By Kristin Ryan, EVP, AI Transformation & Acceleration
AI is no longer simply changing how healthcare content gets made. It is changing how health information is found, evaluated, trusted and acted upon.
In January, I laid out nine shifts to watch across AI, search, social media and healthcare marketing. Six months later, the point is not to score the predictions. It is to understand where behavior and infrastructure have actually moved, and what healthcare marketers should do next.
The clearest midyear takeaway is that several trends are converging. Search is becoming conversational. Conversation is becoming action. Synthetic content is making credibility more valuable. And AI is moving beyond copy generation into the regulated workflows that determine how quickly marketing organizations can operate.
Search is becoming the answer and the agent
AI-powered search has moved firmly into the mainstream. Alphabet reported in July that Google’s AI Mode had surpassed one billion monthly active users. Google also said its AI search features continue to send billions of clicks to websites each week, complicating the idea that AI search is purely a “zero-click” story.
The more important change is where the decision happens. Google’s 2026 search updates emphasize conversational questions, multimodal inputs and agents that can help users move from researching something to getting it done.
For healthcare marketers, this means the website visit can no longer be treated as the center of every journey. A patient or caregiver may encounter a brand, provider, treatment or service inside an AI-generated answer and make significant progress before reaching an owned property, assuming they visit one at all.
Content therefore needs to work as answer inventory: clear definitions, evidence, visible authorship, medical review, recent update dates, structured FAQs and unambiguous next steps.
Measurement must evolve with the experience. Traffic and rankings still matter, but so do inclusion in AI answers, accuracy of representation, citation visibility, and branded search.
Conversational health is becoming expected
The shift from search boxes to conversational answers is particularly visible in health. OpenAI says more than 230 million people globally ask health and wellness questions in ChatGPT each week. Epic’s Emmie is designed to answer patient questions, surface information from medical records and take actions through MyChart. Hospitals are also launching their own patient-facing chatbots as new entry points into care.
That adoption comes with an equally clear warning. ECRI named misuse of AI chatbots the top health-technology hazard of 2026, highlighting the risk of inaccurate, misleading or inappropriately applied information. That means governed source content, privacy protections, defined confidence thresholds, safe-escalation pathways and handoffs to humans are necessary.
Pharmaceutical organizations also need processes for identifying potential adverse events and product complaints. Teams should monitor what the bot cannot answer, where users abandon the experience and which responses create safety or misinformation concerns.
The goal is not to automate every conversation. It is to resolve appropriate questions quickly while recognizing when automation should stop.
Synthetic media triggered a credibility reset
The synthetic-content trend has arrived, although not primarily through polished virtual influencers. The more immediate concern is deceptive content that borrows the authority of real healthcare professionals.
AI-generated videos have impersonated physicians to promote dubious products and health claims. In April, the American Medical Association introduced a policy framework calling for stronger protections against unauthorized physician deepfakes. YouTube has also begun automatically labeling content when its systems detect significant photorealistic AI use that a creator did not disclose.
The result is a broader credibility challenge: even authentic clinicians, patients and caregivers now communicate in an environment where audiences may question whether a person, voice or endorsement is real.
Healthcare creator programs need stronger identity and credential verification, clearer AI and likeness clauses in contracts, visible disclosures and documented sources. Brands also need rapid-response plans for synthetic misinformation: who verifies the claim, who approves the response and which credible clinical voices can be activated quickly.
Trust can no longer be assumed from appearance, title or follower count. It has to be demonstrated.
AI is moving from copy assistant to regulated workflow
Some of the most meaningful progress is happening behind the scenes. In June, Veeva acquired Copli and launched Falcon MLR, an agentic system designed to review promotional and medical content against approved labels, references and local regulations. The development signals a wider move from using AI to generate content toward using it to support the processes around content.
For healthcare and pharmaceutical marketers, the near-term value may come from identifying missing references, checking required language, anchoring claims, routing materials and flagging inconsistencies before formal review.
My recommendation is to start with a small number of painful, measurable workflows. Build human review into the system from the beginning. Measure cycle time, rework, first-time-right performance, content reuse and compliance outcomes, not simply how many assets AI helped produce.
Voice and visual interfaces are coming of age
Health information is also becoming less dependent on typing and reading. Google expanded Search Live, which supports conversations through voice and camera, to more than 200 countries and territories. OpenAI introduced real-time voice models capable of reasoning, translation and transcription during a conversation.
For healthcare marketers, an audio strategy can no longer mean only podcasts or streaming ads. Information needs to remain clear when it is spoken, heard, translated, photographed or interpreted through a camera-based assistant.
That raises practical questions about plain language, pronunciation, captions, multilingual support, accessible design and escalation. Voice can reduce friction for people facing literacy, vision, mobility or language barriers - but an incorrect spoken answer can also feel unusually confident and authoritative.
The AI-first operating model is still unfinished
Investment is moving faster than organizational readiness. Gartner reports that CMOs are allocating an average of 15.3% of their marketing budgets to AI, while only 30% say their organizations are ready to scale those capabilities.
That gap is visible across healthcare. Many organizations are AI-enabled in pockets but have not redesigned ownership, workflows, skills, data access and governance around the technology.
From my perspective, three questions remain especially important for the second half of 2026:
Will agents move from health information to health action? The stakes rise when an assistant begins comparing care options, selecting services, booking appointments or supporting adherence.
Will verification become infrastructure? Labels are useful, but healthcare needs durable ways to validate identity, credentials, consent and content provenance across platforms.
Will measurement catch up with the new journey? Marketing teams need to understand not only whether content generated a click, but whether it shaped an answer, earned trust and helped someone take an appropriate next step.
The first half of 2026 confirmed that AI is becoming a new decision environment, not simply another channel or production tool. The midyear mandate is clear: make content answerable, experiences actionable, automation governable and trust visible.
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