Conversations around artificial intelligence in healthcare often focus on potential harms — privacy risks, biased algorithms or the fear of replacing human judgment. While these are valid concerns that deserve attention, there is an equally important question that is often overlooked: What are the ethical consequences of not using AI in healthcare when the tools already exist to save lives, reduce disparities and improve outcomes?
Let’s look at four areas where AI is delivering positive impacts in healthcare.
Improving Patient Outcomes
AI can help achieve improved patient outcomes by dramatically surpassing human diagnostic capabilities in critical areas. In 2025, Microsoft’s AI Diagnostic Orchestrator correctly diagnosed 85.5% of complex medical cases from the New England Journal of Medicine — cases so challenging they typically require teams of specialists. In contrast, experienced physicians working individually achieved only 20% accuracy on the same cases. This isn’t a marginal improvement, it’s a four-fold increase in diagnostic accuracy at 20% lower cost.
Increasing Operational Efficiency
In healthcare, where diagnostic errors affect millions annually and can mean the difference between life and death, the opportunity cost of not adopting AI is measured in preventable suffering and lost lives.
AI can provide healthcare systems with revolutionary operational efficiencies that directly impact patient survival. Medical professionals are drowning, spending nearly twice as much time on paperwork as with patients, according to a landmark Annals of Internal Medicine study. This isn’t just an inconvenience, it’s a crisis.
I’ve seen this firsthand through my work at Benzait, where we’re building AI agents for rural health systems like Newman Memorial Hospital in Oklahoma. These hospitals operate with skeleton crews serving vast geographic areas, yet their staff spends hours on patient scheduling, insurance verification, prior authorizations, referral coordination and appointment reminders — tasks that AI can handle in seconds.
Every hour our AI agents free up is an hour returned to patient care in communities where every provider counts. AI-powered ambient clinical documentation tools from companies like Nuance, Ambience and Suki can reclaim even more lost hours, capture conversations and generate clinical notes in real-time.
By refusing to embrace these technologies, we aren’t just perpetuating clinician burnout, we’re actively choosing a system where exhausted doctors make more mistakes, miss more diagnoses, and have less time for the human connection that heals.
Expanding Equitable Access to Care
AI can also expand access to specialist-level healthcare in underserved regions. In India and Thailand, where diabetic retinopathy threatens the vision of millions, Google’s AI can detect the disease with accuracy comparable to top ophthalmologists, specialists who are scarce in rural areas. In sub-Saharan Africa, where maternal mortality rates remain tragically high, AI-driven mobile apps are enabling prenatal monitoring that was previously unavailable. These aren’t incremental improvements, they represent fundamental shifts in healthcare accessibility.
Without AI, geographic location significantly influences the quality of care patients receive. The longer we delay deploying these proven tools, the longer these communities must wait for equitable healthcare access.
Additionally, AI gives us powerful capabilities to identify medical emergencies before they become critical. Healthcare systems generate vast amounts of data: vital signs, lab results and clinical observations that exceed human capacity to monitor comprehensively. At Johns Hopkins, the AI-driven TREWS system detects sepsis, a leading cause of hospital deaths, hours before human clinicians typically recognize it. Those hours can make the crucial difference between successful treatment and serious complications.
The ethical debate surrounding AI implementation in healthcare should not be restricted to fears of misuse. It must also address the consequences of delayed adoption.
Diagnostic errors remain a significant challenge in U.S. hospitals, affecting thousands of patients daily. Medical errors continue to be a leading cause of preventable harm, impacting hundreds of thousands of lives annually. While not all of these could be prevented by AI, evidence suggests that many could be reduced through AI-assisted decision-making. These examples represent real patients and families affected by potentially preventable medical events.
Ethics isn’t just about preventing harm, it’s also about preventing neglect. If AI can help save lives, reduce disparities and ease burdens on healthcare systems, then not using it carries its own profound ethical risks.
The real challenge is not whether we should use AI in healthcare, but how we can integrate it responsibly, transparently and equitably. Our goal should be ensuring all patients have access to the best possible care, enhanced by every proven tool at our disposal.
Ralph Whalen is the founder and CEO of BENZAIT, a healthcare IT consulting firm based in New Orleans specializing in data intelligence, AI governance and digital transformation. With extensive experience at the intersection of healthcare delivery, informatics, and operational strategy, he is recognized as a leader in advancing responsible innovation across complex health systems. He may be reached via email at ralph.whalen@benzait.com.
