As artificial intelligence (AI) takes on a larger role in diagnosing, monitoring, and even treating patients, the landscape of medical malpractice law is shifting. In 2025, the integration of machine learning algorithms into healthcare has introduced new legal questions: Who is at fault when AI makes an error? How do you prove negligence when a diagnosis is generated by software? And how are courts handling claims that involve complex digital systems rather than solely human practitioners?

This article breaks down how AI is reshaping medical malpractice lawsuits—from liability concerns to evidentiary challenges—and what patients and legal professionals need to know in this evolving space.

What Qualifies as Medical Malpractice Today?

At its core, medical malpractice still involves a healthcare provider breaching their duty of care, leading to patient harm. But with the rise of AI-assisted decisions, that definition is being reexamined. Traditionally, malpractice hinged on a human making a poor judgment—misreading a scan, overlooking symptoms, or providing incorrect treatment. Now, AI is often the first point of analysis.

In 2025, medical malpractice claims can involve:

• A misdiagnosis provided by an AI tool or algorithm
  
• Delays in care caused by reliance on automated decision systems
  
• Treatment plans developed based on flawed data interpretation
  
• Failure by providers to question or override AI-generated suggestions
  

These scenarios raise a key legal challenge: if a doctor follows an AI-generated diagnosis that turns out to be wrong, is the doctor at fault—or is the software developer responsible?

Who Is Liable: Doctors, Hospitals, or AI Developers?

Determining liability in an AI-influenced malpractice case isn’t straightforward. The human provider, the hospital system, and the software creator might all be involved, and their responsibilities are often intertwined.

Here’s how liability might break down in 2025:

• Physicians: If a doctor blindly accepts AI recommendations without applying clinical judgment, they can still be held liable. Courts continue to expect a human oversight component.
  
• Hospitals and Healthcare Facilities: Institutions that implement AI tools without proper vetting, training, or safeguards may bear responsibility. If a hospital deploys an unreliable algorithm or fails to update it regularly, they may be seen as negligent.
  
• Software Developers: While medical device manufacturers and software firms have historically avoided malpractice liability under most state laws, that’s changing. Plaintiffs are increasingly filing product liability claims against developers whose AI systems malfunction or misdiagnose.
  

The legal field is catching up to technology. Some states have begun drafting statutes that specifically address AI-related medical injuries, blurring the lines between medical malpractice and product liability.

AI Errors Are Difficult to Detect—and Prove

AI tools often work as black boxes. They process vast amounts of data and output conclusions, but the internal logic behind those decisions may be opaque even to the physicians using them. This poses a major problem for patients and their attorneys.

To bring a successful claim in 2025, plaintiffs need to show:

• The AI tool gave an incorrect or unsafe recommendation
  
• A reasonable provider should have recognized the error
  
• That failure to intervene led directly to harm
  

However, proving that an algorithm’s decision was unreasonable can be challenging. These systems are often trained on large data sets that aren't publicly accessible, and proprietary protections can limit what evidence is available. Subpoenaing algorithmic decision logs and metadata has become a regular part of discovery, but courts are still divided on how far that access should go.

The Standard of Care Is Evolving

One of the most significant shifts in medical malpractice litigation is the changing definition of the standard of care. Historically, this standard was based on what a competent healthcare professional would do in a similar situation. In 2025, that standard increasingly includes an expectation that clinicians know how to use AI tools appropriately—and when to ignore them.

Attorneys must now ask:

• Was the AI system FDA-approved or reviewed by a regulatory body?
  
• Did the provider use the tool within its intended purpose?
  
• Were there known limitations or biases in the AI model?
  
• Did the clinician rely too heavily on automation rather than medical training?
  

Courts are also beginning to consider whether a reasonable provider in today’s tech-integrated environment should have used an AI system—and whether failing to do so could itself be a form of negligence.

Real-World Impact: Claims Are Rising

Data from 2024 showed a 14% increase in malpractice claims involving AI tools compared to 2022. The majority stemmed from diagnostic AI used in radiology, cardiology, and oncology. In particular, missed cancer diagnoses by machine-learning software have become a central focus in several high-profile lawsuits.

In response, many malpractice insurers have revised their policies. Some now include AI-specific exclusions, while others require physicians to undergo AI-training to remain covered.

Key Trends in AI-Related Malpractice Claims:

• Growing reliance on AI in high-risk areas like surgery prep, stroke detection, and sepsis alerts
  
• Lawsuits involving telemedicine platforms powered by symptom-checker algorithms
  
• Disputes over whether developers or physicians bear responsibility for flawed outcomes
  

Navigating the Legal Landscape: What Patients and Lawyers Should Do

If a patient believes they’ve been harmed due to an AI-related error, the legal approach should be multifaceted:

• Request all medical records, including logs from AI systems and decision-support tools
  
• Investigate whether the provider used the AI tool properly or ignored signs of failure
  
• Consider adding the software vendor or hospital system as co-defendants, depending on the facts
  

Lawyers handling these claims should also work with expert witnesses familiar with medical AI systems, particularly in radiology and diagnostics. Understanding how these tools are trained, validated, and used in practice is critical to building a strong case.

Conclusion

As AI becomes more deeply embedded in the practice of medicine, it’s reshaping not only how care is delivered but also how malpractice cases are litigated. The legal system is adapting to a world where accountability may rest with more than just the provider in the exam room.

In 2025, patients and attorneys must navigate a more complex web of potential liability, technical barriers, and evolving standards of care. While AI offers enormous promise for improving outcomes, it also demands greater vigilance—both in the clinic and in the courtroom.

Injured? The Office of Brandon J. Broderick, Personal Injury Lawyers, Can Help

Navigating medical malpractice claims can be challenging. Fortunately, you don't need to do it alone. The experienced lawyers at Brandon J. Broderick, Attorney at Law, are available 24/7 to help you understand your legal options, gather necessary evidence, and build a strong case to secure the settlement you deserve.

Contact us now for a free legal review.