Authored by Serge Beckers, Managing Partner, Madchatter Brand Solutions in Wisse Kommunikatie
Three predictions for healthcare communication in the age of AI answers
Patients no longer ask their questions to Google, let alone to the GP, but consult ChatGPT or Gemini. Doctors use AI to search professional literature. Buyers to compare suppliers, directors to retrieve and interpret sector trends. AI is increasingly standing between the healthcare organization and the information it wants to retrieve and the people it wants to reach.
This creates an understandable unrest among many communication professionals, and raises the question of whether we should write mainly for ‘engines’ in the future. I think that this unrest is greater than necessary. After all, the ultimate goal of communication, including content created with AI, remains contact with people, not machines.
The AI engines are not your patients, doctors, customers or financiers, but are the channel to those people. It is still up to the patient to decide whether to trust a treatment and to the surgeon to determine whether a study convinces him.
Compared to other sectors, healthcare has an extra warning label with regard to AI. A wrong AI answer about a restaurant or a car brand is annoying. A wrong answer about a treatment, medicine or medical device can affect a life. AI may make medical information abundant, but healthcare runs more than other sectors on trust. From that field of tension, I predict three shifts.
1. From findability to reliable findability
Initially, AI-generated content and Generative Engine Optimization (GEO) will be in the spotlight. Organizations are going to mass-produce content in the hope that they will be mentioned by AI engines. The goal, human communication, is snowed under by technology. At least that’s how it was when SEO emerged.
But as GEO becomes established, the attention shifts from a lot of content to good content. In healthcare, this is faster and more energetic than in other sectors, because the goal is not for an AI engine to name you, but for it to use you as a reliable source. The winner is not the organization with the most content, but the one with the most quotable content.
And what makes content citable in healthcare? In particular, a clear evidence structure.
Online it must be unambiguously established what a treatment or product does, for whom and for what indication, what evidence there is, which claims are and are not justified, who the experts are and which independent sources confirm this. Peer-reviewed research, recognizable medical authors, collaboration with hospitals, universities and professional associations, consistent terminology and earned media in authoritative media reinforce each other in this evidence.
It is important to realize that there is no single seeker. A patient who asks what treatments are available for prostate cancer is looking for something different than a urologist who wants to weigh the evidence for a surgical technique, or a hospital administrator who is considering investing in a surgical robot to treat patients with prostate cancer.
Good GEO in healthcare therefore does not start from keywords or prompts, but from those different decision routes of the patient, doctor, purchaser, administrator, insurer and policymaker.
2. From content production to expert consultancy
AI helps you gather information faster and turn it into a story. A generic article about robotic surgery, cancer diagnostics or staff shortages is written in a few seconds. What AI does not provide, however, is the judgment of whether such a story is correct, relevant and responsible.
What claim does a doctor find credible? What nuance and personalized treatment does a patient need? Which wording is legally risky? Which journalist assesses a case or innovation objectively, and which goes for the scoop or sensation? How does a Dutch hospital communicate differently from a Belgian one? These kinds of questions cannot be answered without the combination of clinical, regulatory and local insights and people knowledge. It is precisely this combination of insights that becomes the premium.
Healthcare is also a highly regulated playing field, with guidelines and rules such as the EU AI Act, the MDR and IVDR, privacy rules and, in the Netherlands, a ban on advertising prescription-only medicines to the public. Of course, communication professionals do not have to become regulatory affairs specialists, but they do need to know where education ends and a medical or commercial claim begins.
The same requirement must be applied to GEO, because content intended to send AI responses about a treatment can unwittingly cross the line of advertising. We have to be very vigilant about that.
Meanwhile, AI use in healthcare is booming. WHO/Europe found that almost two-thirds of European countries are already using AI in diagnostics. Unfortunately, the WHO also had to conclude that only 8 percent have their own national AI strategy for healthcare. Technology is far ahead of the rules, and with it the urgent need for people who can assess what is responsible is growing.
With this need for ‘real opinions, insights and judgments’ in mind, the question to communication agencies changes from “Can you make this text?” to “Can you judge what we can say responsibly, to whom, on what basis and with what risk?”.
Content production is becoming a commodity, advice is becoming the revenue model. The importance of the large agency that has everything in-house for all possible content productions is decreasing, the importance of the specialist with insight and knowledge of the sector, region, culture and media is increasing.
3. From media monitoring to AI integrity
AI takes the edge off the information it spits out. To put it simply, AI engines condense vast amounts of information into the most likely answer. What is at the ends of the bell curve is thus lost. In addition, more and more AI-generated content flows back into the sources that AI relies on, which means that incorrect assumptions can also repeat and reinforce themselves.
This is a major point of attention in healthcare. Medical knowledge consists of nuance: a treatment works better in one subgroup than in another, an effect is statistically significant but clinically hardly relevant, results differ between experienced and less experienced centers.
An AI engine can quickly turn this into ‘studies show that treatment X is effective’. That is exactly where the risk arises, for the patient and for the reputation of the organization.
That is why nuance – applied in the form of well-thought-out content – is becoming a competitive advantage in healthcare. Organizations that clearly communicate what they know, what they don’t know, and what they are still investigating are considered more trustworthy than those that turn everything into firm marketing claims, and are also rated as more trustworthy by the engines.
Monitoring
Healthcare organizations have always kept track of what journalists and stakeholders said about them. A target group is now being added: the AI engine. AI monitoring is becoming as common as media monitoring.
By the way, you can’t correct an AI answer yourself. What you can do, however, is improve the sources on which AI is based; Such as there is your own information, that of professional associations, patient organizations and independent knowledge sources such as the earned media.
Ideally, monitoring and optimization become one cycle of measuring, detecting inaccuracies and gaps, improving authoritative information, and measuring again. Because AI answers vary by question, moment, and user, they are patterns over a longer time frame, not a snapshot.
The verdict
AI makes medical information easier to find, but it’s about whether it is trusted. AI makes content cheaper, but it’s about whether it offers real medical knowledge and insights. AI summarizes organizations and treatments, but it’s all about whether the summary is accurate.
I expect that in healthcare we will very quickly arrive at a solid GEO foundation that rests on evidence, supplemented with unique insights from people who know the profession. With one clear boundary: GEO in healthcare serves to make correct information findable, not to bend medical answers in one’s own direction.
Organizations that guard that distinction build the trust that healthcare is ultimately all about. Because no matter how smart the machines become, it is still people who decide who to entrust with their health.
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