AI Resilience Report forPhysicians, Pathologists

Pathologists’ work is already being helped by AI tools. For example, new digital pathology scanners can take high-resolution images of tissue slides and use AI “to assist, augment and empower” doctors in spotting disease . These systems can highlight suspicious cells or patterns on a slide so a pathologist can review them more quickly and accurately.

Other AI tools work with pathology reports: one study found that a generative AI (like ChatGPT) could read free‐text cancer pathology reports and extract structured information almost perfectly, reducing time spent writing reports ^[1]. In each case, the AI speeds up routine parts of the job, but it does not make the final decision. Pathologists still check the results – for example, confirming any cancer diagnosis and deciding treatment – because medical problems are complex and need human judgment.

Tasks like supervising lab staff, talking with doctors or teaching students still rely on human skills (empathy, teamwork, experience) that AI cannot replace .

Some AI tools in pathology are now approved for use. The U.S. Food and Drug Administration (FDA) has allowed digital slide scanners for primary diagnosis and even approved an AI cancer‐detection algorithm for prostate biopsies . This means hospitals can use these tools under strict rules.

On the other hand, adoption is cautious. Advanced lab machines and AI software are expensive to buy and hard to integrate into a hospital’s workflow. Doctors and regulators also worry about trust and accountability – for example, who is at fault if an AI makes an error .

Because of this, many clinics start by using AI only as a “second reader” or a check, with the human pathologist making the real call. In time, as more evidence shows that AI can improve speed or accuracy, wider adoption is likely. For now, AI is seen as a helpful assistant, but the human pathologist stays in charge of the final diagnosis .