Traditionally, creative professionals have drawn from a wide array of sources and inspiration, borrowing and building upon the ideas of others in their work. In the last two decades, there is little doubt that search engines and databases have been the starting points in the creative process of many artists and designers. However, in the last couple of years, AI has ushered in a new era of creative possibilities for design disciplines taught in schools, such as graphic design, product design, videography, animation, game design, and multimedia arts. This article explores how AI can help make design students more efficient and inspire original ideas by providing specific examples of AI programmes and their applications in creative disciplines.

Before looking into specific examples, it’s essential to understand how AI can augment the creative process. AI can assist artists and designers in various ways, whether professionals or students.

• Enhancing Efficiency: AI automates repetitive tasks, freeing creative professionals to focus on more complex and imaginative aspects of their work.
• Generating Ideas: AI can generate ideas and concepts based on parameters set by the artist or designer, helping to overcome creative blocks or providing fresh perspectives.
• Expanding Horizons: AI can analyse vast datasets to expose artists and designers to various influences, helping them discover new styles, trends, and techniques.
• Augmenting Skills: AI can bolster technical skills by automating complex processes and enabling professionals to execute tasks they might not have been able to perform manually.

Whilst not exhaustive, the list below covers some specific examples of how AI can empower creativity in the various creative disciplines mentioned above:

Graphic Design:

• AI-Driven Style Transfer: Tools like Deep Dream, Prisma, and Adobe’s Neural Filters allow graphic designers to apply various artistic styles to their work, creating unique visual aesthetics and inspiring original designs.
• Content Generation: ChatGPT, powered by GPT-3, can assist designers in brainstorming ideas, generating ad copy, or even drafting design briefs, sparking new concepts and approaches.
• Image Composition: OpenAI’s DALL·E can generate imaginative and surreal image compositions based on textual descriptions, serving as a valuable reference for graphic designers seeking novel ideas.

Product Design and Engineering:

• Parametric Design: Generative design software like Autodesk’s Generative Design uses AI to optimise product designs based on performance criteria, leading to more innovative and efficient solutions.
• Sketch Enhancement: AI-driven tools, such as Adobe Sensei’s Auto Reframe, can turn rough product sketches into polished technical drawings, helping designers communicate their ideas more effectively.
• Prototyping and Simulation: AI can simulate product prototypes, providing designers with insights into how different design choices affect functionality, aesthetics, and ergonomics.

Videography and Animation:

• Storyboard Generation: AI-powered tools like Plotagon and Wibbitz can generate storyboards from scripts, saving time and enabling filmmakers and animators to visualise scenes before production.
• Scene Recognition: AI can scan hours of video footage to identify specific scenes or objects, allowing video editors to locate and efficiently utilise the needed content.
• Character Animation: AI-driven character animation tools can create lifelike movements and expressions, reducing the manual labour required for animators and freeing them to focus on creative storytelling.

Game Design & Programming:

• Procedural Content Generation: AI algorithms can generate game levels, maps, and assets, introducing variety and unpredictability to gameplay and reducing the need for manual level design.
• Code Generation: Programmers can leverage AI tools like Intellicode to optimise code, improving efficiency and freeing cognitive resources for more creative problem-solving.
• Player Behavior Analysis: AI can analyse player data to identify patterns and preferences, informing game designers about player interactions and helping them design more immersive and enjoyable games.

Multimedia Arts:

• Artistic Collaboration: Artists can collaborate with AI programmes like AIVA to co-compose music that complements their visual art, creating immersive multi-sensory experiences.
• Inspiration from Data: Artists can use AI to transform data, such as climate data or stock market fluctuations, into visually striking artworks that convey complex information in accessible ways.
• Interactive Art Installations: AI-powered interactive installations can respond to viewers’ movements, emotions, or voices, allowing artists to create immersive and participatory art experiences.

For student artists and designers, AI amplifies our capacity to draw inspiration from our surroundings, experiences, and the work of others by introducing new sources of inspiration and streamlining the creative process. Moreover, AI’s ability to analyse vast datasets and generate novel ideas means it can assist in the creation of art and design that is truly unique. AI is ushering in a creative renaissance across these disciplines by automating mundane tasks, generating fresh ideas, and expanding creative horizons. In a world where innovation and originality are highly prized, AI can be a valuable ally for those seeking to push the boundaries of artistic and design expression. In our teaching, finding ways to embrace and make AI a positive experience that fosters more expansive learning rather than narrowing student learning is critical. AI seems set to play a growing role in our lives and the lives of today’s students.

Written by :

Maciej Sudra

AISA Tech Integration & Blended Learning Programme Coordinator