This lecture explores the evolving relationship between artificial intelligence and artistic practice by analysing how machine learning systems transform concepts of creativity, authorship, and agency. While AI is often described as a tool for automation, its integration into the arts reveals a more complex field of negotiation: What forms of “intelligence” emerge when algorithms become co-creators rather than instruments? How does the delegation of aesthetic decision-making to non-human agents challenge established understandings of originality and intentionality? Drawing on a series of artistic research projects — including Me, Myself and I, Artificial Assistants, Still Life 3000, and AI and the Art of Historical Reinterpretation — this lecture investigates how generative models not only reproduce cultural biases but can also be deliberately misused to expose and disrupt them. In doing so, it reflects on how datasets, training processes, and prompt engineering become artistic materials in their own right. By critically engaging with AI as both collaborator and subject, the lecture introduces the notion of “artist intelligence” as a complementary epistemology: one that situates artistic research as a crucial site for negotiating the ethical, political, and imaginative potentials of machine creativity, and for envisioning how human and non-human forms of intelligence can co-shape future cultural production.