From Search to Systems: Rethinking Digital Visibility in the Age of AI
A few weeks ago, Velir hosted a thought leadership dinner alongside our partner Sitecore, with marketing leaders from companies like GEICO, Capital One, Morningstar, Abbott, and Kohl’s. It was one of those rare conversations where everyone around the table could openly admit: the digital space feels like it’s shifting under our feet.
We talked about how AI isn’t some “future problem” we have to plan for, rather it’s already here, quietly changing the rules. And the biggest challenge? The systems we’re all trying to show up in don’t think like people anymore.
Data Isn’t Just “Data” Anymore
Most teams still treat data like it’s something you store in a warehouse and pull out when you need it. But that’s not how it works anymore. Data is now infrastructure. Data is the engine running websites, powering personalization, fueling analytics, and increasingly, making decisions on its own.
The problem is, most organizations don’t agree on what “data” even means for their business. There’s no clear owner, no shared definition, and no real governance. That’s where a lot of AI projects stumble — not because the tech fails, but because the data behind it is messy, inconsistent, or locked away in silos.
At Velir x Brooklyn Data, we’ve seen how much smoother things run when teams get aligned on what data they have, how it’s structured, and who’s responsible for it. We help clients clean up and connect their data so AI systems (and humans) can actually trust it.
Discovery Has Changed — and Most Sites Haven’t Kept Up
There was a lot of talk at dinner about SEO. Remember the times when SEO used to be about making your site appealing to people? The reality now is that large language models (LLMs) are scraping, parsing, and summarizing huge chunks of the web — and serving answers before anyone ever clicks a link.
If you’re not showing up in the top page of organic search results, you’re probably not showing up in AI answers either. And even if you’ve got great content, it might get skipped if it’s not structured in a way that these systems can understand.
That means thinking beyond keywords. It’s about content that’s chunkable, clearly marked up, and machine-readable. At Velir x Brooklyn Data, we work with clients to make sure their content talks to both people and systems — so it’s ready to be found, whether it’s by a human searching Google or an AI pulling together an answer.
AI Isn’t a Side Project — It’s Already in Your Stack
One of the big takeaways from our dinner was how easy it is for companies to think of AI as an “initiative” — something you pilot or test. But in reality, it’s already in your search results, your customer service tools, your analytics dashboards, your personalization engine.
The real question isn’t “Should we use AI?” but “Is our content and data ready for the AI that’s already using it?” That’s where we see organizations getting tripped up. If the system can’t interpret what you’ve built, it will fill in the blanks itself, presenting a risk brands, especially in high-trust or regulated industries.
At Velir x Brooklyn Data, we help teams audit and structure their digital experiences so they’re accurate, usable, and adaptable. That might mean rethinking how content is organized, cleaning up outdated information, or building processes that keep things fresh so AI has the right stuff to work with.
Where Do We Go From Here?
We’re in a moment where the rules of digital visibility are being rewritten in real time. Systems no longer think like people, and if your site isn’t set up to talk to them, you risk disappearing from the conversation entirely.
For the folks at our dinner, that realization was a bit unsettling, but moreso motivating. The good news is that the right adjustments focused on aligning on data, structuring content for discovery, and making sure AI can interpret what you’ve built can make a huge difference.
As we said that night: be cautious, but willing. The consequences to your brand are worth the right risk.