Imagine entering your symptoms into an AI chatbot and hoping for a reliable diagnosis, like in a sci-fi movie. However, a recent British study reveals that these tools do not even surpass a simple Google search when real patients turn to them. With 40 million daily users consulting ChatGPT for health advice, the excitement is growing, but the limitations are becoming apparent.
The AI is powering pharmaceutical research without valid miracle cures
By the end of 2025, scientists at Novartis used generative AI to generate 15 million potential compounds against Huntington’s disease, degraders capable of crossing the blood-brain barrier. Only 60 have been produced in the lab, leading to a promising lead in the optimization phase. A leap in virtual screening, but far from a ready-to-use medication.
Today, no AI discovery treatment has received FDA approval. In January 2024, the Boston Consulting Group counted 75 candidates in clinical trials boosted by AI, shortening preclinical stages from several years to 13-18 months and overall timelines by 30-40%. The pharaonic costs – $2.5 billion per approved molecule, with 90% clinical failures – persist. Raminderpal Singh, an expert, insists that the true measure is in phase III, justifying the industry’s entirely justified caution. An anonymous executive admits: “AI has disappointed us all over the past decade. We have seen failure after failure.” Novartis at the World Economic Forum in January 2026 acknowledges: “AI is not a magic wand. It is a tool to navigate complexity more intelligently.” Human biology remains a puzzle to be solved quickly, despite billions of sorted molecules.
Chatbots: the number one danger for amateur diagnostics
In January 2026, the ECRI placed AI chatbots at the top of the list of health technological risks, with cases of false diagnoses, unnecessary tests, or absurd anatomical inventions. Not classified as medical devices, they proliferate without safeguards.
Oxford researchers tested this in February 2026 through a randomized study on 1,298 volunteers, published in Nature Medicine. In isolation, AI identifies 94.9% of pathologies; when assisting patients, the score drops to 34.5%, equivalent to a basic web search. Rebecca Payne, an Oxford physician, bluntly states: “Despite all the hype, AI is simply not ready to replace the doctor.” Humans struggle to accurately describe their symptoms, unlike professionals who delve in with targeted questions. In mental health, the American Psychological Association warns that these tools are not suited, and Stanford shows biases against conditions like schizophrenia.
Where AI truly helps, far from the role of a virtual doctor
AI excels in image analysis to track certain cancers early, or in administrative tasks freeing up caregivers. It accelerates drug discovery, but struggle with nuanced clinical reasoning. Rebecca Payne succinctly sums it up: “Role of ‘secretary, not doctor’.”
Challenges are rising: 78 million affected by Alzheimer’s in 2030, a five-year survival rate for pancreatic cancer stuck at 13% despite overall progress to 70% for all cancers. Three years after the explosion of generative AI, millions still turn to these tools daily for a simple suspect headache.
In our geek era where AI promises fail-safe diagnoses like JARVIS, the reality is: powerful tools as a support, never as the solo act. It’s better to have an appointment with the doctor than to rely on a flawed quick fix.
