AI Literacy in Higher Education: The Speed of Evolution In and Out of the Classroom
- Clark Boyd
- Nov 13
- 3 min read
Let’s say you’re 49 years old. That’s the median age for tenure-track faculty, according to CUPA-HR. You most likely began teaching in the late 2000s, shortly before online advertising revenues surpassed those of television. Social media was still an emerging channel. AI seemed like a futuristic technology, something out of The Terminator or The Jetsons rather than in your classroom.
Meanwhile, your students were in elementary school at the time. They grew up with, and on, the Internet. Two-thirds of them have used ChatGPT on assignments or exams. How do you go about teaching AI literacy in higher education to students who already know how to use the technology?
AI literacy in higher education isn’t about the tools. It’s about the skills that make them work.
It helps to remember that “literacy” doesn’t necessarily mean “fluency.” Just think about all the essays turned in by those two-thirds that were obviously authored by AI. Fluency is the difference between students using ChatGPT to do their work and using it to improve their own work. As future marketers, their careers depend on that distinction.
The speed of evolution in and out of the classroom
AI technology evolves incredibly quickly. Stanford University’s 2025 AI Index Report shows that from 2023 to 2024, AI’s performance dramatically improved, while the technology is increasingly embedded in everyday life. Business usage also increased by 42% year-over-year.
University governance preserves the high standards of academia. It also makes it difficult for marketing in the classroom to evolve as quickly as marketing in the real world. Between departmental committees, program reviews, and accreditation checks, adding a new required course can take three or four years. That’s par for the course in academia, but seemingly eternal in technology.
Four years ago, ChatGPT didn’t exist. Two years ago, it had 100 million weekly active users.
That massive number doesn’t include many marketing professors, who are less likely than marketers to be power users. The Digital Education Council’s 2025 Global AI Faculty survey found that 61% of faculty have used AI in teaching, 88% do so minimally.
Teaching, research, and admin work means you probably don’t have the bandwidth to stay on top of AI tools, which may change from month to month — if not sooner. However, the key to AI literacy in higher education comes down to a marketing skill as old as time: clear, strategic thinking.
It’s not enough to use ChatGPT. Marketing students must know how to use ChatGPT to supplement their work rather than do it. If they don’t, it will drastically hurt their chances with marketing hiring managers. While many professors fear that AI is eroding students’ critical thinking skills, King’s Business School research found that AI actually enhances critical thinking.
6 skills for teaching AI literacy in higher education
Another roadblock to teaching AI literacy in higher education is the vagueness surrounding the technology. Everywhere you look, there’s another promise with no context clues. “Supercharge workflows.” “Operationalize efficiencies.” “Do more with less.”
What does any of that mean? Who can say?
We created a guide for teaching AI to grad students and MBAs. We reframed foundational marketing skills, such as research and creativity, through the lens of AI. Purposely practical, the guide zeroes in on six specific skills:
Prompt engineering: Crafting clear, specific prompts to get relevant, accurate outputs — and not generic, jargony fluff
Customer research and audience targeting: Feeding AI diverse data and guiding it toward the insights AI can’t generate
Budgeting: Validating AI’s lighting quick budget analyses against students’ understanding of marketing fundamentals
Cross-channel strategy: Coordinating channels with sophisticated customer journey maps that remove the traditional guesswork
Content creation: Giving AI robust creative briefs that accounts for variables like brand voice documentations, visual identity standards, and approval workflows
Performance analysis: Understanding what success looks like across the entire campaign funnel, digging deeper into what worked
Each AI skill has its own deep dive, complete with six lessons to incorporate into your classroom. For example, the prompt engineering exercise has students start with using Gemini to create a generic Facebook ad. Once they’ve reviewed the ad for untrue or misleading claims, they create a more in-depth prompt for a more specific ad. The group discussion will likely shine a spotlight on how underwhelming the first ad is.