In conversation with the Institute for Excellence in Teaching and Learning – a series of thought-provoking exchanges designed to introduce new approaches to teaching that engage students and boost learning outcomes. The higher education landscape continues to evolve, and it becomes more important than ever to equip students with the real-world skills they need to thrive in a rapidly changing professional landscape.  

In Conversation with James Grady—Integrating AI into Teaching & Learning, and Identifying Ways to Build Collaboration & Convergence Across the Faculty Community 

James Grady is a designer, educator, and creative researcher who fosters interdisciplinary collaboration in design, technology, and performance. As an Assistant Professor of Graphic Design at Boston University, he works closely with faculty, students, and industry partners to explore how emerging tools and processes shape creative practice. His teaching emphasizes experimentation, authorship, and process-driven design, encouraging students to merge traditional and digital techniques in innovative ways. 

In addition to his academic work, James leads Design Axl, a design consultancy specializing in brand identity, digital experiences, and interactive storytelling. His projects span venture capital, technology, real estate, healthcare, and the arts, collaborating with clients to solve complex design challenges. His research and professional practice explore computational design, creative process, and the intersection of human and machine-generated work—an approach reflected in his latest talks and award-winning projects.

Q&A

James Grady: My talk, Creative Emergence: Integrating AI into the Design Process, explored how AI can be integrated into design education—not as a replacement for creativity, but as a tool to enhance exploration, authorship, and iteration. There’s a common misconception that creativity begins with a blank canvas, waiting for inspiration to strike. But great design is a process—one that unfolds through experimentation, constraints, and unexpected discoveries. AI fits into this process by acting as both a collaborator and a disruptor, challenging students to rethink their own creative methods. 

In my teaching, I use a structured Discover → Diverge → Design → Deliver model, which encourages both open-ended exploration and refined execution. One of the projects I shared in the talk, AI && You, asks students to blend handcrafted and AI-generated imagery to create a personal visual narrative. The process begins with self-reflection—students answer a set of questions about their design influences, personal history, and artistic interests. They then use AI tools like ChatGPT to uncover new references, generate keywords, and prompt further inquiry. 

The next phase is deliberately analog. Students create 12 handmade images using collage, drawing, or physical materials. Only after this do they generate AI-based visuals using tools like Firefly, MidJourney, and DALL·E. The goal is to blur the line between human and machine-generated work, finding relationships between the two. Through class discussions and pin-ups, students analyze patterns that emerge between their handcrafted and AI-generated images, using these insights to create a final printed publication that integrates both. 

This project reflects a larger philosophy: AI should be a tool for creative augmentation, not automation. By using AI in tandem with traditional techniques, students develop a sense of authorship over their work, rather than feeling like AI is dictating the outcome. Ultimately, this approach empowers students to critically engage with AI—seeing it not as a shortcut, but as a catalyst for new ways of seeing, thinking, and making. 

James Grady: This democratization of AI tools fundamentally shifts creative practice. When AI was primarily the domain of data scientists, its use in design and art required technical expertise. Now, with intuitive interfaces and generative models like DALL·E, MidJourney, and Firefly, artists and designers can incorporate AI into their workflows without needing deep coding knowledge. 

This accessibility expands possibilities for experimentation and interdisciplinary collaboration. It allows designers to iterate faster, explore unexpected directions, and uncover new visual languages. More importantly, AI is no longer just a tool for efficiency, it’s becoming a creative collaborator, pushing artists to ask deeper questions: What is authorship in an AI-assisted workflow? How do we ensure ethical use of these tools? How do we maintain creative integrity while leveraging machine-generated work? 

For students, AI opens up new ways of thinking and making. It encourages them to blend traditional and digital techniques, explore computational design, and engage with emerging media beyond static design. The key is to use AI as an extension of human creativity, not a replacement for it. 

James Grady: This debate has historical precedence. Every major technological shift—from the printing press, the camera, the desktop computer, and the internet—has been met with skepticism. Yet, in each case, new tools didn’t eliminate artists; they expanded the creative landscape. 

AI-generated art is real art, but it challenges traditional notions of authorship. When a designer inputs a text prompt and receives an AI-generated image, they haven’t created the image in the traditional sense, but they have orchestrated its creation. This is similar to conceptual artists like Sol LeWitt, whose wall drawings were executed by others based on his instructions. The key distinction is authorship and intent. 

Rather than replacing artists, AI is shifting their role. It automates aspects of production but elevates the importance of curation, storytelling, and synthesis. Artists who engage critically with AI—not as a shortcut but as a medium—will shape its creative potential. 

As educators, our responsibility is to prepare students to work alongside AI. This means teaching them to integrate AI into their creative practice while maintaining their unique voices, questioning its biases, and understanding its broader implications. The future of design isn’t AI replacing humans—it’s humans learning to harness AI with intentionality and critical thinking. 

James Grady: Interdisciplinary collaboration has been central to my work at BU, particularly through BU Spark!, where I mentor students at the intersection of design, technology, and innovation. Through the BU Spark! Technology Innovation Fellowship, I guide student designers working alongside developers to create digital products for real-world projects. This cross-disciplinary experience is invaluable, as it mirrors how creative teams function in industry—fostering collaboration between design, computation, and storytelling. 

Beyond BU Spark!, I have also worked with the College of Fine Arts (CFA), School of Theatre (SoT) to bridge design and technology through projects like Random Actor. This innovative software tool, which I co-initiated with Clay Hopper, Senior Lecturer in Directing, aims to revolutionize interactive media design. Random Actor allows users—including theatrical designers, artists, and other creatives—to build dynamic, immersive media environments without requiring extensive coding expertise. By integrating computational vision, projection mapping, MIDI control, and generative algorithms to create graphics into a user-friendly interface, the tool democratizes interactive design. While it has already been applied in theater and live performance, we are still exploring where it can have the most impact in the future, including areas such as deaf education and interactive learning experiences. 

These collaborations provide meaningful opportunities for students to engage in interdisciplinary problem-solving, equipping them with the skills needed for dynamic careers. At the same time, faculty gain new avenues for integrating design thinking into their research and teaching. Expanding these efforts will further strengthen BU’s culture of innovation, fostering new connections between disciplines and opening doors to unexpected applications. 

James Grady: Creativity isn’t confined to the arts—it’s embedded in how we approach problems, make connections, and envision new possibilities. One of the most effective ways to promote creativity at BU is by breaking down disciplinary silos. 

Design, at its core, is about problem-solving through a process of iteration and experimentation. If we integrate design thinking into different fields—whether engineering, business, or the sciences—it encourages more open-ended exploration and risk-taking. 

Faculty collaboration could take the form of co-taught interdisciplinary courses, cross-college projects, or design-led research initiatives. A shift in institutional culture—where creativity is seen as fundamental across disciplines—would enrich student learning and research at BU. Encouraging faculty from different domains to come together and experiment will drive this shift forward. 

James Grady: We are just at the beginning of AI’s impact on design and creativity. Right now, AI tools serve mostly as generative assistants—helping designers iterate on ideas, generate assets, or automate tasks. But in the near future, we’ll see more adaptive, co-creative AI models that respond dynamically to human input in real-time, making the creative process even more fluid. 

As AI becomes more integrated into creative workflows, the key challenge will be maintaining authorship and intentionality. I encourage students and faculty to see AI not as a shortcut, but as a conversation partner—one that challenges assumptions and unlocks unexpected directions. 

Ultimately, AI will continue to evolve, but human creativity—our ability to make connections, tell stories, and infuse meaning into our work—will remain irreplaceable.