While many tech giants are investing in developing AI capabilities for the healthcare industry, key industry peers express skepticism about its efficiency and accuracy.
Has Generative AI come a long way? Has it successfully transformed the healthcare industry, or has it barely scratched the surface? The results from various researchers indicate strong disagreement in the healthcare industry as opposed to the aggressive development efforts by the big tech companies. Here’s what is happening there.
Generative AI is the latest evolution in the Artificial Intelligence landscape, and it has immense potential to reshape our professional and personal lives. Every day, it dwells deeper into our operations, comfort, and necessities, ensuring creativity, efficiency, and accuracy. However, the healthcare industry faces challenges that point AI’s perspective in the opposite direction.
The broad enthusiasm for integrating generative AI revolves around improving patient onboarding, optimizing records, generating patient status summaries, and seamless compatibility with IoT devices. While Gen AI can do much more than this, the current status of the capabilities in development shows negative data.
In a recent Deloitte survey, nearly 53% of US respondents showed disappointment regarding their expectations for Gen AI’s capabilities in healthcare. A little short of 50% of those participants said that they thought Gen AI would make healthcare more affordable.
OpenAI’s ChatGPT chatbot has been tested as a pilot for multiple healthcare organizations. The results of these pilot projects show glaring errors made by AI going up to 83% of the time. The commercially available Gen AI products are still struggling to manage medical administrative tasks like sorting patient priorities, summarizing patient status for medical professionals, and optimizing daily workflows.
One of the biggest areas AI lacks in healthcare is around handling complex medical queries or emergencies. The fact that Gen AI can be self-taught also opens the scope for self-righteous answers or illusion-induced responses. If AI remains limited. The latest clinical data cannot be fed in real-time to provide quick resolutions or support. Making it open to learning from the scrapes of the internet will lead to high inaccuracies in its answers. The medical industry cannot afford either of them.
