The growing integration and application of artificial intelligence (AI) within higher education (HE) is profoundly changing information engagement and knowledge creation, presenting both transformational opportunities and significant ethical challenges. This paper highlights the importance of empowering HE stakeholders’ self-efficacy in AI, enhancing their capacity to use the technology ethically, efficiently, and responsibly. The paper proposes the FAIRSPOT framework to help address the ethical challenges and guide responsible AI integration and comprehensive professional development. The framework includes the principles of Fairness, Accountability, Inclusiveness, Reliability, Security, Privacy, Oneness, and Transparency. The paper’s research design employed a meta-bibliometric systematic literature review of AI research publications between 2017 and 2025, examining quantitative frequencies, co-occurrences, and trends, followed by qualitative systematic analysis to examine the ethical challenges of AI implementation in HE. The meta-bibliometric and systematic literature review identified a strong alignment between several FAIRSPOT principles, such as Fairness, Privacy, Inclusiveness, and Transparency, and the ethical challenges documented in HE. Conversely, principles like Accountability, Reliability, Security, and Oneness were comparatively under-represented despite their growing relevance. FAIRSPOT framework’s holistic concept of Oneness offers space for an Ubuntu-inspired approach to interconnected and ethically coherent AI systems. However, further empirical validation is essential to substantiate its practical value across diverse socio-cultural and educational contexts. The study acknowledges its limitations due to its reliance on the Scopus database and specific keywords. The paper seeks to contribute an analytical perspective on the current state of AI ethics in HE.