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Insight of the Day: Nearly two-thirds of consumers surveyed say they’d trust a diagnosis from AI over a human doctor


  • 64% of surveyed consumers trust AI diagnosis over a human doctor.

  • Younger generations are more trusting of AI in healthcare than older ones.

  • Medical imaging analysis is the most accepted application of AI across all generations.

  • Accuracy of diagnoses is the top concern regarding AI in healthcare, followed by data privacy/security and technical limitations.

  • Respondents are generally comfortable with AI and robotics in medical imaging but less so in invasive surgeries.

Key takeaway:

Consumers are increasingly open to AI in healthcare, especially for medical imaging, but concerns about accuracy and data privacy remain.


Growing acceptance of AI in healthcare, particularly among younger generations, but with persistent concerns about accuracy, privacy, and potential job displacement.


  • Public perception of AI in healthcare is shifting towards greater trust, especially in non-invasive applications like medical imaging.

  • Concerns about accuracy and data privacy need to be addressed to increase acceptance of AI in more sensitive areas of healthcare.

  • Different generations have varying levels of comfort with AI, suggesting a need for targeted education and communication strategies.

Implications for Brands:

  • Healthcare providers and AI companies should prioritize transparency and education to build trust in AI technologies.

  • Focus on developing AI applications with demonstrable accuracy and robust data privacy protections.

  • Tailor communication strategies to different age groups, addressing their specific concerns and highlighting the benefits of AI in healthcare.

  • Invest in training and upskilling healthcare professionals to work alongside AI tools, emphasizing the complementary nature of human and machine expertise.

  • Explore opportunities for AI in non-invasive areas like medical imaging, where consumer acceptance is higher, before gradually expanding to more sensitive applications.


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