Why trust is becoming pharma’s most important visibility metric

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.

Trust is becoming the new battleground

For many consumer brands, the challenge presented by AI is visibility. For pharmaceutical companies, this extends further to encompass credibility too.

Unlike consumer brands, however, pharmaceutical companies operate in highly regulated environments where inaccurate information can have real-world consequences for patients.

This sector functions in a trust economy. Scientific evidence, regulatory compliance, and expert validation underpin every communication. Historically, pharmaceutical companies exerted significant control over their information through corporate websites, awareness campaigns, and carefully regulated communications, but AI is changing all of that.

From medical publications and healthcare organisations to patient forums and wider online discussions, AI systems now generate responses by drawing on multiple sources from across the internet. This means authority is no longer something that can be built through owned channels alone. Even the most accurate and evidence-based content can be diluted by competing narratives elsewhere online. Gaps, inconsistencies, and outdated information all negatively impact the chances of brands being featured in LLMs.

As a result, pharmaceutical companies need to think beyond website optimisation and consider the wider information ecosystem surrounding them. Consistency across owned, earned, and third-party channels is vital since AI systems evaluate the collective picture, not a single source.

The key question is no longer whether your website ranks for a keyword, but whether AI systems recognise your organisation as a credible source worth referencing.

Pharma needs new measures of influence

If AI is altering how patients discover information, it’s also changing how influence is measured. This exposes another challenge for the pharmaceutical sector, as many organisations still gauge success using traditional metrics such as clicks and site traffic designed for a different era of search.

Patients using LLMs like ChatGPT are receiving answers before they ever visit a website. An individual might ask an AI assistant about treatment options for a chronic condition, the side effects of a medication, or what symptoms warrant a conversation with a healthcare professional. Similarly, healthcare professionals are asking AI to summarise evidence, compare therapies, or check dosing before consulting traditional references. The key question for pharmaceutical companies therefore becomes what information AI is using to answer said questions.

Pharmaceutical companies need to understand how they are being represented within AI-generated responses. Are evidence-based sources being cited? Is treatment information being described accurately? Are patients and healthcare professionals encountering trusted information first? Is the organisation appearing as part of the answer at all?

This is about more than marketing effectiveness. In healthcare, visibility within AI environments has implications for public understanding and patient outcomes. If AI systems surface incomplete or inaccurate information, the consequences extend far wider than just this sector alone.

The pharmaceutical industry therefore faces a new responsibility. Alongside producing trusted information, organisations must ensure that information is structured, discoverable, and authoritative enough to be recognised by the AI systems increasingly shaping patient decisions. This will ensure that misinformation isn’t being spread.

The future of healthcare visibility will not be defined solely by who ranks highest in search results. It will be defined by who is trusted enough to become part of the answer when patients and healthcare professionals start searching in the first place.

About the author

Chris Pearce is group managing director at Greenpark. He brings a wealth of leadership experience, having previously headed up well-known digital agencies including MRM Worldwide (UK) Ltd, part of McCann Worldgroup, and TMW Unlimited, as well as founding two integrated agencies himself (Blowfish Ltd and HHP&B). At Greenpark, Pearce leads on client satisfaction and product innovation, focusing on driving growth and transformation, and building integrated teams that align content, SEO, tech, and AI. He is well placed to explain what it takes to build future-ready organisations and how to lead effectively in an AI-driven landscape, sitting on the DMA's Customer Engagement Committee and being a part of the DMA AI task force, helping to shape the ethical use of AI for marketers.