AI-Related Diagnostic Errors: Emerging Risks for Malpractice Claims
Artificial intelligence (AI) is transforming healthcare—from radiology scans to predictive analytics. Yet while AI offers speed and efficiency, it also introduces new risks of medical error and liability. When a misdiagnosis is tied to an algorithm, the question becomes: who is responsible—the provider, the hospital, or the technology company?
At Lexcura Summit Medical-Legal Consulting, we help attorneys untangle these complex cases by analyzing medical records, identifying documentation gaps, and providing expert reports that account for both clinical and technological factors.
How AI Is Being Used in Healthcare
AI is increasingly integrated into patient care:
Radiology & Imaging – algorithms detect tumors, fractures, and hemorrhages.
Pathology & Lab Results – pattern recognition for disease markers.
Predictive Analytics – forecasting readmission risks and patient deterioration.
Virtual Triage & Chatbots – initial symptom assessments and referrals.
While these tools enhance speed, they are not foolproof. Misreads, data bias, or overreliance on software can lead to catastrophic outcomes.
Emerging Risks of AI-Driven Errors
1. Misdiagnosis or Missed Diagnosis
AI may fail to recognize subtle findings, such as small tumors or atypical presentations.
2. Algorithmic Bias
If trained on limited datasets, AI may underperform for certain patient groups—leading to inequitable care.
3. Overreliance on Technology
Clinicians may defer too heavily to AI outputs, ignoring their own clinical judgment.
4. Documentation Gaps
When an AI tool contributes to a decision, the reasoning behind the recommendation may be opaque, complicating litigation.
Legal Liability: Who Is Responsible?
In malpractice claims involving AI, multiple parties could be implicated:
Physicians – for failing to confirm AI results or override flawed recommendations.
Hospitals/Systems – for deploying AI without adequate oversight or training.
Software Companies – in potential product liability cases, especially if algorithms are defective or inadequately tested.
These cases require attorneys to prove causation—linking the AI-related error directly to the patient’s harm.
How Attorneys Can Counter AI-Driven Challenges
Request Comprehensive Records – including logs of AI recommendations, clinician overrides, and hospital policies.
Establish Standard of Care – showing whether reliance on AI met or breached accepted practices.
Leverage Expert Review – medical and technology experts can explain how AI contributed to the outcome.
Use Chronologies & Narratives – to clarify timelines where AI influenced clinical decisions.
Lexcura Summit’s Role in AI-Related Malpractice Cases
Our team of 200+ board-certified clinicians provides attorneys with:
Medical Chronologies – reconstructing events minute-by-minute, including AI input points.
Narrative Summaries – simplifying complex AI-clinician interactions for juries.
Life Care Plans – projecting future damages in cases of permanent harm.
Rebuttal & Defense Reports – addressing exaggerated or unclear claims tied to technology use.
With 7-day standard turnaround (2–3 day rush available), HIPAA-compliance, and nationwide reach, Lexcura Summit equips attorneys to handle the evolving intersection of healthcare, technology, and law.
Key Takeaways
AI is revolutionizing medicine—but it also creates new malpractice risks.
Attorneys must understand algorithmic bias, provider oversight, and documentation gaps.
Liability may extend beyond physicians to hospitals and AI developers.
Lexcura Summit helps attorneys build stronger cases with precise timelines, expert reports, and litigation-ready documentation.
Contact Lexcura Summit
Need support on a malpractice case involving AI-related errors? We can help.
Lexcura Summit Medical-Legal Consulting, LLC
📞 (352) 703-0703
🌐 www.lexcura-summit.com
