As AI systems take on increasingly significant decision-making roles, the ethical implications associated with these technologies have become more prominent. While ethical decision-making, which involves the selection of suitable ethical principles, has been extensively examined in traditional settings, its relevance to AI is still not thoroughly explored. This research examines how linguistic framing influences decision-making within AI systems, specifically investigating the effects of various framing techniques—positive, negative, and neutral—on algorithmic choices. Utilizing a qualitative research framework, the study combines a descriptive method to analyze pertinent literature with an analytical approach to extract insights. The findings indicate that linguistic framing significantly influences AI-driven decisions; however, larger language models showed more resistance to framing effects compared to their smaller counterparts. These results highlight the necessity of acknowledging the potential for framing to manipulate AI systems and emphasize the importance of implementing ethical safeguards in the creation and application of AI technologies.