST ACCOUNTING FOR REAL-TIME DECISION MAKING AT INNOSON NIGERIA LIMITED PLC. GRJBM AMSSRN.docx<\/a><a href=\"https:\/\/journals.amssr.org\/grjbm\/wp-content\/uploads\/sites\/3\/2025\/10\/INTEGRATION-OF-ARTIFICIAL-INTELLIGENCE-IN-COST-ACCOUNTING-FOR-REAL-TIME-DECISION-MAKING-AT-INNOSON-NIGERIA-LIMITED-PLC.-GRJBM-AMSSRN.docx.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-6d9ba2dc-b8fe-42b2-bb1c-08b57c711e0e\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><br>Authors<\/h2>\n\n\n\n<p>Onuoha, Perpetua Ijeoma (Ph.D.) <sup>1<\/sup>; Izinya, Thomas Nweke <sup>2<\/sup>\u00a0<\/p>\n\n\n\n<p><em><sup>1<\/sup><\/em><em>Faculty of Management Sciences<\/em><\/p>\n\n\n\n<p><em>Alex &#8211; Ekwueme Federal University Ndufu &#8211; Alike, Nigeria.<\/em><\/p>\n\n\n\n<p><em><sup>2<\/sup><\/em><em>Department of Accountancy<\/em><\/p>\n\n\n\n<p><em>&nbsp;Ebonyi State University Abakaliki, Nigeria<\/em><\/p>\n\n\n\n<p><em>&nbsp;<\/em><em><sup>1 <\/sup><\/em><a href=\"mailto:onuohaijeomaperpetua@gmail.com\"><em>onuohaijeomaperpetua@gmail.com<\/em><\/a><em>, 07033548086<\/em><\/p>\n\n\n\n<p><em><sup>2 <\/sup><\/em><a href=\"mailto:izinytoms36@gmail.com\"><em>izinytoms36@gmail.com<\/em><\/a><em>, 08032643781<\/em><\/p>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p><strong>Research Objectives:<\/strong> This study investigates how Artificial Intelligence (AI) can be integrated into cost accounting systems to enhance real-time decision-making at Innoson Nigeria Limited Plc. It aims to assess the potential benefits, evaluate existing limitations in traditional cost accounting, and provide recommendations for AI-driven transformation.<\/p>\n\n\n\n<p><strong>Methodology:<\/strong> The research adopts a qualitative design using secondary data from academic literature, industry reports, and case studies on AI in accounting and manufacturing. Company-specific insights were drawn from available organizational reports and industry analyses. Comparative review techniques were applied to highlight the gaps between traditional cost accounting and AI-enabled systems.<\/p>\n\n\n\n<p><strong>Findings:<\/strong> The results show that AI leads to better accuracy and timeliness of the cost allocations, reinforces predictive planning with digital twins, boosts transparency with explainable AI, and promotes risk management with anomaly detection in cost data. Based on the statistical examples, there is better precision in cost allocations, less error is generated and the rate of decision making is higher with the new approach than the old one.<\/p>\n\n\n\n<p><strong>Conclusion:<\/strong><em> <\/em>This research arrives at the conclusion that AI-based cost accounting will give Innoson a sound baseline upon which to make a proactive, transparent, and evidence-based decision-making process.&nbsp;<\/p>\n\n\n\n<p><strong>Recommendations:<\/strong> The study recommends phased AI adoption, workforce reskilling, collaboration with technology partners, and embedding AI tools into the company\u2019s existing management information systems to ensure sustainability and scalability.<\/p>\n\n\n\n<p><strong>Keywords: <\/strong>Artificial Intelligence, Cost Accounting, Real-Time Decision-Making, Manufacturing, Innoson Nigeria Plc<br><\/p>\n\n\n\n<p>&nbsp;<strong>References<\/strong><\/p>\n\n\n\n<p>Al-Hashimy, H. N. H. (2021). Evaluating the impact of real-time data processing in electronic accounting information systems on financial decision-making. <em>Kyzylorda Scholarly Review<\/em>.&nbsp; <a href=\"https:\/\/bulletin.ouk.kz\/index.php\/bulletin\/article\/view\/19\" target=\"_blank\" rel=\"noopener\">https:\/\/bulletin.ouk.kz\/index.php\/bulletin\/article\/view\/19<\/a><a href=\"https:\/\/bulletin.ouk.kz\/index.php\/bulletin\/article\/view\/19?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">bulletin.ouk.kz<\/a><\/p>\n\n\n\n<p>Alrujoubi, A. M., &amp; B\u00fcy\u00fckmirza, H. K. (2025). The role of artificial intelligence to integrate robotics in cost accounting. <em>Libyan International Journal of Natural Sciences, 1<\/em>(1), 1\u201310.&nbsp; <a href=\"https:\/\/aonsrt.ly\/iljs\/index.php\/iljsen\/article\/view\/9\" target=\"_blank\" rel=\"noopener\">https:\/\/aonsrt.ly\/iljs\/index.php\/iljsen\/article\/view\/9<\/a><a href=\"https:\/\/aonsrt.ly\/iljs\/index.php\/iljsen\/article\/view\/9?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">aonsrt.ly<\/a><\/p>\n\n\n\n<p>Alrujoubi, A. M., &amp; B\u00fcy\u00fckmirza, H. K. (2025). The role of artificial intelligence to integrate robotics in cost accounting. <em>Libyan International Journal of Natural Sciences, 1<\/em>(1), 1\u201310.&nbsp; <a href=\"https:\/\/aonsrt.ly\/iljs\/index.php\/iljsen\/article\/view\/9\" target=\"_blank\" rel=\"noopener\">https:\/\/aonsrt.ly\/iljs\/index.php\/iljsen\/article\/view\/9<\/a><a href=\"https:\/\/aonsrt.ly\/iljs\/index.php\/iljsen\/article\/view\/9?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">aonsrt.ly<\/a><\/p>\n\n\n\n<p>Chen, B. (2022). 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Leveraging advanced AI in Activity-Based Costing (ABC) for enhanced cost management. <em>Journal of Computer, Signal, and System Research, 5<\/em>(1), 68\u201384.&nbsp; <a href=\"https:\/\/www.gbspress.com\/index.php\/JCSSR\/article\/view\/68\" target=\"_blank\" rel=\"noopener\">https:\/\/www.gbspress.com\/index.php\/JCSSR\/article\/view\/68<\/a><a href=\"https:\/\/www.gbspress.com\/index.php\/JCSSR\/article\/view\/68?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">gbspress.com<\/a><\/p>\n\n\n\n<p>Shrestha, Y. R., Krishna, V., &amp; von Krogh, G. (2020). Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges. <em>arXiv<\/em>.&nbsp; <a href=\"https:\/\/arxiv.org\/abs\/2011.02834\" target=\"_blank\" rel=\"noopener\">https:\/\/arxiv.org\/abs\/2011.02834<\/a><a href=\"https:\/\/arxiv.org\/abs\/2011.02834?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">arXiv<\/a><\/p>\n\n\n\n<p>Sofianidis, G., Ro\u017eanec, J. M., Mladeni\u0107, D., &amp; Kyriazis, D. (2021). A review of explainable artificial intelligence in manufacturing. <em>arXiv<\/em>.&nbsp; <a href=\"https:\/\/arxiv.org\/abs\/2107.02295\" target=\"_blank\" rel=\"noopener\">https:\/\/arxiv.org\/abs\/2107.02295<\/a><a href=\"https:\/\/arxiv.org\/abs\/2107.02295?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">arXiv<\/a><\/p>\n\n\n\n<p>Yoo, S., &amp; Kang, N. (2020). Explainable artificial intelligence for manufacturing cost estimation and machining feature visualization. <em>arXiv<\/em>.&nbsp; <a href=\"https:\/\/arxiv.org\/abs\/2010.14824\" target=\"_blank\" rel=\"noopener\">https:\/\/arxiv.org\/abs\/2010.14824<\/a><a href=\"https:\/\/arxiv.org\/abs\/2010.14824?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">arXiv<\/a><\/p>\n\n\n\n<p>Yukcu, S., &amp; Aydin, O. (2021). Digital twin as a cost reduction method. <em>arXiv<\/em>.&nbsp; <a href=\"https:\/\/arxiv.org\/abs\/2107.14109\" target=\"_blank\" rel=\"noopener\">https:\/\/arxiv.org\/abs\/2107.14109<\/a><a href=\"https:\/\/arxiv.org\/abs\/2107.14109?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">arXiv<\/a>Yukcu, S., &amp; Aydin, O. (2021). Digital twin as a cost reduction method. <em>arXiv<\/em>.&nbsp; <a href=\"https:\/\/arxiv.org\/abs\/2107.14109\" target=\"_blank\" rel=\"noopener\">https:\/\/arxiv.org\/abs\/2107.14109<\/a><a href=\"https:\/\/arxiv.org\/abs\/2107.14109?utm_source=chatgpt.com\" target=\"_blank\" rel=\"noopener\">arXiv<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Download PDF Authors Onuoha, Perpetua Ijeoma (Ph.D.) 1; Izinya, Thomas Nweke 2\u00a0 1Faculty of Management Sciences Alex &#8211; Ekwueme Federal University Ndufu &#8211; Alike, Nigeria. 2Department of Accountancy &nbsp;Ebonyi State University Abakaliki, Nigeria &nbsp;1 onuohaijeomaperpetua@gmail.com, 07033548086 2 izinytoms36@gmail.com, 08032643781 Abstract Research Objectives: This study investigates how Artificial Intelligence (AI) can be integrated into cost accounting systems to enhance real-time decision-making at Innoson Nigeria Limited Plc. It aims to assess the potential benefits, evaluate existing limitations in traditional cost accounting, and [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":21662,"comment_status":"open","ping_status":"0","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19,221,219],"tags":[],"class_list":["post-22460","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-grjbm","category-vol-5-issue-2","category-volume-5"],"_links":{"self":[{"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts\/22460","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/comments?post=22460"}],"version-history":[{"count":1,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts\/22460\/revisions"}],"predecessor-version":[{"id":22462,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts\/22460\/revisions\/22462"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/media\/21662"}],"wp:attachment":[{"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/media?parent=22460"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/categories?post=22460"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/tags?post=22460"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}