Why Your Brand Should Consider A SEO Health Check

Perhaps you’ve heard the buzz about AI search but aren't sure what to make of it. You've got a lot on your plate, and another "must-do" initiative probably sounds exhausting.

Let me share why this particular shift is worth your attention.

Consumer Discovery Is Evolving

Recent data from the AP-NORC Center shows 60% of U.S. adults now use AI to search for information. Among people under 30, that number jumps to 74%.

Your potential customers are still using Google, but they're also asking questions to ChatGPT, Perplexity, and other AI assistants. If your website isn't structured for these systems to understand, your brand might not show up in those conversations. This shift is happening faster than many expected.

The Opportunity for Early Movers

Here's what makes this timing interesting: AI-driven discovery is still new enough that brands who start optimizing now can build authority before the space gets saturated. 

A solid SEO health check covers your fundamentals - site speed, crawlability, schema markup. Those are the basics. Beyond that, your content should be optimized for AI-driven queries (sometimes called AIO). And structuring your brand information so large language models can understand and cite you (that's GEO - Generative Engine Optimization) helps you show up in AI-powered answers.

When you start now, you're positioning your brand ahead of the curve rather than responding to it later.

Why a Balanced Approach Makes Sense

Google remains important. That's not changing anytime soon. But the discovery landscape is expanding.

AI assistants are becoming another channel for how people find information and make decisions. Traditional SEO tactics address Google well, but they don't fully cover how AI systems work.

When you combine an SEO health check with AIO and GEO optimization, you're preparing your brand for current search behavior while building flexibility for future shifts. This approach reduces the need for major rebuilds down the road.

Common Questions and Concerns

I've had enough conversations about this topic to know the questions that come up. Let me address them directly, because they're legitimate concerns worth discussing.

Question 1: "AI search traffic is only 5% of Google volume. Why prioritize this now?"

This question makes sense, especially for brands operating with defined budgets where every investment needs clear justification.

The 5% figure measures current traffic volume, but it doesn't capture market direction or influence. With 60% of adults already using AI for informational searches, we're watching adoption rates that outpace what we saw with early social media or mobile.

Consider mobile search; In 2007, it represented a small fraction of Google traffic. Brands that optimized early gained significant advantages. Those that waited spent years catching up at higher costs.

Much of this work serves both channels. Improvements to crawl optimization, schema implementation, and site speed benefit both Google and AI search. You're not choosing one over the other.

Question 2: "You can't measure ROI without traditional tracking metrics. How do we know this works?"

This is a fair concern. Traditional SEO metrics don't translate directly to AI search, and I understand the hesitation to invest without clear measurement. The measurement approach is different, but there are meaningful metrics you can track:

·       Citations in AI responses (how often your brand gets mentioned)

·       Answer presence (whether you appear in response to relevant queries)

·       Knowledge graph inclusion (entity recognition across systems)

·       Referral patterns (traffic sources from AI platforms) Share of voice in AI responses compared to competitors

A phased approach helps build confidence: start with a baseline audit, implement changes, then monitor monthly. Each phase shows progress.

Think about how programmatic advertising evolved. Early adopters faced similar measurement challenges, but the brands that learned early built lasting advantages.

Question 3: "Isn't this just regular SEO with different terminology?"

I appreciate this question because the digital marketing industry has a history of rebranding services with new names...and adding more annoying acronyms!  Good SEO remains foundational. If your site has crawl errors, slow load times, or broken schema, those need fixing regardless. That work is essential.

The difference is that traditional SEO optimizes for Google's algorithm, while AIO and GEO optimize for how large language models consume, understand, and cite information. There's overlap in the technical requirements, but they're not identical.

Some key differences:

·       Traditional SEO focuses on keywords and backlinks. GEO emphasizes entity relationships and structured data.

·       Traditional SEO targets search queries. AIO optimizes for conversational questions and follow-up interactions.

·       Traditional SEO aims for page rankings. GEO aims for citation authority across multiple AI systems.

If a partner is simply adding "AI optimization" to their invoice without adjusting their approach, that would be worth questioning. But the category itself represents a genuine shift in how optimization works.

Question 4: "AI models change constantly. Won't optimization become obsolete quickly?"

This concern is understandable given how fast AI technology evolves.

The AI models themselves do update frequently - ChatGPT, Claude, Perplexity all release new versions regularly. But the underlying principles remain stable:

·       Clear, authoritative content gets cited more frequently

·       Structured data helps machines understand context

·       Entity relationships build trust signals

·       Question-answer formatting improves discoverability

These fundamentals won't become obsolete with the next model update. They're based on how language models process information.

It's similar to social media advertising. Platforms change algorithms regularly, but brands that understand audience behavior and creative principles adapt successfully. The core concepts transfer.

Question 5: "Our brand ranks well on Google now. Why change our approach?"

Strong Google rankings are valuable and worth protecting. The challenge is that customer behavior is shifting alongside your rankings.

When potential buyers start their research with AI assistants and your brand doesn't appear in those responses, your overall visibility decreases even while your Google position stays strong.

We're seeing this pattern across industries: solid organic traffic from Google, but fewer brand mentions in AI-driven research. By the time this trend appears clearly in analytics, recovery takes longer and costs more.  Brands that maintain presence across both traditional and AI-powered search channels are building visibility for the next phase of discovery.

Question 6: "Is this another pitch for additional services?"

I run an agency, and we do offer these services. Whether you work with us, another partner, or build this capability internally, the market shift is real. Your buyers are using AI for search. Some competitors are already optimizing for it.  The decision is about timing and approach, not whether the shift matters.

I've watched similar patterns unfold across digital channels over two decades. Brands that move early typically gain advantages. Those that wait often face steeper learning curves and higher costs later. You get to decide which approach works best for your situation.

Question 7: "Remember voice search? This feels similar."

Voice search is a useful comparison because it teaches us something important about technology adoption. Voice search didn't transform discovery the way many predicted. Here's why AI search is different:

·       Voice required new behavior - talking to devices instead of typing. AI search fits existing behavior - people already ask questions, they're using a different interface.

·       Voice had limited utility beyond simple queries. AI search handles complex research, product comparisons, and multi-step decision processes.

·       Voice was device-specific and often awkward in public settings. AI search works across platforms and feels natural.

·       Most significantly: voice search never reached 60% adoption. AI search has, and growth continues.

The lesson isn't to ignore emerging search behaviors. The lesson is to distinguish between forced behavior change and natural evolution. AI search appears to be the latter.

Question 8: "Our team doesn't have bandwidth for major technical projects."

This is a common and legitimate constraint. Development teams at middle-market brands are typically backlogged with priorities.

The good news is that this doesn't require a complete site rebuild. The work phases naturally:

·       Phase 1: SEO "Health Check" and clean up of errors and issues

·       Phase 2: Critical fixes (structured data, crawl issues - manageable scope, high impact) and Content optimization (primarily editorial work)

·       Phase 3: Reporting and Continuous Search and LLM Support; Entity building (ongoing, incremental improvements)

Many brands see meaningful results from phases 1 and 2 alone. We're talking 2-3 weeks of focused work, not multi-month projects.

For resource-constrained teams, the right partner handles implementation while you focus on strategy and approval. The technical execution happens without overwhelming your internal staff.

Question 9: "Our industry is highly specialized. Will AI even understand it?"

I hear this question frequently from brands in technical fields, B2B markets, and specialized industries.  AI systems are trained on enormous datasets that include specialized content across virtually every field. They handle technical terminology, industry jargon, and niche concepts more effectively than many people expect.

The challenge isn't whether AI understands your industry. The challenge is structuring your content so AI systems can connect your expertise to relevant user queries.

For example, a technical white paper written for industry experts might not be discoverable if it lacks clear structure, entity definitions, and contextual relationships. The same content, properly formatted, becomes a valuable, citable resource.

Your brand's specialization is often an advantage. Fewer competitors are focusing on AI search optimization in specialized niches, which means brands that start early can establish authority more easily.

Question 10: "How does the investment compare to current SEO spending?"

Budget is always a consideration for middle-market brands. Adding new initiatives requires clear justification.  One way to think about it; Wat's the cost of waiting? If a significant portion of your potential customers are using AI for research and your brand isn't visible there, you're facing an opportunity cost that compounds over time.

If competitors establish citation authority and entity relationships while you wait, catching up becomes progressively more difficult and expensive.

If Google continues integrating AI features that reduce traditional organic clicks, current SEO investments may deliver diminishing returns.

Many brands find they can phase this work within existing budgets by adjusting priorities rather than adding entirely new line items. It's often about reallocating some resources to prepare for where search is headed, while maintaining focus on what's working today.

A conversation with your current SEO partner (or a new one) about phased implementation can help clarify the actual investment required for your specific situation.

What This Means for Your Brand

When implemented thoughtfully, here's what you gain:

·       Visibility in both traditional Google results and AI assistant responses

·       Content structured for how people and machines search today

·       Infrastructure that adapts as search technology continues evolving

·       Positioning ahead of market shifts rather than reacting to them

·       Trust signals and entity associations that build over time

What To Do Next

For middle-market brands, the question is less about whether AI search matters and more about when to start preparing for it.

Brands that invest in comprehensive discovery strategies - combining SEO health checks with AIO and GEO optimization - are building visibility for both current and emerging search behaviors. The shift in how buyers find information is real. The timing and approach you choose will depend on your resources, priorities, and competitive landscape.

If you'd like to explore what this looks like for your brand's specific situation, we're happy to talk. At First Position Digital, we work with middle-market brands to develop discovery strategies that address both immediate needs and future opportunities.

What's your experience with AI search so far? Are you seeing changes in how customers find your brand? I'd welcome your thoughts in the comments.

Sean Sweeney Founder and CEO, First Position Digital