Your students are already using AI. Here's what that means for your program.

CHELSEA WAGNER, MS CGC | JULY 21st, 2026

If you direct, teach, or supervise students in a genetic counseling program, I'd bet money most, if not all, of your students are using AI right now. For board prep. For summarizing papers. For first drafts of assignments. Some of them are doing it well. Some are trusting a hallucinated citation and don't know it.

The question in front of you isn't whether students should use AI. That decision has already been made with the accessibility of tools left, right, and upside down. The real question is whether they learn to use it critically inside your program, or whether they figure it out alone, badly, after they graduate and whether or not there’s a patient on the other end.

I've talked to a lot of program directors over the past year, and the honest reaction is usually some version of: I know I should be addressing this but I don't know where to start. I'm more afraid of getting it wrong than of getting it done. When given the choice, we’d likely all choose a controlled, methodical, evidence-based, well-studied slow integration of a new technology into our practice. So if you feel some apprehension to the wild-wild-AI-west - that’s totally reasonable. 

But here’s the thing, not teaching about AI has its own risk. Waiting until the schedule allows or there is a miraculous decrease in the amount you have to teach to students in their short graduate training years is a fever dream. Not incorporating AI fluency now leaves students to develop their own AI “literacy” - perhaps without the guardrails or critical thinking skills necessary to "first, do no harm”.  

Here's the reframe I'd offer. You are not being asked to become an AI expert. You're being asked to do the thing your program already does well: teach critical evaluation. Your students already learn to appraise a paper, question a source, spot bias in a study, and hold uncertainty without collapsing it into false confidence. Those are exactly the skills that make someone good with AI. The subject is new. The muscle isn't.

What does it look like in practice? A few things I've seen work.

Name it out loud. Just acknowledging that students use these tools, and that the program has a point of view, changes the culture. Silence reads as "figure it out yourself."

Teach the failure modes before the use cases. Students should understand hallucinations, bias, and privacy risk before they're taught a single prompt. Skill without judgment is a dangerous combination.

Make verification a graded skill. The valuable competency isn't generating an AI output. It's evaluating one. An assignment where students critique an AI-generated variant summary teaches more than one where they produce it.

Set a real privacy line. Students need to know, concretely, that pasting a real clinical note into a consumer tool is a problem, and why. That single lesson prevents a lot of future harm.

The reason we built GC x AI Foundations is that most program directors don't have time to build this from scratch, and they shouldn't have to. It's a modular, ready-to-teach curriculum: 12 mini-lectures, facilitator guides, activities, and assessment questions, mapped to ACGC practice-based competencies so it slots into what you already do. You don't rebuild a course. You integrate a set of pieces.

I'm not going to pretend a curriculum solves everything. Your program's context is yours. The right integration depends on where AI fits in your existing courses, your institution's policies, your students' starting point. What a shared foundation does is save you from inventing the core content alone, and give you something rigorous to adapt rather than a blank page and a deadline.

Our first cohort opens August 17, built specifically for programs that want to introduce this responsibly for the coming academic year. Founding partners get a hand in shaping where the curriculum goes next, which matters to me, because we’d rather build this with you rather than without you. 

Whether or not GC x is the right fit for your program depends - but the underlying point stands. Your students are already in this. The kindest, most responsible thing a program can do is meet them there with structure, guidance, and the skills needed to navigate something new.