Who’s Liable When AI Makes a Medical Mistake?

Exploring the legal risks, patient rights, and liability issues when artificial intelligence in healthcare goes wrong.

Is your doctor real… or are they an AI? 

No, no, we kid (sort of). Your doctor is a real person, not a very human-like robot—we haven’t reached that level of AI, yet. But although you might sit across from a human doctor in the examining room, that doesn’t mean they’re not using AI in your diagnostics or treatment. In fact, there’s a strong chance that AI plays a large role in your healthcare, whether you realize it or not. 

Artificial intelligence has taken on a major role in healthcare, especially in diagnostics, in recent years. From AI-powered imaging analysis to predictive algorithms that flag possible diseases, these tools promise faster, more accurate results. 

But as AI use grows, so have legal risks. Medical malpractice claims involving AI diagnostic tools rose by approximately 14% in 2024 compared to 2022, signaling a shift in patient expectations and the legal landscape.There’s value in AI for medical diagnostic purposes. AI tools can process massive amounts of data—including X-rays, MRIs, lab results, etc.—far faster than human doctors can. They can identify patterns in images, compare cases to vast medical databases, and flag conditions that might otherwise be missed. In some specialties, like radiology and dermatology, AI has matched or even exceeded human accuracy in controlled trials. This is important for two primary reasons; first, it can help diagnose and provide information to treat a problem quickly. Second, it can relieve pressure on overworked and understaffed medical facilities by taking some tasks off the human workers.

However, with any emerging technology comes some growing pains—AI is no exception. Here’s a look at why courts are seeing an increasing number of medical malpractice lawsuits related to AI diagnostics and treatments.

How is AI used in medical diagnostics?

1. Image analysis for radiology and pathology

An AI algorithm that is typically based on deep learning, can analyze X-rays, CT scans, MRIs, mammograms, and pathology slides to detect abnormalities like tumors, fractures, or internal bleeding. 

For example, Google Health has an AI model for breast cancer detection, in which trials show a higher accuracy rate than some human radiologists. PathAI is another tool that can detect cancerous cells in biopsy slides. These are valuable because AI can scan thousands of images quickly and flag subtle anomalies that the human eye might miss.

2. Screening and early detection tools

AI-powered screening apps and devices help identify conditions like diabetic retinopathy, skin cancer, and heart disease before symptoms become severe. For example, IDx-DR is an FDA-approved AI system that detects diabetic retinopathy from retinal images, without requiring a specialist to interpret results.

3. Clinical decision support

AI systems assist doctors in diagnosing based on patient symptoms, lab results, and historical health records. IBM Watson is an oncology tool used to recommend cancer treatment plans based on large datasets of medical literature. However, while AI can synthesize vast information, over-reliance without clinical judgment can lead to errors, and this is repeatedly appearing in emerging medical malpractice claims.

4. Predictive analytics

AI models are used in healthcare to use patient data to predict risks of certain conditions or complications for the purpose of enabling preventive care. For instance, algorithms used by hospitals can predict sepsis infections before symptoms become widespread or severe.

5. Point-of-care diagnostic apps

Some medical providers encourage patients to use various smartphone apps for quick diagnosis, particularly in remote or resource-limited areas where patients can’t get an in-person medical appointment. SkinVision is one example of an app that analyzes moles and skin conditions to assess the risk of melanoma.

Where are the biggest problems in medical AI?

• Missed or delayed diagnoses. AI can review a medical scan fast, but it could fail to detect a serious condition. This can lead to a medical malpractice claim if failing to provide early treatment results in progression of the disease. 
• False positives. A patient could be informed that they have a serious illness or condition. This could result in unnecessary stress, procedures, or treatment. 
• Overreliance on AI. Healthcare providers might lean too heavily on AI output without cross-checking or applying their own clinical judgment. Anything that’s red-flagged by AI should be independently verified by a human healthcare provider.
• Integration errors. Miscommunication between AI systems and electronic medical records sometimes leads to incorrect patient data being analyzed. Technology needs to be compatible with whatever technology it works with; if it isn’t, mistakes can happen.

Who’s liable for an AI-related medical malpractice claim?

Typically, if you’re the victim of medical malpractice, you’d file a lawsuit against the doctor or provider. And if you’ve suffered an injury because of an app or website, you could file a lawsuit against the company that owns the app. 

However, combining health care with AI presents different scenarios than traditional malpractice claims. There are a variety of potential defendants in a medical malpractice lawsuit when AI is responsible for the negligence:

• AI software developer. This would likely be a product liability lawsuit for defective design or inadequate warnings. 
• Hospital or clinic. The hospital or medical facility could be found liable for negligent implementation, training, or oversight of AI systems. 
• Third-party AI vendors. If another party provides cloud-based diagnostic services, they could be liable for negligence under some circumstances.

Courts are still unsettled on whether AI can be treated like a medical device, a service, or a “tool” used by a physician. This classification could change how courts handle future medical malpractice lawsuits involving AI.

How can medical providers reduce their risk of malpractice while using AI?

• A physician should treat AI as a supplement or adjunct to their judgment, but not a replacement 
• Hospitals should require ongoing training for providers who use AI tools
• AI developers must improve transparency to allow doctors to see how conclusions are reached 
• A patient should be informed when AI is used in their diagnosis

The law is catching up to a technology that is evolving at breakneck speed. But it’s not well-settled yet. As we know from the dramatic increase in numbers of AI-related medical malpractice claims, the stakes are high—and so is the need for clarity in both medical and legal standards.

Can you protect yourself from being a victim of medical AI mistakes?

As patients, we do have ways to take some control over our own healthcare. 

Here are a couple of things you can do in a medical environment to protect yourself if your provider is employing AI for your care:

1. Ask questions about the use of AI in your care

You can ask your provider questions like:

• Was this diagnosis or treatment recommendation provided by an AI system?
• Has this software or AI been FDA-approved or clinically validated?
• How is this result double-checked by a human doctor?

The more you know about how the AI is being applied, the better you can understand its limitations. Some AI tools simply assist doctors by flagging possible issues, while others can generate entire diagnostic suggestions. Understanding whether your provider is using AI as a helper or as a decision-maker can affect how much follow up you should demand.

2. Request a human second opinion

Never rely solely on an AI-generated diagnosis or treatment plan. Ask for another physician’s review, particularly if the diagnosis is serious or life-changing, or if there are multiple treatment options.

If the diagnosis is a particularly serious illness or invasive treatment, you might consider consulting a specialist at a different medical practice or facility for a second opinion.

3. Maintain copies of your medical records

In today’s world, most patients have an online medical chart (electronic medical record, or EMR) like MyChart or similar. Usually, you can access test results, reports, notes, and other information directly from your online portal. However, it’s a good idea to store these records yourself, also. You can often download records from the chart and store them locally on your own device.

These documents could be very valuable if errors were made and you need to challenge a diagnosis or take legal action.

4. Be alert for red flags

Red flags could include situations like if the AI diagnosis doesn’t seem to match your symptoms, if your doctor can’t clearly explain the AI’s recommendation, or if there isn’t human review before a course of treatment is prescribed. If any of these things happen, you can request additional testing or another opinion before proceeding with treatment.

Patients’ rights for AI in medical care

1. Right to informed consent

Under U.S. law, you must be informed about the nature, risks, and benefits of your treatment—including if AI technology is involved. The provider should explain what the AI does, its known accuracy rates or limitations, and whether human review is part of the process. You may refuse AI-assisted care if you prefer a human-only approach.

2. Right to a human review

While not yet a federal law, most medical boards and hospitals have policies that require physician oversight of AI outputs. Some states are considering rules to mandate human verification of AI diagnoses, especially in radiology and pathology.

3. Right to access your medical records

Under the Health Insurance Portability and Accountability Act (HIPAA), you have the right to see all test results, request copies of AI-generated reports, and ask for explanations of medical terms or codes. If an AI tool made an error, these records can help trace what happened.

4. Right to file a complaint

You may file medical board complaints against providers for negligence, regulatory complaints with the FDA if a medical device or AI system malfunctions, and HIPAA complaints if your data was mishandled by the system. In some instances, you might be able to join a class action lawsuit if multiple patients were harmed by the same AI tool.

5. Right to seek damages through a lawsuit

If AI-related medical malpractice caused you an injury or illness, you can file a lawsuit against the healthcare provider for negligent reliance on AI, the hospital or clinic for inadequate oversight, or the AI software developer for a product liability claim. A lawsuit can recover medical costs, lost wages and pain and suffering.

6. Right to know who is responsible

Even if AI is involved, the doctor is still legally responsible for your care in most jurisdictions. This means you can hold human decision-makers accountable, even when an algorithm is at fault.

Bottom line: If you believe that AI has negatively affected your medical care, you could be entitled to damages from a lawsuit. Contact a medical malpractice lawyer near you for guidance on how to navigate this complicated legal process.