From a lack of funding to long wait times, healthcare systems around the world are facing immense pressure.
Patients are increasingly turning to AI for health information. An estimated 40 million people globally now use large language model tools (LLMs) like ChatGPT every day, looking for instant, personalised answers to questions ranging from symptoms and diagnoses, to comparing treatment options.
However, while access to this information has never been easier, trust in these resources grows increasingly fragile. Faced with a growing volume of conflicting information online, many patients are looking for answers, but remain uncertain about which sources to rely on, with 1 in 3 questioning the results LLMs provide if they’re not backed by scientific information.
This shift raises an important question for pharmaceutical companies: what happens when AI becomes a first source of information for patients and the healthcare professionals who treat them?
For years, these organisations have focused on ensuring accurate, evidence-based information is accessible through trusted channels. But, as AI platforms become a common starting point for patients and their health-related questions, visibility takes on a new meaning. Success will depend not just on publishing credible content, but on ensuring that this content is recognised, understood, and surfaced by the AI systems.
And this isn’t just confined to patients. Healthcare professionals are increasingly using AI tools as a first step for clinical information and to compare treatment options. For pharmaceutical companies, this raises the stakes even more. When AI shapes a clinician’s understanding of a therapy, any gap between an AI-generated answer and a product’s approved profile carries consequences for prescribing decisions and patient safety.
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