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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">BJCR</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">British Journal of Contemporary Research</journal-title>
        <abbrev-journal-title xml:lang="en">BJCR</abbrev-journal-title>
      </journal-title-group>
      <issn>2979-8582</issn>
      <publisher>
        <publisher-name>Bexford Publishing Ltd</publisher-name>
        <publisher-loc><uri>https://bexfordpublishing.co.uk</uri></publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">BEX_JUN_26_039</article-id>
      
      <article-categories>
        <subj-group xml:lang="en" subj-group-type="heading">
          <subject>Original Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title xml:lang="en">Artificial Intelligence and Environmental Sustainability in International Political Economy: Implications for Nigeria</article-title>
      </title-group>
      <contrib-group content-type="author">
      <contrib corresp="yes">
        <name-alternatives>
          <name name-style="western" specific-use="primary">
            <given-names>Tony Aku Amba</given-names>
          </name>
        </name-alternatives>
        <email>revtonyakuamba@gmail.com</email>
        <bio xml:lang="en"><p>Neo Tropical Urban Rural Environmental Resilience  and Sustainable Development Initiative Jos, Plateau State , Nigeria, Nigeria</p></bio>
      </contrib>
      <contrib>
        <name-alternatives>
          <name name-style="western" specific-use="primary">
            <given-names>Nanbil Amba</given-names>
          </name>
        </name-alternatives>
        <email>nanbilamba@gmail.com</email>
        <bio xml:lang="en"><p>Department of Mass Communication. Plateau State Polytechnic Jos</p></bio>
      </contrib>
      </contrib-group>
      <pub-date date-type="pub" publication-format="epub">
        <day>10</day>
        <month>07</month>
        <year>2026</year>
      </pub-date>
      <volume>1</volume>
      <issue>2</issue>
      
      
      <pub-history>
        <event event-type="received">
          <event-desc>Received: <date date-type="received">
            <day>11</day>
            <month>06</month>
            <year>2026</year>
          </date></event-desc>
        </event>
        
        <event event-type="accepted">
          <event-desc>Accepted: <date date-type="accepted">
            <day>16</day>
            <month>06</month>
            <year>2026</year>
          </date></event-desc>
        </event>
      </pub-history>
      <permissions>
        <copyright-statement>Copyright (c) 2026 Tony Aku Amba</copyright-statement>
        <copyright-year>2026</copyright-year>
        <license xlink:href="https://creativecommons.org/licenses/by/4.0">
          <license-p>This work is licensed under a Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
      <abstract><p>Artificial Intelligence (AI) has emerged as a transformative technology with significant implications for environmental governance, sustainable development, and the evolving dynamics of the International Political Economy (IPE). This study examines the role of AI in advancing environmental sustainability in Nigeria while exploring how global political–economic structures influence its adoption and effectiveness. Using a mixed-methods research design, the study combined quantitative data from 210 respondents drawn from environmental regulatory agencies, technology firms, academic institutions, and civil society organizations with qualitative interviews involving 25 key informants. Descriptive statistics and thematic analysis were employed to analyze the data. The findings reveal that AI contributes substantially to environmental monitoring, climate prediction, energy efficiency, and resource management, with environmental monitoring recording the highest perceived effectiveness. However, inadequate digital infrastructure, high implementation costs, weak regulatory frameworks, limited technical expertise, and dependence on foreign AI platforms significantly constrain its widespread adoption. Correlation analysis further demonstrates a strong positive relationship between institutional capacity and the effectiveness of AI-driven environmental sustainability initiatives, highlighting the importance of governance and policy support. Qualitative evidence indicates that donor dependence, foreign ownership of AI technologies, limited national control over environmental data, and alignment with external development agendas shape AI implementation in Nigeria, reinforcing existing technological and political–economic dependencies. The study concludes that while AI offers considerable opportunities for improving environmental sustainability, its transformative potential can only be fully realized through strengthened institutional capacity, investment in domestic innovation, improved digital infrastructure, and policies that promote technological sovereignty. By integrating AI, environmental sustainability, and International Political Economy perspectives, the study contributes to contemporary debates on sustainable development and provides practical policy recommendations for enhancing Nigeria’s resilience and competitiveness in the global digital economy. 

Keywords: Artificial Intelligence; Environmental Sustainability; International Political Economy; Environmental Governance; Nigeria.</p></abstract>
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  </front>
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