I use AI every day, and increasingly I notice that I'm using it in places where I would have gone to Google even a year ago. I'm not just asking simple questions. I'm using it to research companies, compare products, evaluate options and help me narrow down decisions. That change in my own behavior has made me think a lot about what the same shift means for our clients and for Advoda.

For years, companies have focused heavily on SEO. Where do we rank? Are we on page one? Are prospective customers finding our website? Those questions still matter, but there is now another one that may become just as important: when someone asks AI about the problem we solve, are we part of the answer?

The latest research around AI search describes a fundamental shift from links to answers. Instead of giving users a list of places to research something themselves, generative AI increasingly does the research, synthesizes the information and delivers an answer or recommendation. The specific numbers around adoption and traffic will continue to evolve, but the direction seems pretty clear: buyer behavior is changing.

For businesses, that matters because there may never be a traditional search results page in some buying journeys. If a prospective client asks ChatGPT, Gemini, Perplexity or another AI platform to recommend companies that can solve a specific problem, AI may effectively create the initial consideration set. If your company isn't included, the buyer may never know you were an option.

Measuring It Isn't Enough

This is where I've become particularly interested in the emerging AI visibility and Generative Engine Optimization market. There are now platforms that can show companies how frequently they appear in AI-generated answers, how they compare with competitors, what sources AI is citing and where they have gaps. That's valuable information, particularly because most organizations don't have a baseline today.

But measurement alone isn't where I see the real value. If I learn that Advoda appears in a fraction of relevant AI responses while a competitor appears far more frequently, I don't need another dashboard telling me the same thing every week. I need to understand why the competitor is outperforming us and what we can actually do about it.

Is our positioning unclear? Are there important topics where we don't have enough authoritative content? Are competitors being cited more frequently by credible third-party sources? Is our website structured in a way that makes it difficult for AI agents to understand what we do? Are there specific questions buyers are asking that we simply aren't answering well? Those are much more useful questions because they lead to action.

For me, that's the distinction companies should be paying attention to as they evaluate this emerging technology category. Measurement gives you the baseline, but the real business value comes from using that intelligence to improve how your company is understood, cited and ultimately recommended.

SEO Isn't Going Away, But the Strategy Is Expanding

I don't believe Generative Engine Optimization replaces SEO. Companies still need strong websites, useful content, good technical architecture and credible third-party references. In many cases, the work that improves traditional search visibility will also help improve AI visibility.

The difference is that optimizing only for traditional search assumes the buyer is still searching the traditional way, and increasingly that isn't always true. We're beginning to move from competing primarily for a position on a search results page to also competing for inclusion in the answer itself.

That creates an interesting window for companies willing to pay attention early. Most organizations have spent years developing SEO strategies, budgets, expertise and performance metrics. Very few have that same maturity around AI visibility yet. Companies that begin learning now can understand where they are missing from important conversations, identify why competitors are being recommended and start systematically improving their position before this becomes a much more crowded discipline.

Where Advoda Fits

We've been actively evaluating this category at Advoda, both because we need to understand it for our own business and because we believe it will become increasingly relevant to our clients. What we've already found is that there are meaningful differences between the platforms entering the market. Some lean heavily toward monitoring and measurement, while others go further into optimization, content recommendations, competitive intelligence and understanding how AI agents actually interact with a company's digital presence.

That's why I don't think companies should start by asking which tool they should buy. They should start by understanding what they're trying to accomplish, where their current gaps are and how aggressively they want to improve their visibility in AI-driven discovery.

Advoda can help clients evaluate and source solutions in this emerging category, but the technology itself is only part of the conversation. Our role is to help clients understand the market, determine which capabilities matter to their business and select technology based on the outcome they're trying to achieve rather than simply adding another AI platform to the stack.

That is consistent with how we think about AI more broadly. There is no shortage of new AI technology to buy, and simply adding another platform doesn't create value. The opportunity comes from identifying where AI is changing a business process or customer behavior, determining what that means for your organization and applying the right technology in a way that produces a measurable outcome.

AI-driven search is a good example of that shift happening in real time. We've spent years making sure our companies show up when customers search for what we do. Now we also need to understand whether we're part of the answer when customers ask AI who can help them, and if we're not, what we're going to do to change that.