{"id":22540,"date":"2025-12-28T16:51:00","date_gmt":"2025-12-28T16:51:00","guid":{"rendered":"https:\/\/journals.amssr.org\/grjbm\/?p=22540"},"modified":"2026-02-04T16:53:33","modified_gmt":"2026-02-04T16:53:33","slug":"artificial-intelligence-integration-and-organizational-planning-efficiency-in-the-national-biosafety-management-agency-abuja","status":"publish","type":"post","link":"https:\/\/journals.amssr.org\/grjbm\/2025\/12\/28\/artificial-intelligence-integration-and-organizational-planning-efficiency-in-the-national-biosafety-management-agency-abuja\/","title":{"rendered":"ARTIFICIAL INTELLIGENCE INTEGRATION AND ORGANIZATIONAL PLANNING EFFICIENCY IN THE NATIONAL BIOSAFETY MANAGEMENT AGENCY, ABUJA"},"content":{"rendered":"\n<p>Download PDF<br><\/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:\/\/journals.amssr.org\/grjbm\/wp-content\/uploads\/sites\/3\/2026\/02\/ARTIFICIAL-INTELLIGENCE-INTEGRATION-AND-ORGANIZATIONAL-PLANNING-EFFICIENCY-IN-THE-NATIONAL-BIOSAFETY-MANAGEMENT-AGENCY-ABUJA.docx.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of ARTIFICIAL INTELLIGENCE INTEGRATION AND ORGANIZATIONAL PLANNING EFFICIENCY IN THE NATIONAL BIOSAFETY MANAGEMENT AGENCY, ABUJA.docx.\"><\/object><a id=\"wp-block-file--media-e443b34b-ad2c-45f8-8f4e-089dab112ae8\" href=\"https:\/\/journals.amssr.org\/grjbm\/wp-content\/uploads\/sites\/3\/2026\/02\/ARTIFICIAL-INTELLIGENCE-INTEGRATION-AND-ORGANIZATIONAL-PLANNING-EFFICIENCY-IN-THE-NATIONAL-BIOSAFETY-MANAGEMENT-AGENCY-ABUJA.docx.pdf\">ARTIFICIAL INTELLIGENCE INTEGRATION AND ORGANIZATIONAL PLANNING EFFICIENCY IN THE NATIONAL BIOSAFETY MANAGEMENT AGENCY, ABUJA.docx<\/a><a href=\"https:\/\/journals.amssr.org\/grjbm\/wp-content\/uploads\/sites\/3\/2026\/02\/ARTIFICIAL-INTELLIGENCE-INTEGRATION-AND-ORGANIZATIONAL-PLANNING-EFFICIENCY-IN-THE-NATIONAL-BIOSAFETY-MANAGEMENT-AGENCY-ABUJA.docx.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-e443b34b-ad2c-45f8-8f4e-089dab112ae8\">Download<\/a><\/div>\n\n\n\n<p>Author<\/p>\n\n\n\n<p><strong>&nbsp;\u00b9<\/strong><strong>Adogbo Victoria<\/strong><strong>,&nbsp;<\/strong><\/p>\n\n\n\n<p>Department of Business Administration, Faculty of Management Sciences, National Open University of Nigeria, Abuja, Nigeria<\/p>\n\n\n\n<p>&nbsp;&nbsp;<strong>&nbsp;&nbsp;\u00b9<\/strong><a href=\"mailto:adogbovictoria@gmail.com\">adogbovictoria@gmail.com<\/a>&nbsp; 09134375759<\/p>\n\n\n\n<p><strong>ABSTRACT&nbsp;<\/strong><\/p>\n\n\n\n<p><strong>Research Objective:<\/strong><br>This study examined the influence of artificial intelligence (AI) integration on organizational planning efficiency within the National Biosafety Management Agency (NBMA), Abuja, with a specific focus on AI adoption level, perceived usefulness of AI, and perceived ease of use of AI systems.<\/p>\n\n\n\n<p><strong>Methodology:<\/strong><br>A quantitative survey research design was employed. Structured questionnaires were distributed to NBMA staff, with a sample size of 250 determined using Yamane\u2019s (1967) formula from a population of 500. A total of 162 valid responses were analyzed. The reliability of the instrument was confirmed by Cronbach\u2019s alpha values, all exceeding 0.70. Data were analyzed using SPSS Version 27, employing descriptive statistics and Pearson correlation.<\/p>\n\n\n\n<p><strong>Findings:<\/strong><br>The results revealed significant positive correlations between all AI integration dimensions and planning efficiency. Perceived usefulness of AI demonstrated the strongest influence on planning efficiency (r = 0.701, p &lt; 0.01), followed by perceived ease of use (r = 0.621, p &lt; 0.01), and AI adoption level (r = 0.584, p &lt; 0.01). High mean scores across all constructs indicated generally favorable staff perceptions towards AI-enabled planning processes.<\/p>\n\n\n\n<p><strong>Conclusion:<\/strong><br>Effective integration of AI, particularly when systems are perceived as useful and user-friendly, substantially enhances organizational planning efficiency in public sector agencies such as NBMA.<\/p>\n\n\n\n<p><strong>Recommendations:<\/strong><br>The study recommends strategic investment in user-centered AI deployment, continuous staff training, and robust change management initiatives to maximize AI\u2019s potential and sustain improvements in planning efficiency.<\/p>\n\n\n\n<p><strong>Keywords:<\/strong>\u00a0Artificial Intelligence, AI Adoption, Perceived Usefulness, Perceived Ease of Use<\/p>\n\n\n\n<p><strong>REFERENCES<\/strong><\/p>\n\n\n\n<p>Al-Okaily, M., Alqudah, H., Alqudah, H., &amp; Alsharari, N. M. (2022). 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(2022). Artificial intelligence in public administration: A systematic review and research agenda.&nbsp;<em>International Review of Administrative Sciences, 88<\/em>(1), 20\u201342. https:\/\/doi.org\/10.1177\/0020852320919533<\/p>\n\n\n\n<p>World Economic Forum. (2023).&nbsp;<em>AI and digital transformation in government: Global trends and best practices<\/em>. https:\/\/www.weforum.org\/reports\/ai-digital-transformation-public-sector-2023<\/p>\n\n\n\n<p>Yu, S., Li, Y., &amp; Wang, H. (2022). Digital technologies and organizational planning efficiency.&nbsp;<em>Technological Forecasting and Social Change, 178<\/em>, 121610. https:\/\/doi.org\/10.1016\/j.techfore.2022.121610<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Download PDF Author &nbsp;\u00b9Adogbo Victoria,&nbsp; Department of Business Administration, Faculty of Management Sciences, National Open University of Nigeria, Abuja, Nigeria &nbsp;&nbsp;&nbsp;&nbsp;\u00b9adogbovictoria@gmail.com&nbsp; 09134375759 ABSTRACT&nbsp; Research Objective:This study examined the influence of artificial intelligence (AI) integration on organizational planning efficiency within the National Biosafety Management Agency (NBMA), Abuja, with a specific focus on AI adoption level, perceived usefulness of AI, and perceived ease of use of AI systems. Methodology:A quantitative survey research design was employed. Structured questionnaires were distributed to NBMA staff, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":21662,"comment_status":"open","ping_status":"0","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19,224,222],"tags":[],"class_list":["post-22540","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-grjbm","category-vol-6-issue-2","category-volume-6"],"_links":{"self":[{"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts\/22540","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=22540"}],"version-history":[{"count":1,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts\/22540\/revisions"}],"predecessor-version":[{"id":22542,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/posts\/22540\/revisions\/22542"}],"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=22540"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/categories?post=22540"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/journals.amssr.org\/grjbm\/wp-json\/wp\/v2\/tags?post=22540"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}