"AI health search is really becoming a patient's entry point." -- Bev Ho, The Next Practice

Patients don't Google their symptoms the same way they did two years ago. They ask ChatGPT. They talk to Perplexity Health. They use AI to compare treatment options, check eligibility, and decide whether to raise their hand for a clinical trial -- all in a single conversation.

That shift is already affecting enrollment. And most trials aren't ready for it.

In this 45-minute webinar, The Next Practice's Colin Foster and Bev Ho walk through why the majority of clinical trials are functionally invisible to AI search, what it takes to change that, and how to audit your own trial's visibility today.

What You'll Learn

Why AI has compressed the patient decision journey. Before AI search, a patient researching a trial navigated five-plus websites over days or weeks. Today, that same journey happens in one conversation thread -- from symptoms to eligibility to next steps. If your trial isn't surfaced in that conversation, it doesn't exist for that patient.

The two trust systems AI uses to surface your trial. Colin breaks down machine trust, what makes AI confident enough to cite your trial, and patient trust, what makes a candidate take action. Both require your content to answer questions in plain language, not clinical protocol language.

"The whole patient journey has been collapsing from weeks... to just one compressed discovery conversation." -- Bev Ho

The AI Trust Ladder. ClinicalTrials.gov is the apex of authority for every LLM. From there, third-party citations, sponsor pages, and recruitment sites either reinforce or undermine your trial's credibility. Most teams invest at the bottom of this stack, paid media, without building the top, and AI ignores them as a result.

The First Answer Readiness Framework. This is the core of the webinar: a seven-layer structure for ensuring your trial content is citable in AI answers. It covers question territory, structured eligibility in plain language, trust signal architecture, context precision, design philosophy, machine readability, and category context.

"The idea here isn't to rank in search results. It's really to be cited in AI answers." -- Colin Foster, The Next Practice

A live audit. Bev runs a real clinical trial site through EnrollIQ's AI visibility scoring tool, showing exactly how bot accessibility, content delivery, content structure, and citation readiness get evaluated, and where gaps appear.

A five-point action plan you can start today. No budget required. Search for your own trial the way a patient would. Read your ClinicalTrials.gov entry as a patient. Write two sentences describing your target candidate without clinical jargon. Audit terminology consistency across all your digital properties. Confirm that every patient-facing page clearly explains what happens after someone expresses interest.

AI health search is not a future consideration. One in four ChatGPT users already submits health-related prompts every week, according to OpenAI. The platforms built to serve those queries are looking for authoritative, consistent, patient-readable content. The trials that provide it will show up. The trials that don't, won't.

Watch the webinar to see exactly where most trials fall short and what to do about it.