What AI Experts Would Say to Professors Struggling With AI Emergence
Periods of meaningful change rarely arrive with instructions. More often, they arrive as pressure—questions we can’t quite answer yet, tools that work before we fully understand their implications (and before we trust the output), and a growing awareness that familiar practices may no longer be sufficient.
In the January 2026 issue of PRSA’s Strategies & Tactics, Alicia C. Aebersold, chief communications and membership officer at the American Psychological Association, makes this case in her article Why Passive AI Adoption Won’t Cut It in 2026. Writing to strategic communication leaders, she argues that the greatest risk organizations face is not misuse, confusion, or even resistance to AI—it’s passivity. Using AI just enough to signal relevance, while avoiding the harder work of rethinking judgment, workflows, and leadership responsibilities, creates the illusion of adaptation without the substance.
That diagnosis extends well beyond the communications profession. It names a dynamic that many professors should recognize immediately.
Higher education is not struggling because AI threatens the core purposes of teaching, learning, and scholarship. It is struggling because AI exposes how much of our daily work has become procedural—and how rarely we pause to examine whether our practices still serve the formation of thinking, judgment, and meaning. For educators, the question is not whether AI belongs in academic life, but whether we will engage it intentionally enough to shape its role rather than inherit it later.
Academic leadership has never been about chasing tools. It has always been about stewarding meaning—aligning knowledge, values, and practice in ways that serve students, disciplines, and the common good. AI does not change that responsibility. It intensifies it.
What follows translates this leadership insight into practical guidance for professors navigating the rapid emergence and escalation of AI—grounded not in enthusiasm or fear, but in discernment, experimentation, and professional stewardship.
7 Ways We Should Engage with AI
1. Embrace a Mindset Shift
Superficial use of AI (e.g., “I used ChatGPT to write this,” or adopting one tool as a badge) is not enough. Leaders and experts emphasize that effective use requires a change in mindset. AI should be seen as a collaborator that helps surface assumptions and frame problems more deeply, not just as a convenience. Feeling uncertain or overwhelmed is normal; ignoring AI isn’t.
2. Dive In and Experiment
AI fluency comes from doing, not just observing. Try different models—ChatGPT, Claude, Copilot—on real academic challenges: assignment design, framing learning objectives, or examining your assumptions. Experts encourage asking AI to push your thinking (e.g., “Where might my assumptions lead students astray?”) rather than just to automate tasks.
3. Provide Context and Teach the AI
Treat AI like you would a new colleague. Provide context: your teaching philosophy, course goals, student needs, and examples of past work. This helps the AI produce more relevant insights. Aebersold suggests giving AI enough “context, color, and consequence” so it understands what matters to you rather than operating like generic software.
4. Use AI to Amplify Your Strengths
AI excels at routine, tactical work—summaries, first-pass feedback, structural drafts—freeing faculty to focus on higher-order tasks: judgment, mentoring, strategic teaching, and learning design. Experts stress that AI doesn’t replace human strengths, but amplifies them when used purposefully.
5. Foster a Culture of Experimentation and Learning
Progress isn’t a single pilot project or a one-off workshop. Experts encourage regular experimentation, reflection, and shared learning. Begin small, reflect often, and share insights with colleagues. The gap between those who have practiced thoughtfully with AI and those who haven’t is already visible—and it will grow.
6. Demand Critical Engagement From AI
Tell AI explicitly to challenge your ideas, question your assumptions, and avoid flattering responses. This shifts its role from assistant to thinking partner. Aebersold recommends instructing AI to lean into hard questions rather than just produce agreeable or surface-level outputs.
7. Stay Connected and Share Perspectives
AI tools and best practices evolve rapidly. Engage with professional communities, conferences, and scholarly discussions to stay attuned to ethical, pedagogical, and technical developments. Collective learning accelerates individual readiness and avoids isolation.
Practically Speaking
- Avoid passivity: Rapid emergence of AI isn’t something to subtly track or lightly use—it’s something to engage with critically.
- Focus on thinking: AI isn’t a shortcut; it’s a stimulus for deeper reflection.
- Reframe teaching: Use AI to reduce administrative workload so you can strengthen mentoring, strategic thinking, and learning design.
As Aebersold asserted, the choice isn’t between resistance and enthusiasm, but between passive adoption and thoughtful engagement. Professors who lean into AI now, with intention and context, will not just cope—they’ll lead.
AI-assisted: Tools supported research, ideation, and drafting; human discernment determined the outcome and all meaning, interpretation, and conclusions.