2026· International journal of research and innovation in social science· Vol 10, pp. 6905-6928· 0 citations
TL;DR
This study systematically reviews the emerging literature on Ethical AI and Corporate Governance to examine the social implications of AI-driven decision-making in business organisations and proposes an integrated Ethical AI Governance Framework.
Abstract
Artificial Intelligence (AI) is increasingly transforming organisational decision-making processes across finance, human resource management, marketing, risk assessment, and strategic planning. While AI-driven systems offer significant benefits in terms of efficiency, accuracy, and predictive capabilities, they simultaneously raise critical ethical and governance concerns related to transparency, accountability, fairness, privacy, and stakeholder trust. As organisations increasingly rely on algorithmic decision-making, traditional corporate governance frameworks face new challenges in ensuring the responsible and socially acceptable deployment of AI.
This study systematically reviews the emerging literature on Ethical AI and Corporate Governance to examine the social implications of AI-driven decision-making in business organisations. Using a systematic literature review methodology, relevant studies published between 2018 and 2025 were identified through Scopus, Web of Science, Google Scholar, Emerald Insight, and ScienceDirect databases. Following a structured screening and selection process, 68 peer-reviewed publications and policy reports were analysed using thematic analysis.
The review identifies six major themes: algorithmic bias and discrimination, transparency and explainability, accountability and responsibility, privacy and data governance, workforce transformation, and regulatory governance frameworks. Beyond synthesising existing knowledge, the study critically examines tensions between innovation and regulation, human oversight and automation, and Western and non-Western AI governance approaches. The paper proposes an integrated Ethical AI Governance Framework and discusses practical implications for boards of directors, policymakers, and organisational leaders. The study contributes to the growing discourse on responsible AI by offering a governance-centered perspective that balances technological innovation with ethical responsibility and sustainable organisational performance
Overall, AI-assisted governance offers substantial potential to strengthen accountability and stakeholder trust when supported by robust ethical safeguards, transparency measures, and clearly defined responsibility structures.
M. Mar, Ing. Nikolai Fabian Sebastián Yucra Añazco, Delia Nieves Coaquira Pari· Journal of Organizational an...· 0 citations
Examining how artificial intelligence (AI) governance supports sustainable decision-making across organizational contexts in Europe reveals that governance increasingly aligns with formal frameworks through policies, dedicated structures, human oversight and Environmental, Social and Governance oriented indicators, enhancing transparency and reliability.
Fernando Almeida· Journal of Ethics in Entrepr...· 0 citations
Artificial Intelligence (AI) has significantly transformed Human Resource Management (HRM), causing ethical and governance challenges around algorithmic decision making. Despite growing research, the literature is conceptually fragmented and lacking an integrative framework to connect applications of AI models with ethical and governance strategies. This study aims to conduct a systematic literature review and develop a comprehensive governance framework for responsible AI use in HRM. A systematic literature review of 84-peer reviewed articles from 2018 to 2024 was conducted through applying PRISMA protocol. Identifying five core HR-functions and nine major ethical issues. Findings indicate that AI adoption is prominent in recruitment, selection, and performance management, where algorithms shape evaluative decisions. Thus, the applications are associated with bias, transparency, and accountability issues. We develop an integrative governance framework highlighting maturity model, legitimacy, and accountability theory to address these concerns. Shifting the focus from AI adoption to governance, advancing literature on AI-HRM, and creating a clear framework for ethically responsible AI management. Offering actionable practical insights for HR professionals, AI developers, and policy makers on the implementation of responsible AI.
The findings of this study indicate that although artificial intelligence (AI) is increasingly embedded in operational practices across the Australian insurance sector, explicit engagement with ethical AI principles remains limited. Based on an analysis of 156 AI-related web pages from Australian insurers, the results show that 58% of companies do not reference any AI Ethics Principles, highlighting a gap between AI adoption and ethical governance. The predominance of operational themes over governance-oriented discourse suggests that ethical considerations are not yet systematically integrated into public-facing communication strategies. While certain principles, particularly human wellbeing and privacy, receive greater attention, others such as accountability and contestability remain comparatively underrepresented. This imbalance indicates a structural gap between technological implementation and transparent ethical articulation. From an actuarial and governance perspective, strengthening the visibility and consistency of responsible AI commitments may enhance stakeholder trust and support sustainable innovation. This study provides one of the first empirical assessments of publicly articulated ethical AI governance in the Australian insurance sector; future research could extend the analysis to international markets and additional data sources.
M. Armijo, Jinhui Zhang, Yanlin Shi· Risks· 0 citations
The application of artificial intelligence (AI) technologies in the public sector has led to improved public services, enhanced administrative performance, and strengthened automated decision-making. However, the increasing reliance on AI systems has raised concerns regarding accountability, ethical compliance, privacy protection, transparency, human oversight, and risk management. This study, employing both conceptual and qualitative research methodologies, examines the governance factors and requirements for responsible AI implementation in the public sector. The research methodology includes a comparative analysis of international AI governance frameworks and regulations. The study identifies key dimensions influencing responsible AI implementation, such as accountability, human oversight, ethical governance, legal compliance, risk management, and transparency. The findings demonstrate that the adoption of responsible AI cannot be achieved through technological means alone but also requires a commitment to comprehensive governance mechanisms. Furthermore, the sequential interaction and interdependence of governance factors reduce operational and societal risks, increase transparency and explainability, and foster public trust in the systems. This study contributes to enriching the culture and knowledge of AI governance, and the proposed framework helps government sector leaders develop responsible AI governance in accordance with international standards and regulations.
Ghazwan Hani Hussein, Faiza Mohamed, A. Abuzreda· Journal of Technology and Sy...· 0 citations
A strong positive relationship was found between the use of AI and the four dimensions of corporate administration that were investigated, thereby suggesting that the proposed integrated framework could serve as a basis for developing a theory and organizational practice for the future.
Tulika Dutta Roy· International Journal of Mod...· 0 citations
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