Designing with AI: Why Instructional Designers Still Need Human Mentors

Melody Buckner, Associate Vice Provost, Digital Learning and Online Initiatives, University of Arizona

Late one afternoon, an instructor met with an instructional designer to discuss a new online course. Before the meeting, the instructor had used an AI tool to generate a course outline, draft discussion prompts and suggest assessments. “This saved me hours,” the instructor said. “But I’m not sure if it’s actually good.” Together, they reviewed the AI-generated materials. The instructional designer asked questions about course outcomes, student needs and learning goals. They discussed how some assignments could better support student engagement and how others might be redesigned. By the end of the conversation, the AI-generated outline had become a thoughtfully designed learning experience. Moments like this illustrate the evolving role of artificial intelligence in course development. AI can accelerate the process, but it cannot replace the human mentorship that helps educators design meaningful learning experiences.

Artificial intelligence is rapidly changing how instructional designers approach their work. Instructors are beginning to experiment with these tools when designing curriculum, and students are increasingly using AI as a study aid or writing assistant. This emerging ecosystem means that AI is influencing course design while also reshaping how instructors teach and how students engage with learning. AI can function as a brainstorming partner, surfacing pedagogical strategies drawn from vast datasets and quickly producing drafts of instructional materials that can then be refined. Yet while AI can accelerate the design process, it cannot replace human guidance. Mentorship remains one of the most powerful mechanisms for cultivating professional growth, pedagogical judgment and confidence among instructional designers.

Instructional design is not simply a technical process of assembling course components. It involves thoughtful reasoning about how people learn, how technology shapes learning experiences and how pedagogical decisions affect diverse students. One framework that supports this work is Universal Design for Learning (UDL), which emphasizes designing learning environments that provide multiple means of engagement, representation and expression so that all students can access and demonstrate learning.

AI tools can generate activities aligned with learning objectives, but they rarely explain the pedagogical reasoning behind those suggestions or how they might support diverse learners. For example, an AI tool may produce a discussion prompt aligned with a learning outcome, but it cannot fully articulate how that activity might support students with different learning preferences, language backgrounds, or accessibility needs.

“AI can accelerate the process, but it cannot replace the human mentorship that helps educators design meaningful learning experiences.”

Mentorship helps bridge this gap. Experienced instructional designers guide newer designers in understanding the deeper pedagogical principles behind design decisions. Through mentoring conversations, designers learn not only what design choices to make but also why those choices matter. Mentors often introduce frameworks such as UDL to help designers anticipate learner variability rather than reacting to barriers after they emerge.

University teaching and learning centers play an important role in facilitating this mentorship. As many organizations shifted toward remote work, many of the informal mentoring interactions that occurred naturally in shared office environments disappeared. Teaching and learning centers had to rethink how mentorship could be sustained in distributed teams.

One instructional design team responded by reimagining mentorship in a virtual environment. The initial approach paired senior designers with newer team members in a traditional hierarchical mentoring model. While well-intentioned, this structure proved less effective than expected. Instructional designers often come from diverse professional backgrounds—including teaching, technology support, multimedia production and research—and their career goals vary widely.

The team eventually shifted toward a more flexible, collaborative approach centered around a program called Summer Camp. Rather than relying solely on formal mentor pairings, Summer Camp created opportunities for designers to learn from one another through shared activities, project discussions and informal conversations. A particularly successful element was a series of gatherings called Campfire Chats, where team members discussed design challenges, exchanged ideas and reflected on emerging issues such as supporting faculty experimentation with AI.

This collaborative model helped recreate the sense of connection lost during remote work. Mentorship became less hierarchical and more community-driven, allowing designers to seek guidance from multiple colleagues depending on the project context. One important lesson from this initiative was that organizational culture does not develop automatically in virtual environments. It must be intentionally cultivated. Through regular conversations, shared professional development and collaborative problem-solving, mentorship reinforced collective values around accessibility, student engagement, faculty partnership and the thoughtful integration of emerging technologies such as AI.

As AI continues to reshape instructional design workflows, mentorship will remain essential for helping designers, faculty and students navigate this evolving landscape. AI can accelerate tasks, but it cannot replace the human relationships that foster professional growth and critical reflection. Ultimately, the success of instructional design teams and the courses they help create will depend not only on the technologies they adopt but also on the relationships they build. In an age of rapidly advancing artificial intelligence, human mentorship may be the most important technology supporting teaching, learning and student success.

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