Why AI Literacy Is Foundational, Not Optional, for Higher Education

Brett Christie, Ph.D.
VP, Educational Innovation & Inclusivity

As AI becomes an increasingly integrated part of our daily lives, classrooms, and workplaces, one thing is certain: we don’t need to turn every course into a course about AI. Nor do we need to embed AI tools or experiences into every assignment or learning outcome. But we do need to recognize that teaching and learning are now happening within a world shaped by AI.

This doesn’t mean every educator needs to become an AI expert. In fact, most won’t, and shouldn’t. There will always be a place for specialists who want to explore AI at a deep level. But for the majority, what’s needed is something far more attainable: baseline AI literacy. A shared, foundational understanding that allows educators to make informed decisions, adapt reasonably to new tools and trends, and model responsible, ethical use for their students.

A Manageable, Meaningful Layer of Professional Learning

Rather than creating an overwhelming or exhausting learning curve, AI literacy should be viewed as an intentional layer of professional learning. It is within reach, deeply relevant, and immediately applicable.

That reality requires something deeper than tool familiarity or trendy experimentation. It requires a shared foundation of AI literacy. An ability among faculty, staff, and institutional leaders to navigate this new landscape confidently, ethically, and effectively. It’s not about chasing the latest technology. It’s about preparing people to make thoughtful, informed decisions that serve students while protecting the integrity of education.

AI Literacy as a Collective Institutional Priority

At the recent AAC&U AI Leadership Symposium, where campus leaders gathered to explore the future of AI in higher education, this message came through clearly: AI literacy is not optional. It is a critical capacity that institutions must develop collectively, not only to keep pace but to evolve with intention.

At Alchemy, we believe AI can be a powerful enabler of more inclusive, engaging, and responsive learning. But only when it is used by people who understand its risks, its potential, and its proper role in the learning process.

Building Confidence and Capacity, Not Complexity

We’re not asking every educator to become an AI expert. That is neither realistic nor necessary. What we are advocating for is broad, baseline readiness. A shared language and framework that allows faculty across disciplines to:

• Make pedagogically sound choices about if and how AI fits in their courses
• Uphold ethical standards for student work and academic integrity
• Understand how AI tools impact assessment, equity, and learner agency
• Feel empowered, not overwhelmed, by the evolving role of technology in education

This is exactly the purpose behind the free AI Literacy Micro-Credential I developed in my role at Alchemy. To equip educators with the capacity to lead, not just react. And to do so in a way that reflects our commitment to thoughtful innovation in teaching and learning.

When campuses foster this kind of shared literacy, they don’t just prepare faculty. They build a culture that is proactive, principled, and prepared for what comes next.

AI in the Background, Not the Spotlight

AI doesn’t need to be the center of every course, but it is now at least a part of the context for all learning. The sooner we build capacity to operate within that reality, the better we can support the educators and learners who are navigating it every day.

If you’re interested in learning more about this topic, join us for our upcoming webinar, “AI Literacy at Scale: A Strategic Imperative for Higher Education” with Chris Hakala, Ph.D. of Springfield College.