Search behavior has changed. AI Overviews are stealing clicks. Tools like Perplexity, ChatGPT, and Reddit are rewriting the discovery funnel. What used to be about keywords and backlinks is now about entity recognition, semantic structure, and AI visibility. SEO teams are being asked to do more, scale faster, and prove value across surfaces that don’t even send traffic.

For instance, Google is more popular than its ever been, but how Google is showing information (like with AI overviews) and how users interact with Google has changed as well. 

While back-to-basics SEO principles remain relevant, the methodologies and tools have transformed dramatically.

Now what’s important are AI-driven approaches that prioritize user intent, semantic relevance, and machine-readable content. 

The team from iPullRank calls this relevance engineering and defines it like this:

“Relevance engineering is the art and science of improving visibility for any search surface. It’s the intersection of information retrieval, user experience, artificial intelligence, content strategy, and digital PR to give visibility in any form of search.”

At AirOps, we've collaborated with numerous SEO teams navigating this transition and it’s worth highlighting the differences. 

Classic SEO includes the manual techniques that dominated the industry for years:

• Keyword research and optimization: Picking a core keyword and writing for it
  
  
• Long-form content creation: 1,500-word articles with subheads and intro/outro patterns
  
  
• Manual internal linking and backlink outreach: Heavy lifting for authority
  
  
• Technical optimizations: Meta tags, sitemaps, site speed
  
  
• Human-crafted content: Strategist-built, writer-delivered, SEO-edited

While these methods have yielded results, they are often time-consuming, costly, and challenging to scale.

What Is Modern AI SEO?

Modern AI SEO blends human expertise with machine-driven optimization, enhancing capabilities and efficiency:

• AI-driven keyword clustering: Grouping topics based on searcher intent
  
  
• Content generation with editorial oversight: Briefs and drafts built with LLMs, then refined
  
  
• Proactive SERP modeling: Forecasting features, competitors, and AI surfaces
  
  
• Automated refresh detection: Pages flagged for staleness or schema gaps
  
  
• Workflow-based execution with human review: Internal linking, on-page changes, and schema integrated into repeatable systems with humans calling the shots and editing
  
  

People still have questions, just the places they ask may have changed. Wil Reynolds from Seer Interactive mentioned this in an AirOps webinar: 

At SEO Week, Jeff Coyle from SiteImprove and MarketMuse showed that modern SEO relies on hybrid retrieval, which combines semantic and keyword-based search. Optimizing for both lexical relevance and vector similarity gives content the best chance of being retrieved, summarized, and cited by AI systems like ChatGPT and Perplexity.

Classic SEO vs. Modern AI SEO: Side-By-Side Comparison

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Why hybrid SEO strategies are winning in 2025

The definition of SEO content has expanded. AI Overviews, zero-click results, and AI-native platforms like Perplexity are reshaping the SEO landscape. Even with high rankings, websites may not secure clicks. To remain competitive, content teams must optimize for visibility, influence, and discoverability across various formats and platforms.

SEO consultant Nick LeRoy shared that his clients are already seeing signs that their peak organic traffic may be behind them. He’s advising teams to prepare for further decline as AI continues to reshape the SERP. Rather than chasing new content volume, he recommends focusing on content that’s almost performing—investing in strategic updates that can push it into visibility.

This evolution necessitates:

• Multi-Intent Journey Optimization: Addressing various user intents within content
  
  
• Proactive Content Creation: Anticipating and answering questions before they're asked
  
  
• Diversified Content Distribution: Publishing across owned and earned channels, including Reddit, YouTube, and newsletters
  

George Chasiotis echoed this journey-based strategy, emphasizing that SEO is no longer just about “pages.” It’s about content ecosystems designed to support discovery, engagement, and conversion across channels.

“Nowadays SEO is way more complicated which makes our job more difficult but way more exciting as well, right? We have to start thinking about brand, we have to start thinking about and talking about digital PR. Leveraging social media and forms like UGC websites, we have to go multiformats, because it's not jus text-based content that we need today to to win.”

Brand mentions surpass backlinks

AI-driven engines are shifting focus from traditional backlinks to assessing topical authority, entity alignment, and brand presence across the web. Brands with consistent mentions in public content, such as Reddit or forums, are increasingly featured in AI-generated responses.

Reddit is increasingly dominating AI overviews and the organic SERPs, too and is one of the largest sites on the web.

This transition favors brands that cultivate ecosystem authority, not just page authority. For content teams, that means engaging with community platforms, expert contributors, and content aggregators—not just pursuing backlinks.

Attribution: Evolving SEO Measurement

Traditional SEO metrics like rankings and traffic are becoming less indicative of success. AI tools often do not pass referrer data, and AI Overviews can provide information without directing users to the source website. This shift complicates ROI tracking.

Here are new content metrics that you can follow:

Answer Engine Optimization (AEO)Optimize content to be citable by AI tools. Think: structured, authoritative, and easy for LLMs to pull into responses.

AI Overview & LLM Impressions
Track how often your brand/content appears in tools like ChatGPT, Perplexity, or Google’s AI Overviews. Visibility > clicks.

Quality of Output
Instead of volume, measure cost per usable asset, review time, and human oversight needs. High-quality > high-quantity.

Brand Impressions (Everywhere)
Include branded search trends, social shares, mentions in newsletters, and citations in AI tools. Track sentiment and authority, not just volume.

Referral Traffic from AI
With declining organic CTRs, track which AI tools send actual clicks your way. Tools like Ahrefs and Perplexity can help.

The Breakdown: Classic SEO vs. Modern AI SEO

Below is a side-by-side breakdown of where classic SEO falls short and how modern teams are adapting to AI-powered search.

1. Content creation

Classic SEO: Fully human-written articles, manually optimized for keywords.
Modern SEO: Human + AI-assisted content created through structured workflows.

Content today is co-created. Writers use AI for speed and consistency—generating outlines, drafts, and repurposed assets—while editors refine for voice, accuracy, and brand alignment.

2. Keyword research

Classic SEO: Manual research focused on seed terms and keyword volume.
Modern SEO: AI-driven clustering based on user intent and topic coverage.

Instead of targeting a single term, modern SEO clusters related queries by journey stage. Tools surface intent-based gaps automatically, reducing guesswork.

3. Internal linking

Classic SEO: Links manually inserted by content teams.
Modern SEO: AI recommends internal links by analyzing context, entity relationships, and authority flow.

This ensures that critical pages are connected and reinforces your site's topical structure.

4. Link building

Classic SEO: Cold outreach for backlinks to boost rankings.
Modern SEO: Brand visibility across Reddit, YouTube, and forums signals authority to search engines and LLMs.

Links still matter—but so do citations, mentions, and the company you keep across public knowledge graphs.

5. Scalability

Classic SEO: Scaling required larger teams and more manual output.
Modern SEO: AI workflows enable small teams to scale content, updates, and audits efficiently.

With structured systems, you can refresh hundreds of pages, expand keyword coverage, and track quality—without bottlenecks.

6. Algo adaptability

Classic SEO: Reactive updates after Google algorithm changes.
Modern SEO: Proactive strategies aligned with semantic search, structured data, and LLM behavior.

Optimizing for search engines now means optimizing for understanding—not just rankings.

7. Measurement & attribution

Classic SEO: Rankings and organic sessions were primary KPIs.
Modern SEO: Visibility in AI Overviews, brand mentions in LLMs, and influence across channels are equally critical.

Success is no longer just clicks. It’s citations, summaries, and strategic content footprint—across both human and AI audiences.

8. User journeys

Classic SEO: Optimize a single page for a specific keyword.
Modern SEO: Build content ecosystems that support full user journeys.

Today’s search is non-linear. Tools like Google MUM and AI Overviews follow intent chains—so your content must span awareness, comparison, and conversion topics.

9. Search surfaces

Classic SEO: Optimize primarily for Google SERPs.
Modern SEO: Optimize for visibility across AI tools, social platforms, and aggregators.

Success now includes ranking in Perplexity, being cited in Reddit threads, appearing in DeepSeek answers, and surfacing in ChatGPT.

10. CONTENT FORMATS

Classic SEO: Focus on long-form articles as the primary format.
Modern SEO: Use modular content in multiple formats—FAQs, diagrams, videos, and tools.

Modern search surfaces favor content that can be reused, cited, and embedded in AI answers. Multiformat = multi-surface visibility.

11. Technical SEO priorities

Classic SEO: Prioritize crawlability, mobile-friendliness, and site speed.
Modern SEO: Prioritize structured data, semantic markup, and AI-readable content.

JavaScript-heavy sites and ambiguous layouts can harm AI discoverability. Simplicity, schema, and context are the new essentials.

12. CONTENT REFRESHES

Classic SEO: Refresh manually based on intuition or traffic drops.
Modern SEO: Use AI to identify underperforming pages and recommend structured updates.

Refreshing is no longer just about rewriting. It’s about updating facts, improving structure, adding schema, and aligning with modern SERP features.

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Final Thoughts: Take on the long game

Despite AI's rapid advancements, SEO remains a long-term strategy. Achieving rankings and building brand visibility require consistent effort and adaptation.

Nick LeRoy emphasized:

"If you need revenue in six months or you’ll go out of business, SEO won’t save you. But if you invest now, it can be your most sustainable channel over time."

Integrating AI into SEO practices accelerates processes, enhances testing capabilities, and ultimately strengthens returns over time. Success in 2025 hinges on blending foundational SEO principles with modern AI-powered scalability.

How AirOps Improves Your SEO Workflows

AirOps empowers content and SEO teams to:

• Automate Repetitive Tasks: Streamlining content briefs, updates, and internal linking
  
  
• Leverage AI-Powered Research: Using AI for keyword research, optimization, and performance tracking
  
  
• Maintain Quality at Scale: Keep brand standards and content quality across large portfolios
  
  

A notable example is Descript, which used AirOps’ content refresh workflows to grow organic traffic by 35% in just three months by combining their data with AI-driven recommendations.  Read the full story.

Ready to scale your SEO efforts with AI-powered workflows? Schedule a strategy session with AirOps today.