Your Next Pharma Website Visitor May Be an AI Agent

The customer journey is changing before the website visit

For years, the digital engagement model was familiar: a person entered a few keywords, compared search results, clicked a link, and explored a website. Pharmaceutical companies invested in search visibility and designed their sites to educate, build trust, and help that visitor take an appropriate next step.

Now, part of that journey can happen inside an AI-generated answer or an ongoing conversation. A person can describe a situation, ask follow-up questions, and request a simpler explanation without opening each underlying source. The expectation is moving from “show me where to look” toward “help me understand what matters.”

This is an extension of a broader evolution from typed keywords to questions, voice, images, and conversational discovery. In its May 2025 AI Mode announcement, Google described users asking longer, more complex questions and introduced an experience built around follow-ups and information gathered across multiple sources.

There is evidence that this changes website engagement. In a study of browsing data from 900 U.S. adults in March 2025, Pew Research Center found that traditional-result links were clicked in 8% of Google visits with an AI summary, compared with 15% without one. That is an observational finding from a specific period, not proof that AI caused the difference or a forecast for pharma traffic.

For pharma companies, this changes where engagement begins and how it should be measured. The brand website remains an authoritative destination, but it may also supply information to an experience another company controls.

From finding answers to asking an agent to help

The next step in this progression is delegation: “Now help me do something with what I have learned.” An AI answer summarizes information. An AI agent can also use tools to carry out a permitted task on someone’s behalf. These capabilities overlap, but they carry different responsibilities.

The early signals are clearer outside healthcare. Reuters reported in September 2026 that John Lewis attributed 2.5% of product searches to AI agents, up from 0.3% a year earlier. Harvard Business Review examines governance as commercial agents interact. These developments make delegation worth planning for; they do not establish that autonomous agents are a mainstream pharma channel.

Pharma should therefore prepare for three overlapping ways people may engage: visiting directly, learning through an AI-generated answer, and authorizing an assistant to retrieve information or request a service. Traditional search and human browsing will continue alongside these experiences.

What a future patient journey could look like

Consider a hypothetical person preparing for a conversation with their clinician. Instead of navigating several websites, they ask an assistant: “Help me understand this condition, prepare questions for my appointment, and find the manufacturer’s patient-support information.”

1. Understand

   The assistant gathers information from appropriate sources, explains it in plain language, and links back to current references. The manufacturer’s role is to make approved information understandable and accessible, with safety context intact.

2. Prepare

   The person asks follow-up questions and creates a discussion guide for their clinician. The assistant helps organize questions; treatment decisions stay with the patient and healthcare professional.

3. Connect

   With explicit permission, the assistant could help locate a support service or prepare a request for a human representative. Any submission involving personal information would require appropriate consent, identity checks, and confirmation inside an approved process.

This is an illustrative future experience, not a claim that manufacturers already provide it. It shows the potential value: less effort finding reliable information, better preparation for human conversations, and a clearer route to support.

A healthcare professional could similarly ask an assistant to locate current prescribing information and the appropriate medical-information contact. In both cases, the company’s contribution may begin before a person reaches its website—and continue through a controlled handoff when human expertise is needed.

The executive stakes: visibility, trust, and access

Visibility moves upstream. If approved information is hard to find or interpret, other sources may frame the conversation first. Being represented accurately in an answer becomes an additional objective alongside earning the website visit. Inclusion in an AI answer is neither guaranteed nor necessarily an endorsement.

Trust depends on context surviving the journey. A pharmaceutical claim may apply only to a particular indication, audience, geography, and use. A summary that preserves the benefit but loses the qualifier or safety information can change its meaning. The strategic asset is reliable information with its context attached.

Access can become easier—or more fragmented. A well-designed handoff could help someone reach an appropriate service with fewer steps. A poorly controlled one could send them to the wrong workflow, expose personal information, or leave a medical question without a qualified response.

Measurement needs a wider view. Visits and conversions still matter, but traffic alone cannot show whether information was understood correctly elsewhere. Add a repeatable review of answers to priority questions, the sources they cite, whether safety context survives, and whether visitors complete useful support journeys. Treat these reviews as sampled observations, not a complete measure of AI influence or clinical outcomes.

Google also advises evaluating the value of search visits beyond click volume. For pharma, the implication is to connect digital performance to reliable education and appropriate service access, while retaining conventional search and website measures.

The technology should serve a clear business boundary

The future website could serve two roles: a destination people trust and a controlled source of information and services that authorized assistants can use. That requires an explicit decision about what an assistant may read, what it may request, and when a person must approve the next step.

Think of the gateway in this diagram as the company’s controlled front door. It checks who is asking, what permission they have, and which service they may use. It keeps a record and routes consequential requests to the right people.

The enabling technology is taking shape. Adobe’s Developers Live program addresses customers and their agents, while its Adobe Experience Manager documentation describes standardized tools through which authenticated AI clients can access content. The underlying protocol, MCP, is a way for an assistant to use connected tools. Technical access to a content system does not by itself authorize an external customer agent to change or publish material.

Companies do not need to choose a protocol first. They need to agree on the customer need, the information that can be shared, the actions that require consent or review, and who is accountable when something goes wrong.

The regulatory distinction matters: FDA’s January 2025 AI draft guidance concerns support for regulatory decision-making, not promotional websites. Its risk-based approach is a useful design analogy here, not a requirement for this proposed architecture.

What leadership should ask for in the next 90 days

1. Choose one customer need worth improving

   Start with a bounded journey, such as helping people find approved patient-support information. Define the intended benefit and the activities that remain out of scope before selecting technology.

2. See the experience customers encounter today

   Ask teams to examine a consistent set of relevant questions across conventional search and AI experiences. Record which sources appear, what is missing, and where the answer could mislead. Establish a baseline before claiming improvement.

3. Make approved information easier to use correctly

   Bring content, medical, legal, regulatory, and digital teams together to connect claims with their references, safety context, audience, and review status. Prioritize useful answers over producing more pages.

4. Give the pilot a business owner and clear limits

   Assign an accountable sponsor, with medical, regulatory, privacy, security, and service teams defining the boundaries. Begin with retrieval of approved public information. Add delegated actions only after permissions, human handoffs, and failure handling are demonstrated.

5. Set the evidence required to expand

   Evaluate source accuracy, preservation of context, successful routing, and user effort. Agree on stop conditions, including unsafe summaries or failed escalation. Expand only when the pilot shows a useful benefit within those boundaries.

The immediate investment decision is a focused learning program using the existing digital estate. Its purpose is to find where changing search behavior affects a real customer need and what the organization must improve to respond responsibly.

“If the next customer journey begins inside an AI conversation, how will we earn trust—and help the person reach the right next step?”