How to Plan an AI Keynote for a University Faculty Event

At the California State University, a survey drew 94,000+ respondents, and 95% of them have used generative AI. A faculty event that opens with an explanation of what generative AI is starts a year behind the people in the seats. I advise on AI at the California State University system, which spans 22 universities and 470,000+ students, and I have delivered 310+ keynotes on 6 continents. This is how I would plan the AI keynote for a faculty event, working backward from the outcome to the speaker.

Set the outcome before choosing the speaker

A faculty event has one scarce resource: a few hours of shared attention from people who seldom sit together. Write the outcome as something that exists when the last session closes. A draft course-level AI policy for each department qualifies. So does a ranked list of three assessment redesigns, or a shared definition of acceptable AI use in student work. A keynote that cannot name its contribution to that outcome is entertainment with a fee attached.

Sequence the day as keynote, working session, follow-up

The keynote sets common language. Faculty arrive with different levels of experience: one professor has rebuilt a syllabus around AI tools, and a colleague down the hall has never opened a chatbot. Forty minutes of shared framing puts both in the same vocabulary and gives the provost's office a reference point for later policy work.

The working session produces the output. Each department meets for 60 to 90 minutes with a one-page template: what students may do with AI in this course, what they may not do, and how the instructor will tell the difference. The follow-up closes the loop within 30 days, when each chair reports what changed. In my experience that third step decides whether the event leaves a trace by spring.

A faculty keynote is judged by what each department commits to the following week.

Choose a speaker who understands how universities decide

Universities decide through shared governance: faculty senates, curriculum committees, and academic freedom norms that no executive can override. A speaker who treats a campus like a corporation loses the audience within the first ten minutes. Ask each candidate how the talk accounts for those structures and who on campus owns each decision it raises.

My own preparation comes from two sides. I spent nearly two decades at Cisco, where I helped shape a $1.1B innovation portfolio and established innovation centers in 14 countries on 5 continents, which taught me how large organizations absorb change. My advisory work with the California State University system puts me in front of the same governance questions faculty ask every semester.

Five questions to put to any speaker

1. What will faculty hold at the end of the keynote that they can use in a syllabus?
2. How does the talk treat differences between disciplines, such as nursing, composition, and engineering?
3. What is the speaker's position on instructor discretion over AI use in a course?
4. What does the speaker provide for the working session and the 30-day follow-up?
5. What work has the speaker done inside an institution, beyond the stage?

A speaker who answers all five with specifics has prepared for your campus. Vague answers mean the same talk gets delivered everywhere.

Underneath all faculty AI planning sits the question of how quickly skills lose value. My forthcoming book, The Great Relearning, takes that question up for the workforce, and it shapes every faculty session I design: the goal is a campus that can relearn on a schedule it controls.

Alex Goryachev is a WSJ-bestselling author and AI keynote speaker who advises universities and enterprises on AI decisions their teams can act on.

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