AI’s Benefits and Risks for Healthcare

Artificial intelligence (AI) holds tremendous promise and potential peril. In few domains is this truer than healthcare.

We must remain vigilant to realize the promise of AI for improving health outcomes.   Without appropriate testing, risk mitigations, and human oversight, AI-enabled tools used for clinical decisions can make errors that are costly at best—and dangerous at worst. Absent proper oversight, diagnoses by AI can be biased by gender or race, especially when AI is not trained on data representing the population it is being used treat. Additionally, AI’s ability to collect large volumes of data—and infer new information from disparate datapoints—could create privacy risks for patients. All these risks are vital to address.

Yet at the same time—so long as we can mitigate these risks—AI carries enormous potential to benefit patients, doctors, and hospital staff. By one estimate, AI’s broader adoption could help doctors and health care workers deliver higher-quality, more empathetic care to patients in communities across the country while cutting healthcare costs by hundreds of billions of dollars annually. It could also help patients make more informed health choices by better understanding their health conditions and needs. While widespread AI adoption throughout the healthcare sector is a long way off, it is clear, that AI has the potential to positively impact healthcare outcomes and the lives of doctors and patients in myriad ways.

Each year, hospitals produce massive numbers of medical images—3.6 billion worldwide. AI is helping doctors analyze images more quickly and effectively, seeking signs of breast cancer, lung nodules, and many other conditions to reach more people with early detection than has previously been possible.

Today, developing new drugs takes years and costs over $2 billion on average. AI is streamlining development with its ability to match drug targets with new molecules that can treat and cure diseases, saving time and money—and translating to cheaper, better care for patients.

Clinician burnout is also a big challenge. On average, for every patient they see, hospital staff must fill out over a dozen forms. New generative AI applications can extract data from patients’ medical records, populate it instantly into forms, record notes from patient sessions, and speed and improve patient communications.