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Evaluation of generative artificial intelligence (GENAI) as a transformative technology for effective and efficient governance, political knowledge, electoral, and democratic processes

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  • Chiji Longinus Ezeji

    (University of Johannesburg, South Africa)

  • Dominique Emmanuel Uwizeyimana

    (University of Johannesburg, South Africa)

Abstract

The incorporation of generative artificial intelligence in governance, political knowledge, electoral, and democratic processes is essential as the world transitions to a digital paradigm. Numerous nations have adopted Generative AI (GenAI), a disruptive technology that compels electoral bodies to advocate for the integration of such tools into governance, electoral, and democratic processes. Nevertheless, these technologies do not ensure effortless integration or efficient usage owing to intricate socio-cultural and human dynamics. Certain African jurisdictions are ill-prepared for the adoption of these technologies due to factors including underdevelopment, insufficient electrical supply, lack of technology literacy, reluctance to change, and the goals of governing parties. This study examines generative artificial intelligence as a disruptive technology for enhancing governance, political knowledge, electoral processes, and democracy. A mixed-method approach was employed, incorporating surveys and in-person interviews. The analysis of data, debates, and interpretation of findings were grounded in postdigital theory and theme analysis employing an abductive reasoning technique, in alignment with the tenets of critical realism. The study demonstrated that GENAI can influence political knowledge, election processes, and enhance efficiency in government and democracy. Moreover, GENAI, including ChatGPT, can either exacerbate or mitigate societal tendencies that contribute to human division, facilitate the dissemination of misinformation, perpetuate echo chambers, and undermine social and political trust, as well as polarise disparate groups or sets of viewpoints or beliefs. AI offers substantial opportunities but also poses many obstacles, including technical constraints, ethical dilemmas, and social ramifications. The swift progression of AI may disrupt labour markets by automating tasks conventionally executed by people, resulting in job displacement. Implementing AI necessitates significant upskilling and proficiency with digital tools; therefore, governments and organisations must adequately train their personnel to reconcile the disparity between AI's capabilities and users' comprehension. Additionally, there is a requisite for governmental oversight, regulation, and monitoring of AI adoption and utilisation across all facets of its implementation. Key Words:Artificial, Democratic, Electoral, Evaluation, Generative, Governance, Intelligence, Knowledge, Political Processes, and Technology

Suggested Citation

  • Chiji Longinus Ezeji & Dominique Emmanuel Uwizeyimana, 2025. "Evaluation of generative artificial intelligence (GENAI) as a transformative technology for effective and efficient governance, political knowledge, electoral, and democratic processes," International Journal of Business Ecosystem & Strategy (2687-2293), Bussecon International Academy, vol. 7(3), pages 241-254, June.
  • Handle: RePEc:adi:ijbess:v:7:y:2025:i:3:p:241-254
    DOI: 10.36096/ijbes.v7i3.831
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    References listed on IDEAS

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    1. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    2. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 58(1), pages 237-291, March.
    3. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
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