Artificial intelligence is rapidly becoming part of contemporary design practice. For designers and design students, the important question is no longer simply whether AI is “good” or “bad,” but how we use AI professionally, responsibly, critically, and creatively. This distinction is especially important in Visual Communication Design, where AI use should not be confused with AI dependence.

It is understandable that students may have concerns when they see others using generative AI. Those concerns may involve fairness, originality, authorship, or the perception that AI gives someone an unfair advantage. But before judging a work simply because AI was involved, we need to understand how AI was used and what role it played in the design process. There is an important difference between AI-assisted design and using AI as a substitute for design. Using AI does not automatically make a design unoriginal, just as using Photoshop, Illustrator, photography, stock imagery, or 3D software does not determine the originality or quality of a design. What matters is the designer’s intellectual and creative contribution. AI can assist the creative process, but it cannot replace the student’s authorship, design thinking, and decision-making. Students remain responsible for the concept, visual direction, prompt strategy, selection, iteration, composition, typography, hierarchy, editing, and final execution.

Consider two students. One enters a simple prompt, accepts the first AI-generated image, places it into a layout with minimal consideration, and submits it as a finished design. Another begins with a developed concept, constructs and revises prompts, generates multiple possibilities, critically evaluates the results, directs further iterations, edits the selected imagery, and integrates it into a carefully considered composition. Both have used AI, but they have not demonstrated the same design process. The second student is exercising design thinking, visual judgment, critical selection, iteration, and authorship. AI participates in the process, but the student remains the designer.

AI is already part of professional creative practice. During the summer of 2026, while visiting family in China, I had the opportunity to visit the Shanghai offices of Ogilvy and McCann World Group, two leading global advertising agencies with strong U.S. roots. There, I spoke with a Creative Director, a Design Director, and an Account Director about how AI is being integrated into contemporary advertising practice. I specifically asked each of them how extensively AI was being used within their respective agencies, particularly what percentage of the design process and execution now involved AI. Their responses were remarkably consistent: both indicated that AI was involved in at least 60% of their design processes and execution. More importantly, they explained that AI use was not limited to creative teams, but had extended into marketing, account management, and marketing research.

Broader industry research reflects the same transformation. According to 2026 research from the Interactive Advertising Bureau (IAB), 83% of advertising executives reported that their companies had deployed AI within the creative process, compared with 60% in its 2024 study. IAB also reported in 2025 that 50% of advertisers were already using generative AI to create video ads, while 86% were using or planning to use it for video ad creative.

Figma’s 2025 research involving approximately 2500 designers and developers found that more than 80% believed learning to work with AI would be essential to success in their future roles, and 78% said AI significantly improved their efficiency. Yet only 32% said they need rely on AI output. This is an important distinction: professionals recognize the value of AI while also recognizing its limitations.

These developments in professional practice are also reflected in the University’s direction for teaching and learning. Faculty have received University communications encouraging us to integrate AI into our teaching where appropriate and to help students develop the knowledge and skills needed to use it effectively. Design education has a responsibility to prepare students for the profession they are entering, not the profession as it existed ten or twenty years ago. This does not mean abandoning fundamental design knowledge; as our tools become more powerful, understanding concept, typography, composition, hierarchy, color, visual language, audience, communication, and ethics becomes even more important. AI can generate possibilities, variations, and images, but generation is not judgment. The designer must evaluate what communicates effectively, determine which direction deserves development, and remain responsible for what is communicated and why.

Responsible AI use should therefore never mean lowering expectations for student work. If AI makes certain aspects of production faster, students should use that opportunity to explore more possibilities, make stronger decisions, and produce better work. A more sophisticated tool should lead to more sophisticated thinking, not less.

The question is not whether AI is good or bad. The question is how we use AI professionally. AI may generate the image, but the designer must develop the concept, define the visual language, set the creative direction, exercise critical judgment, and shape the final communication. I hope our students, as future professional designers or design educators, will understand this distinction and learn to approach AI not as a substitute for their creativity, but as a tool they can direct with knowledge, judgment, and purpose.