By Rajiv Mahale

AI has revolutionized the healthcare industry in numerous ways. From models that identify patient risk for early interventions to machine learning algorithms that detect patterns humans miss, AI's capabilities often seem limitless. Newer generative AI (GenAI) tools hold immense potential to improve healthcare. GenAI supports clinical decision-making at the point of care and aids in creating personalized treatments. It also works behind the scenes, enhancing administrative efficiencies in data management, billing, payment processing, and workflow automation.

The innovation and potential AI holds has prompted healthcare leaders to significantly increase their budgets for adopting the technology, with a reported 300% rise. As the pressure increases to implement AI, so do the risks – and in an industry like healthcare, the stakes are too high to get it wrong. Organizations that rush into AI adoption may wind up with technology that is untested, inadequate, biased, or even harmful to patients.
Poor or inadequate AI tools can lead to several negative consequences, including restricting access to care, financial repercussions and liability, damage to organizational reputation, and depletion of patient trust. When irresponsible AI use rises to the level of patient harm (as we saw recently with claims that AI technology is adversely affecting Medicare Advantage patients), we may quickly see a shift away from excitement about the potential to reactionary rules and laws that restrict the use and innovation of AI. Ensuring the safety and trustworthiness of healthcare AI solutions is of utmost importance to mitigate the potential fallout of unethical or irresponsible use.

AI is most beneficial when used as a support system for clinical teams, not as a replacement for human capabilities. Payers and providers can only realize AI's positive outcomes and change the trajectory of the healthcare system by embracing responsible AI.

How to ensure ethical and responsible AI in healthcare
How can healthcare organizations integrate AI seamlessly and responsibly while prioritizing patient safety and well-being alongside data security? It requires a focused commitment to ethical use at every step of the AI development and deployment journey. Organizations that use or develop AI should define guiding principles that every team member fully understands and agrees to abide by. Broad themes for these principles should include:

Artificial Intelligence Homepage