By Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)
Most of us in education and learning design know the signs of burnout: feeling drained, irritable, or overwhelmed. The revisions never end, inboxes overflow, and the to-do list keeps expanding. Some of us withdraw, neglect self-care, or lie awake at night thinking about what’s still unfinished.
My turning point came in the early hours of a summer morning in 2023. After days of crafting syllabi and course communications for my first semester as an assistant professor, I was running on empty. Out of sheer fatigue, I pasted a draft email to my teaching assistants into ChatGPT and asked for a clearer version. The revision came back sounding like me, but sharper and more confident.
That simple act revealed something powerful: AI could do more than save time. It could help me refocus on why I teach instead of drowning in the how.
Designing Courses with AI, Not for AI
In the months that followed, I began exploring what responsible integration could look like. I designed a workplace-assessment course that used AI as a design and learning partner. Rather than treat AI as a standalone topic, I wove it into the experience through branching scenarios, AI-generated case studies, and interactive activities built with H5P.
Students didn’t just use AI; they used it to think critically. When practicing data analysis, they generated practice datasets with ChatGPT clearly labeled as simulated. This opened meaningful discussions about authenticity and integrity: When does AI support learning, and when does it cross the line?
That exercise reminded us that AI can’t replace honesty or judgment, but it can strengthen both when handled transparently.
From Solo Experiment to Shared Practice
Then, at a regional education conference, I met others who were asking the same questions. We compared notes on what worked and what didn’t, guided by ethics rather than hype, and returned to our institutions eager to experiment further.
Back on campus, I led sessions on AI-enhanced curriculum planning and assessment, showing how chatbots, AI tutors, reading assistants, and text-to-video platforms can streamline design. Colleagues wanted to discuss not just what tools to use, but how to frame AI for learners.
The most meaningful result wasn’t technology adoption, it was connection. Conversations that began with skepticism evolved into curiosity and collaboration. We began to see AI not as a disruptor but as a curriculum companion that could amplify the creative, human side of teaching.
Lessons for Sustainable Teaching
Two years of experimentation led to five practical lessons that apply in any learning environment, from higher education to corporate training.
1. Start Small & Low-Stakes
Use AI where impact is immediate but risk is minimal: editing an email, refining a rubric, or brainstorming discussion prompts. Small wins build confidence and model curiosity for learners.
2. Prioritize Ethics & Transparency
Discuss AI use openly with students and stakeholders, and explain the “why” behind policy decisions. For example, generating a mock dataset for practice may be acceptable, especially when textbooks offer similar exercises that are less personalized to a learner’s field of study. However, asking AI to produce an untouched research paper risks learning deficits and plagiarism. Model attribution, clarify boundaries, and encourage reflection on when AI supports learning and when it hinders it.
3. Design for Dialogue
AI should provoke inquiry, not replace it. Give students structured opportunities to reflect on their experiences with AI as a learning companion. Ask them to evaluate AI-generated material, compare perspectives, and refine their own thinking through class discussions, brief surveys, or short reflective interviews. Building these moments into the course design makes feedback on AI use part of our ongoing critical practice.
4. Blend Human & Machine Strengths
Have learners apply concepts to real-world contexts, connecting theory to lived experience in ways AI cannot replicate. Live discussions, peer interviews, recorded presentations, and peer review pair naturally with AI-supported research and analysis. The blend keeps critical thinking alive while easing repetitive tasks.
5. Share What You Learn
Exchange successes and challenges with colleagues. Host a monthly “AI share-out” or create a team chat channel dedicated to exploring new tools. Collaboration builds confidence, reduces anxiety, and creates a stronger foundation for ethical AI use across your organization.
Re-Energizing the Work
Exploring a new wave of educator-focused AI tools and professional training rekindled the curiosity that first drew me to teaching. Each new learning opportunity offered fresh ways to create, experiment, and connect, reminding me that AI isn’t a threat to creativity but a catalyst for it.
Across 16 years in education, I’ve led professional development, coached peers, and built curricula. Yet AI feels categorically different. It has restored efficiency without sacrificing authenticity, allowing more time for mentoring and meaningful design work. Burnout didn’t vanish overnight, but the work felt purposeful again.
Guiding the Future
AI is no longer an experiment at the edges of learning, it’s embedded in our professional reality. As new platforms evolve, educators and designers have a choice: resist or lead.
Leadership doesn’t mean blind enthusiasm; it means curiosity with integrity. The question isn’t whether to use AI, but how to use it to strengthen human connection and learning outcomes.
If burnout is the problem, thoughtful integration may be part of the solution. My first experiment, a single late-night email, opened the door to new energy, efficiency, and joy. For anyone feeling the weight of the workload, that same door is waiting.
Image credit: LaylaBird
