Despite adoption hurdles, healthcare is all-in on Generative AI

3) Use cases vary by technical experience and company size

GenAI’s applications in healthcare are diverse, with the most common uses being answering patient questions (21%), medical chatbots (20%), and information extraction/data abstraction (19%). Technical leaders, on the other hand, prioritize information extraction and biomedical research, indicating a strategic focus on gleaning data-driven insights and advancements.

Respondents foresee GenAI having the most significant impact on transcribing doctor-patient conversations, medical chatbots, and answering patient questions over the next few years. Smaller companies, in particular, have high expectations for these technologies, likely due to their agility and drive to gain a competitive edge.

4) Human intervention remains necessary 

Accuracy, security, and privacy are paramount when evaluating LLMs, with Technical Leaders placing even greater emphasis on these criteria. The survey reveals that cost is the least important factor, suggesting a willingness to invest in high-quality, reliable models. Major roadblocks to adoption include concerns about accuracy, legal and reputational risks, and the technology’s alignment with industry-specific needs.