Abstract: Generative artificial intelligence, enabled through sophisticated machine learning frameworks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), is disrupting the creative landscape within many of the creative industries, opening a new set of tools for content creation. Therefore, this article investigates the disruptions generative models present across multiple aspects of creative production, focusing on the influences of art, music, literature, and design. In the visual arts, generative AI produces original artworks that blend aesthetics and styles that extend conventional notions of creativity; in music, AI-composition tools allow musicians to compose original musical works and experiment with entirely new genres. In literature and storytelling, the same generative processes offer AI systems the ability to propose narrative frameworks and other textual elements that may instigate human writers to take these concepts further with a narrative or may stand on their own as original content. In design, generative algorithms support product development all the way down to quickly prototyping new products. The paper includes specific case studies or outlines of the application of generative AI tools to proposed projects, a discussion of effectiveness with the respective generative model, and the potential limitations generative models present for each creative area. The paper will also reflect on the threats generative AI may pose, the potential to redefine human creativity, originality, and ownership, implications for the potential decision-making capabilities of these systems, and if there may be consequences for society. In all these considerations, there are opportunities for and more significant implications of the potential of generative AI to assist and expand human creative possibilities throughout the entire creative process.