In May 2025, a Dubai doctor created a ripple in social media by posting that he hoped to get a job in McDonalds as his diagnostic expertise is already automated. He wrote “I am about to lose my job. This is scary because I developed my skill over 20 years”. Dr. Mohammad Fawji Katranji had examined an X-ray of the chest and diagnosed pneumonia after encircling the concerning area. Moments later, he ran the same X-ray through an AI diagnostic system to find that AI correctly identified pneumonia and marked the same part of the image. Apart from that, AI also flagged another area overlooked by the doctor. The doctor posted these results online and concluded “Now you don’t need professional eyes to look at these X-rays”. He jokingly added that he was applying to McDonalds soon and hoped there is an opening.
When a professional expertise of 20 years is replicated by an AI diagnostic model instantly, it’s a ground-breaking revolution in any industry. The most important part of healthcare industry is diagnosis. The treatment methodology, drug prescriptions and advice to patients are all a direct result of the medical condition a doctor diagnoses. When a diagnosis requiring painstaking study and experience is delivered accurately within seconds by an AI tool, the healthcare professionals are bound to feel insecure.
The AI takeover of health sector
As per the World Economic Forum (WEF), about 4.5 billion people lack access to basic healthcare services. AI can bridge that gap through automation in key areas like fracture detection, X-ray analysis, diagnostics and documentation. The white paper of WEF states that AI’s adoption in healthcare is “below average”. It points to higher potential for AI integration into healthcare infrastructure to better serve the customers. Apart from delegation of repetitive tasks, AI outperforms human service in key areas like brain scans. There is an AI software that examines brain scans at twice the accuracy of a professional. Alongside the accuracy of AI model, it also identifies the timescale within which the stroke happened. AI can spot more bone fractures than professionals ensuring lesser suffering for the patients when doctors can’t find the cause of pain. Interestingly, AstraZeneca, a leading pharma company claims that its new machine learning tool can detect early signs of more than 1000 diseases even before symptoms are experienced by the patients. Pre-empting a disease or early detection of life-threatening diseases can be the biggest boon in the medical sector. AI can be a life-saving tool to detect warning signs early and stop the medical condition from exacerbating.
Customized medical chatbots
As per a study in America, the general large language models (LLMs) like ChatGPT, Claude or Gemini weren’t capable of providing sufficient relevant or evidence-based answers to medical questions of clinicians. The generic LLM’s proved inadequate for a specialist task. Specialised LLM’s are the future so that output relevant to industry expertise is produced. Microsoft has announced Dragon copilot, an AI tool that can listen to, and create notes on, clinical consultations. Google has a slew of AI models tailored to shoulder the administrative burdens in healthcare. A German AI platform Elea has successfully cut testing and diagnosis time from weeks to hours. Delegation of time-consuming documentation and administrative tasks to AI tools will improve productivity and ease the patient experience leaving more time for patient-doctor interaction. An AI application that takes notes on your doctors appointment, records patient’s medical history and schedules doctor appointment will ensure higher accuracy than human hand scribbling through the notes. A case study on digital patient platform Huma revealed that digital interfaces can reduce readmission rates by 30% and time spent reviewing patients by 40% resulting in reduced workload for healthcare providers. With multiple specialized tools for specialized tasks, AI LLM’s are set to change healthcare sector forever.
