JOURNAL ARTICLEZainab Aziz · Tshilidzi Eric Nenzhelele
International Journal of Business Ecosystem & Strategy · 2026
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Artificial intelligence (AI) is progressively revolutionising project management by enhancing forecasting, planning, decision-making, risk evaluation, and organisational efficacy. Nevertheless, escalating apprehensions about trust, accountability, equity, transparency, and human supervision have underscored the necessity for governance strategies that transcend mere technical efficacy. This research performs a concept-focused systematic literature review to investigate the convergence of Ubuntu, African ethics, Human-Centred Artificial Intelligence (HCAI), and project governance. This research consolidates disparate knowledge domains related to responsible AI, HCAI, ethical leadership, stakeholder governance, organisational preparedness, and Ubuntu-informed leadership, stakeholder inclusivity, and a comprehensive Ubuntu-informed human-AI governance framework, utilising peer-reviewed literature from 2022 to 2026. This research posits that Ubuntu offers a unique governance viewpoint rooted in collective responsibility, relational leadership, and human dignity. The results indicate that Ubuntu-informed AI governance can assist African governments and policymakers in establishing ethical and responsible frameworks. This research establishes a basis for subsequent investigations on Ubuntu, artificial intelligence governance, and project management. The results underscore the significance of ethical leadership, stakeholder engagement, human supervision, and responsibility for project management professionals in responsible AI-driven project settings.
DOI 10.36096/ijbes.v8i4.13660 Crossref citations0 OpenAlex citations
JOURNAL ARTICLEAhmed Alribi
International Journal of Research in Business and Social Science · 2026
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Artificial intelligence (AI) is fundamentally transforming accounting practice by displacing traditional data-processing tasks, augmenting auditing functions, and reshaping the professional competency requirements of financial reporting. While these technological developments generate substantial efficiency gains, they simultaneously introduce unprecedented ethical challenges, including algorithmic opacity, accountability diffusion, bias propagation in automated judgment, and the erosion of professional scepticism — that threaten the integrity of financial reporting and the public trust upon which the accounting profession's social licence to operate ultimately depends. This paper develops a rigorous, theoretically grounded analysis of the intersection between artificial intelligence and accounting ethics, drawing on institutional theory, agency theory, virtue ethics, and the stakeholder trust framework to diagnose how AI adoption reconfigures the ethical architecture of financial reporting and to prescribe the governance, professional, and regulatory responses required to safeguard ethical standards and trust in this transformed environment. The paper makes three original contributions: first, it develops a multi-dimensional taxonomy of AI-related ethical risks in accounting, distinguishing technical, professional, and systemic risk categories; second, it proposes the Ethical AI Accounting Governance Framework (EAAGF), an original implementation model that integrates algorithmic governance, professional ethics renewal, regulatory adaptation, and stakeholder assurance mechanisms; and third, it situates these contributions within a comparative empirical analysis of AI adoption experiences across major accounting contexts, integrating evidence from surveys, regulatory reports, and case illustrations. The paper argues that the central challenge is not whether AI will transform accounting — this is already occurring — but whether the profession, regulators, and organisations can collectively construct the ethical governance infrastructure required to ensure that transformation advances rather than undermines the accountability, transparency, and trust that constitute the profession's foundational social purpose.
DOI 10.20525/ijrbs.v15i5.53030 Crossref citations0 OpenAlex citations