The AI Marketing Syllabus I'd Teach this Fall

By Clark Boyd, co-founder of Novela.

Two years ago I put a slide of Google results in front of a marketing class, and a student stopped me. "Erm, we don't really google things any more. We ask ChatGPT. We search TikTok."

He was half wrong and I enjoyed saying so. Billions of people still google, and search keeps growing. But his half was real: he and his classmates start on ChatGPT, TikTok and YouTube, and my slides mentioned none of them. My syllabus was five years behind reality.

I've spent fifteen years in digital marketing, and before Novela I was on the hiring side of it. At one company we had a hundred open graduate roles, and I spent that year measuring what graduates arrived knowing against what the job needed. Then I taught, and saw the other end of the pipeline. What was being taught was years behind the work I'd been hiring for. That gap is why Novela exists. It was wide five years ago. Consider it now.

Here's the course I'd teach this fall if I were back in the classroom. You can have the full week-by-week version, and if you send me your syllabus, I'll map it to your course; details at the end.

Why not just add an AI week?

Because AI rewrote the job twice over. It changed how the work gets done: research, copy, analysis and reporting now run through AI tools, and employers expect graduates who can drive them. And it changed how customers find brands: ChatGPT, Gemini, Perplexity and Google's AI Overviews now answer the questions that used to return ten blue links, and whether a brand appears in those answers is a marketing problem nobody owned three years ago.

A course that ignores this sends students into interviews confident about a world that's gone. SEO as it stood in 2015, a keyword list and ten blue links, is the clearest casualty, and it's still what most textbooks describe. An "AI week" bolted onto that course fixes nothing. The spine has to change.

The two changes are one loop. Marketers use AI to make the work, and the AI engines judge that work when they write their answers. Most AI marketing courses teach the first half, the tools. GEO consultants sell the second half, the visibility. The job is both, so the course is both.

The cost is smaller than it sounds. About two-thirds of a good existing course survives intact.

How I'd structure it

Fifteen weeks, four parts: foundations, search, social and B2B, lifecycle. AI runs under every week rather than getting one of its own. On a shorter term, compress the foundations and merge the paid weeks; the shape holds.

One warning about the order: it isn't the funnel. Five years ago we taught search as the bottom, capturing demand, and social as the top, meeting strangers. A customer now finds a brand on TikTok, asks ChatGPT to compare it with two rivals, checks Google reviews and buys through an Instagram ad in the same afternoon. Every channel runs the whole journey, so the course teaches each one that way, and the journey map from week 4 gets used every week after.

Foundations

Week 1. How AI rewrote marketing. The shock first: students have to see that search became answers before any tactic makes sense. Huang and Rust's research-strategy-action framework gives the subject an academic spine.

Week 2. Working with AI as a marketer. Prompting, drafting, analyzing, and judging the output: where AI is wrong, and where the call has to stay human. Every later week assumes these skills.

Week 3. Ethics and responsible AI. Bias, disclosure, manipulation, on both sides of the loop: what you produce with AI, and what you do to shape its recommendations. It sits in the foundations because students carry it into every decision after.

Week 4. The AI-era customer journey. Lecinski's Zero Moment of Truth, updated for the moment that now happens inside a machine-written answer. Students map a real purchase across the new touchpoints. Every channel week hangs off this map.

Search

Week 5. SEO in an AI world. Crawling, authority and intent still matter; zero-click results and AI answers changed what winning looks like. Students use AI to audit a real site and draft the fixes.

Week 6. GEO: getting cited by AI. The week almost nobody teaches, and the one interviewers are starting to ask about. Students create content with AI, then measure whether the engines cite the brand and describe it accurately. The whole loop in one week. Anchor it in Dubois and colleagues' Harvard Business Review work on how language models misread brands.

Week 7. Paid search, and ads in AI answers. When you can't earn a position, you rent one. Students run the established version, paid search, and study the new one: Perplexity has begun placing ads inside AI answers, and the other engines will follow. Teach the trade-off; the interfaces will have changed by graduation.

Week 8. Integrated search and measurement. Students allocate one budget across SEO, GEO and paid, then defend the split. This is where the judgment lives.

Social, content and B2B

Week 9. The future of social media. Grounded in Appel and colleagues' research agenda rather than this month's platform panic. AI now shapes what gets made and what gets surfaced.

Week 10. Organic social and content. Students produce a content plan with AI tools, then confront the hard question: when anyone can generate ten posts, why does one considered post win? Sequencing and focus beat volume, and they see it in their own output.

Week 11. Paid social. AI-generated creative, tested against real audiences, with a budget and consequences. Funnel balance over one-off wins.

Week 12. B2B and the buying committee. Most marketing graduates end up in B2B; most courses barely mention it. The committee, the 95-5 problem of out-of-market buyers, and AI doing the account research and personalization.

Lifecycle and measurement

Week 13. Email, automation and CRM. The channel that still pays the rent. Lifecycle flows, segmentation, deliverability, and the AI tools now drafting and timing the sends.

Week 14. Analytics and attribution. Why the numbers lie: standard analytics can't see AI's influence on a purchase, and a marketer who can't explain that to a finance director loses budgets they earned. Students use AI to run the analysis and build the argument.

Week 15. Capstone. A full strategy across the loop, built with AI, defended aloud. AI writes a passable strategy document now, so the exam is the defense.

What actually changes in your course?

Read the list again: you already teach most of it. Consumer behavior, positioning, email, paid trade-offs, B2B, analytics, a capstone, all intact. What's new is the search arc, weeks 5 to 8, taught against the surfaces as they exist now, plus the working-with-AI foundation.

The bigger change is assessment. Every week should contain a decision made under uncertainty, because a student who made the call and got it wrong learned more than one who read the chapter alone. The record of those decisions is better evidence of competence than an essay, and accreditors keep asking programs to evidence exactly that.

Why give this away?

Because we build the practice layer for it. Our B2B and social simulations already have AI tools embedded; students use them to do the work, the way they will on the job. The one we're building now covers the search arc: students create content with the AI tools inside the simulation, and the scoring shows whether the AI engines surface the brand. Both halves of the loop in one exercise. We work with the Digital Marketing Institute and Jellyfish on the industry side, and our simulations run at Columbia, Kellogg, INSEAD, Oxford and fifty other institutions.

We also hand you the entire course, ready to teach: simulation, slides, assignments, readings, teaching notes, assessment. The upgrade costs you a few decisions, and it shouldn't cost you your summer.

Most marketing simulations students play today wouldn't have prepared them for the industry of five years ago, let alone this one. The category needs an overhaul. We intend to lead it.

Email me and I'll send the full week-by-week syllabus the same day, readings, activities and assessment included. Or send me your current syllabus and I'll reply with a review: where AI fits, what to keep, what to change, mapped to your weeks. Either way it's clark@novela.academy, or the form at novela.ltd/ai-marketing-syllabus. And if you think I've got a week wrong, tell me. A syllabus for a field this young gets built through argument, and it'll be better for yours.