I think we can all feel it.
If you open any trade publication or just spend time online, it’s AI all the time.
For anyone who knows me or has worked with me, I’m a skeptic at heart. That probably comes from years in data, trying to move away from insights that reinforce an opinion toward ones that actually drive action.
But, I’ve had two real “wow, this is different” moments with AI.
The first was about two years ago, when Claude Opus was first released. I used it to help write R code for a Monte Carlo simulation, modeling how small shifts from detractors to advocates could impact NPS for a national payer.
I wrote it, validated it, and ran hundreds of thousands of simulations in a few hours, essentially stress-testing what-if scenarios to predict exactly how customer loyalty would drive bottom-line growth. In my own IDE, my own coding environment. It worked. That was the first time I paused and thought, this is not incremental.

Maximizing with AEO and GEO
The second, though, has been more gradual: watching how behavior around search is changing. Search is no longer about ranking pages. It’s about shaping answers.
Search used to be Google. SEO mattered a ton, but it was familiar to practitioners. You knew the levers and how to move them.
AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) feel different.
- At a simple level, AEO is about how you show up in the answer. It shapes the output.
- GEO is about what that answer is built from. It shapes the inputs that make that output possible.
Some core SEO principles still hold. You still need structured, machine-readable content. You still need to be clear and consistent in how you define your brand, your science, and your positioning.
Entity management unites brands with people
Underneath that, entity management is starting to matter a lot more. How you define and govern the core entities tied to your business like brand, molecule, indication, and patient vs. HCP. Those definitions need to hold up everywhere an AI system looks.
You’re building a knowledge graph, telling AI this molecule belongs to this brand, which treats this indication, and here’s how to explain it to a patient vs. a doctor. When that foundation is consistent, everything else starts to compound. When it’s not, things break quickly.
But the scope has expanded quite a bit.
It now includes how your brand shows up across everything people and systems reference for more information—Reddit, Wikipedia, Stack Overflow, journals, research, publications, and expert commentary. All of that is getting pulled into how answers are formed, and it’s crucial to have a solid foundation to empower consumers with the right information.
One of the reasons I like this space is that it never sits still, and AI is moving search faster than most things I’ve seen.
What started for us as calling AI platforms through APIs to see how they describe a brand, has already evolved. Now we’re building systems that track how brands are represented across those responses, including tone and consistency. That becomes the input for where to adjust content and where there are gaps.
Paid search is shifting in parallel. It used to be about how you show up in a list of links. Now we’re starting to see how paid signals and brand constructs show up inside AI systems themselves, from AI Overviews to how models incorporate or reference sponsored results.
That’s forcing a bit of a reset internally. Search, programmatic, content, and data science are all starting to work on the same set of problems. Sometimes intentionally, sometimes not. The upside is we’ve been building toward this for a while, so we’re walking into it with media, data, technology, and creative already working together.
At MERGE, we’re doing much of this work in healthcare and lifestyle, and the brands that are ahead tend to have a few things in common.
- They don’t treat AEO as a standalone channel. It cuts across content, experience, and how the brand shows up more broadly.
- They’re leaning into research, publications, and expert commentary. If AI systems are pulling from credible sources, that ecosystem matters.
- And they’re not standing still. What worked a few months ago already feels dated.
We’re testing things now that feel early, like identifying where AI responses have gaps, and targeting individuals who are consuming that information. I’ll probably look back on that in a few months and it won’t feel new at all.
It’s a fast-moving space.
And it’s a rare moment where you can see the change happening in real time.
Search didn’t just evolve. It changed shape. We’re no longer optimizing for pages. We’re optimizing for presence inside machine-generated answers. And the brands that understand that shift early, won’t just be easier to find.
They’ll be the ones defining what gets found in the first place, ensuring the person on the other side of the screen gets the information they need to live a healthier, happier life.