This pioneering study explores students' perceptions of AI-giarism, an emergent form of academic dishonesty involving AI and plagiarism, within the higher education context. A survey, undertaken by 393 undergraduate and postgraduate students from a variety of disciplines, investigated their perceptions of diverse AI-giarism scenarios. The findings portray a complex landscape of understanding, with clear disapproval for direct AI content generation, yet more ambivalent attitudes towards subtler uses of AI. The study introduces a novel instrument, as an initial conceptualization of AI-giarism, offering a significant tool for educators and policy-makers. This scale facilitates understanding and discussions around AI-related academic misconduct, aiding in pedagogical design and assessment in an era of AI integration. Moreover, it challenges traditional definitions of academic misconduct, emphasizing the need to adapt in response to evolving AI technology. Despite limitations, such as the rapidly changing nature of AI and the use of convenience sampling, the study provides pivotal insights for academia, policy-making, and the broader integration of AI technology in education.