This paper offers an exploratory examination of the emerging discourse and practices on decolonising AI ethics. Whilst the field of AI ethics has made substantial progress in proposing normative frameworks for responsible innovation, these frameworks remain predominantly grounded in Western epistemological traditions, foundations which have limited the capacity of AI ethics to engage with plural ontologies and non-Western moral traditions, particularly those emerging from the Global South. Drawing from decolonial and critical data studies, this paper interrogates what an alternative, decolonial orientation to AI ethics might entail in both conceptual and practical terms. We contend that mainstream AI ethics frameworks fail to recognise epistemic diversity and to establish dialogical relations with non-Western knowledge systems, thereby reproducing colonial hierarchies of thought and governance within technological design and deployment. An answer to the question of decolonising AI ethics is not simple or straightforward and will, therefore, not be single handedly delivered in this paper, whilst we acknowledge the situatedness and limitations of our study. Whilst we understand that there are many other realms to examine for a decolonial AI ethics (such as critical infrastructure, labour, and political economy), we decide to focus on the following reflections: (1) AI as a means to redress power asymmetries and structural exploitation; (2) AI grounded in local data sovereignty and equitable epistemic participation; and (3) AI conceived as relationally entangled with humans, more-than-humans, and the Earth. These reflections foreground the material and ecological dimensions of data—its extractive infrastructures, environmental externalities, and geo-political inequalities—as central to the ethical assessment of AI. Through a literature-based exploration of these domains, we argue that decolonising AI ethics requires moving beyond the universalist and procedural tendencies of Western ethical paradigms towards pluriversal, situated, and ecologically embedded forms of ethical reasoning. The paper concludes by outlining how these reflections can serve as a theoretical scaffold for rearticulating AI ethics in and from the Global South, resisting the uncritical replication of Northern frameworks and opening pathways for epistemic plurality in global AI governance.