Genetic Counselors

AI is starting to help with data-heavy parts of genetic counseling, but it isn’t replacing counselors. For example, researchers have built machine-learning models that look at common lab test results and DNA variants to give a risk score for diseases ^[1]. In practice, some clinics use AI-driven software or chatbots to flag high-risk patients and even to draft visit summaries and educational materials.

One industry Q&A notes counselors are experimenting with AI “scribes” and risk-assessment tools to sort patients and prepare notes ^[2]. Studies show large language models (like ChatGPT) can answer genetics questions correctly most of the time, producing easy-to-understand info for patients ^[3] – though they can make mistakes or use confusing terms ^[3]. Importantly, tasks that need human empathy or judgment (for example, explaining a prenatal test or providing emotional support) still rely on the counselor.

In short, today’s AI is an assistant that handles routine analysis, paperwork, and teaching aids, while counselors continue doing the personal and complex parts of care ^{[4] [5]}.

Whether AI tools spread quickly in genetic counseling depends on costs, trust, and work needs. Right now, the counseling field is small but growing fast: the U.S. Bureau of Labor Statistics expects about 9% job growth by 2034 as genetic testing expands ^[6]. There is a big mismatch – one expert noted only ~4,500 U.S. counselors for millions of patients – so clinics feel pressure to scale up with technology ^[7].

In theory, AI could save money by automating paperwork (note-taking, report writing) and routine education ^{[5] [8]}. But genetic counseling involves very sensitive information, so safety and trust are key. Many people are wary of AI in their care: a survey found 4 out of 5 patients felt uneasy if doctors used AI for diagnoses without transparency ^[9].

Regulators will demand careful testing and human oversight (as McKinsey notes, AI errors mean clinicians must always check results ^[8]). Also, many counselors report little formal AI training now ^[10], so adoption may start slowly with tools for note-writing or data summaries, and ramp up only as professionals and patients gain confidence ^{[5] [8]}.