AI Is Entering a Deeper Application Phase: Healthcare, Marketing, and Brand Visibility

AI đang bước vào giai đoạn ứng dụng sâu hơn: y tế, marketing và khả năng hiển thị thương hiệu

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Nội dung
  1. Google pushes AMIE from diagnostic support to health condition management
  2. MarTech: AI is both the problem and the solution to the content challenge
  3. Adobe launches Brand Visibility to track brands across AI surfaces
  4. When performance marketing exposes its weakness: don’t just manage the dashboard
  5. A perspective for the Vietnamese market
  6. References

AI is moving quickly from a “content creation tool” to an operational infrastructure role across many industries, from healthcare and content marketing to brand visibility measurement. For Vietnamese marketers, this is not just a story about new technology, but also a signal that the way users search, evaluate, and make decisions is changing right before our eyes.

Four recent international stories paint a fairly clear picture: AI is moving into higher-value touchpoints, while businesses must learn how to manage content, brand, and measurement efficiency in an environment increasingly shaped by large language models.

Google pushes AMIE from diagnostic support to health condition management

In a newly published study, Google said AMIE — its AI healthcare system — is being expanded from a diagnostic support role to helping manage conditions and monitor health. Rather than focusing only on a single consultation, the new direction emphasizes the ability to accompany users over the long term as they deal with health issues.

Google pushes AMIE from diagnostic support to health condition management
Google’s AMIE medical AI system is being expanded to support patients over the long term, moving beyond its initial diagnostic support role. Photo: Marketing365.

What stands out is that this study reflects the broader trend of next-generation AI: it does not stop at answering a question, but takes part in decision chains and continuous monitoring. In healthcare, that places very high demands on reliability, safety, and how the system interacts with people.

For marketers, this news points to something even more important: AI is shifting from “producing outputs” to “managing journeys.” As technology enters longer, highly personalized processes, the real value is no longer just response speed, but the ability to maintain context, consistency, and trust. Source: Google AI Blog.

MarTech: AI is both the problem and the solution to the content challenge

MarTech highlights a familiar paradox of the AI era: marketers are drowning in content, but AI itself can be the tool that helps them escape that overload. In the interview, Erica Gunn — CMO of Canto — emphasizes the context in which AI becomes both the cause and the solution to the content asset management crisis.

MarTech: AI is both the problem and the solution to the content challenge
As AI helps produce content faster, businesses face the challenge of managing and controlling a rapidly expanding digital asset library. Photo: Marketing365.

From a practical standpoint, the biggest issue is no longer simply “creating more content,” but organizing, reusing, controlling versions, and ensuring brand assets do not become fragmented. When AI helps production move faster, content volume can easily grow beyond control if the business does not have a strong management system.

This is a point Vietnamese marketers should pay special attention to: investing in AI cannot stop at tools for writing articles, generating images, or creating captions. Without content governance processes, AI can increase chaos instead of efficiency. Source: MarTech.

Adobe launches Brand Visibility to track brands across AI surfaces

Adobe announced a new solution called Brand Visibility, part of the Adobe CX Enterprise ecosystem, designed to help businesses ensure their brands are seen, trusted, and chosen across “AI surfaces” — meaning the surfaces where large language models and AI tools synthesize information for users.

Adobe launches Brand Visibility to track brands across AI surfaces
Adobe’s Brand Visibility solution helps brands track their presence directly within AI-generated answers. Photo: Marketing365.

This is a notable move because it shows traditional SEO is expanding into a new era: businesses not only need to appear on search results pages, but also need to be present correctly in answers generated by AI. Adobe also cites data showing traffic from AI to U.S. retail sites increased 1,324% from October 2024 to May 2026, while the travel industry grew 2,215% over the same period.

However, the bigger meaning lies in the strategic question: if users no longer go through traditional search links but instead arrive at answers synthesized by AI, how will businesses measure “brand visibility”? This is precisely the arena of GEO — generative engine optimization — which Adobe is investing in to turn into a concrete measurement and operational capability. Source: MarTech.

When performance marketing exposes its weakness: don’t just manage the dashboard

MarTech also published a notable critical perspective on performance marketing: overly tight measurement systems can sometimes leave businesses managing only the numbers on the dashboard, rather than the brand and long-term business outcomes. The article revisits the warning behind the phrase “what gets measured gets managed” — that measurement does not always mean the right things are being managed.

When performance marketing exposes its weakness: don’t just manage the dashboard
Overreliance on dashboard metrics can cause marketing teams to lose sight of the long-term brand picture. Photo: Marketing365.

In a context where AI is increasingly involved in ad optimization, budget allocation, and resource distribution, the risk of “overreliance on metrics” becomes even clearer. When businesses look only at ROAS, CAC, or CTR, they can easily optimize for a short-term slice while overlooking the brand value, emotion, and trust that AI cannot fully measure through a dashboard.

The important message here is not to reject performance marketing, but to remind marketers to keep a balance between measurement and strategy. AI can help optimize many things, but if the evaluation criteria are wrong, technology only makes mistakes faster. Source: MarTech.

A perspective for the Vietnamese market

The four stories above show that AI is entering a “post-experimentation” phase: businesses are no longer asking whether AI can do something, but how AI should be governed, how it should be measured, and what value it creates for the customer journey. For the Vietnamese market, this is the time for brands to view AI as a strategic infrastructure layer, not just a set of creative support tools.

Specifically, marketers should prioritize three things: build a content governance system strong enough to avoid an “asset explosion” when using AI; monitor brand visibility across search and answer surfaces generated by AI; and balance short-term metrics with long-term brand health. Those who do these three things well will have a clear advantage as users’ search and decision-making behavior continues to change.

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References

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