AI and SEO: What's Changing in 2025

The State of AI in Search: 2025

The conversation around AI and SEO has moved past speculation. We’re now dealing with concrete changes that affect traffic, visibility, and how businesses get found online.

Google’s AI Overviews appear in roughly 30-40% of search results. ChatGPT, Perplexity, and Claude are processing millions of search-like queries daily. Bing Copilot integrates AI answers directly into Microsoft’s search engine.

For SEO professionals, this isn’t a distant future scenario—it’s the current operating environment. And the strategies that worked in 2023 need significant updates to remain effective.

Google’s AI Overviews: Impact and Adaptation

What AI Overviews Are Doing to Click-Through Rates

AI Overviews (formerly Search Generative Experience) display a synthesized answer at the top of search results for many informational queries. The effect on organic traffic varies dramatically by query type:

High impact (traffic loss of 30-60%):

• Simple factual queries (“what is a 301 redirect”)
• Definition queries (“what does bounce rate mean”)
• Quick-answer questions (“how many characters in a meta description”)

Moderate impact (traffic loss of 10-30%):

• How-to queries with multiple steps
• Comparison queries
• List-based queries

Low impact (minimal traffic change):

• Commercial investigation queries (“best CRM for small business”)
• Local intent queries (“SEO agency near me”)
• Complex decision-making queries
• Queries requiring personal judgment or experience

Adapting Your Content Strategy

The key insight: AI Overviews primarily affect content that provides single, definitive answers. Content that offers analysis, opinion, comparison, and multi-faceted exploration retains its traffic because AI can’t fully synthesize nuanced perspectives.

Shift toward:

• Original research with proprietary data
• Expert analysis and opinion pieces
• Experience-based content (case studies, process documentation, lessons learned)
• Interactive tools and calculators that AI can’t replicate
• Content that requires visual demonstration

Shift away from:

• Pure definition/glossary content
• Thin FAQ pages that AI Overviews answer completely
• Basic how-to content for simple processes
• Aggregated information without original perspective

Getting Cited in AI Overviews

AI Overviews pull from web sources and display citation links. Getting cited in these overviews becomes a new ranking objective. Sites that get cited tend to:

• Provide clear, well-structured answers with supporting detail
• Demonstrate topical authority through comprehensive coverage
• Use precise, factual language with specific data points
• Maintain strong E-E-A-T signals (author credentials, citations, publication standards)

This is closely related to Generative Engine Optimization (GEO), which focuses specifically on optimizing for AI-generated responses.

ChatGPT, Perplexity, and the Rise of AI Search Engines

AI Search as a New Channel

ChatGPT with browsing capabilities, Perplexity AI, and similar tools are becoming legitimate search alternatives. They don’t just answer questions—they browse the web, synthesize information from multiple sources, and provide cited answers.

This creates a new discovery channel that operates differently from traditional search:

No position one—there’s citation or nothing. AI search tools either cite your content as a source or they don’t. There’s no ranking ladder to climb. Your content is either authoritative enough to be selected as a reference or it’s invisible.

Longer, more conversational queries. Users interact with AI search using natural language questions, not keyword strings. This favors content that addresses topics comprehensively rather than targeting specific keyword phrases.

Follow-up questions change the dynamic. Users ask follow-up questions in the same conversation, going deeper into topics. Content that covers a topic thoroughly—anticipating follow-up questions—is more likely to be cited across a conversation thread.

Optimizing for AI Search Platforms

The strategies for AI search visibility overlap with but extend beyond traditional SEO:

• Be the authoritative source. AI models prioritize authoritative, well-established sources. Building genuine domain expertise and authority matters more than ever.
• Structured, clear content. AI systems parse content more effectively when it’s well-organized with clear headings, precise language, and logical structure.
• Factual accuracy. AI tools increasingly cross-reference information across sources. Inaccurate content gets filtered out.
• Freshness signals. AI search tools favor recently updated content, especially for topics that evolve (technology, regulations, market data).

For a deeper look at optimizing specifically for ChatGPT and similar platforms, see our guide on optimizing for ChatGPT and AI search.

AI Content Generation: Where It Helps and Where It Fails

The Current State of AI-Written Content

AI writing tools have matured significantly. They can produce grammatically correct, topically relevant content at scale. But “correct and relevant” isn’t the same as “valuable and rankable.”

Google’s official position: they don’t penalize AI-generated content per se, but they do penalize low-quality, unhelpful content—regardless of how it was produced. The practical effect is that purely AI-generated content without human expertise, editing, and original perspective rarely ranks well for competitive queries.

Where AI Content Tools Add Value

Research and ideation: AI tools excel at synthesizing research, identifying content gaps, and generating outlines. Using AI as a research assistant dramatically accelerates the content creation process.

First drafts and frameworks: AI-generated first drafts give writers a starting point. The human expert then adds original insights, experience-based observations, proprietary data, and the kind of nuanced perspective that AI can’t produce.

Content optimization: AI tools can analyze existing content and suggest improvements for readability, keyword coverage, and structural organization.

Scaling production: For large-scale content programs (product descriptions, location pages, data-driven reports), AI can generate baseline content that humans then review, customize, and enhance.

Where AI Content Falls Short

Original thought. AI recombines existing information. It doesn’t generate original insights based on professional experience, client work, or proprietary research. These are exactly the signals Google’s ranking algorithms increasingly prioritize.

E-E-A-T demonstration. Experience and expertise are human qualities. Content that demonstrates genuine experience (“in our work with 50+ healthcare clients, we’ve found…”) is qualitatively different from AI-generated content that mimics expertise without possessing it.

Brand voice. AI-generated content tends toward a homogeneous, formal tone. Distinctive brand voices—the kind that build recognition and loyalty—require human writing.

How AI Is Reshaping Keyword Research and Strategy

The Shift from Keywords to Topics

Traditional keyword research focused on finding specific search phrases and optimizing individual pages for each one. AI is accelerating a shift that was already underway: from keyword-centric optimization to topic-centric authority building.

Google’s AI systems understand semantics far better than the keyword-matching algorithms of a decade ago. They evaluate whether a page (and a domain) genuinely understands a topic—not just whether it mentions specific phrases. This means:

• Topic clusters outperform isolated pages. A comprehensive collection of interlinked content on a subject signals deeper expertise than scattered articles targeting individual keywords.
• Semantic coverage matters. Google evaluates whether your content addresses the full scope of a topic, including related concepts, prerequisites, and common follow-up questions.
• Search intent interpretation is more nuanced. AI can distinguish between “python” the programming language and “python” the snake based on query context—and your content needs to align with the specific intent Google identifies.

Conversational Search Changes Query Patterns

As more people use AI interfaces for search, query patterns are shifting. Instead of typing “best SEO agency NYC,” users ask “Which SEO agency in New York has the best track record with e-commerce companies?” These natural language queries are:

• Longer and more specific
• Often phrased as complete questions
• More likely to include qualifying criteria
• Less predictable and harder to target individually

Content that addresses specific scenarios, qualifications, and contexts performs better for these conversational queries than content optimized for two-word keyword phrases.

Zero-Click Implications by Industry

The zero-click impact varies dramatically by industry. Understanding where your vertical falls helps you allocate resources:

High zero-click risk: Informational publishers, recipe sites, definition/glossary sites, basic how-to content. These verticals are seeing measurable traffic declines from AI Overviews answering queries directly.

Moderate zero-click risk: B2B SaaS, professional services, educational content. Some top-of-funnel traffic is absorbed by AI answers, but commercial and mid-funnel content retains click-through.

Low zero-click risk: Local businesses, e-commerce product pages, real estate, healthcare providers, law firms. Transactional and local intent queries still drive clicks because users need to take action on a specific website.

Structured Data and AI: A Deeper Connection

Why Schema Markup Is More Important Than Ever

Structured data has always helped search engines understand content. In an AI-powered search environment, it becomes even more critical because:

AI systems use structured data as reliable metadata. When evaluating which sources to cite, AI models consider how well a page communicates its content type, authorship, and context through machine-readable markup.

Rich results compete with AI Overviews. Pages with rich results (FAQ dropdowns, how-to steps, review stars) maintain visibility even when AI Overviews appear above them. These enhanced listings capture attention and clicks that plain blue links lose.

Entity recognition depends on structured data. Schema markup explicitly defines entities (organizations, people, products, locations) that AI systems use for knowledge graph construction. A well-marked-up site is more likely to be recognized as an authoritative entity in AI-generated responses.

Priority Schema Types for AI Visibility

• Organization and LocalBusiness — Establishes your entity in knowledge graphs
• Person (for authors) — Connects content to verified experts
• Article with author attribution — Signals editorial content with identifiable creators
• FAQ — Provides direct question-answer pairs that AI can extract
• HowTo — Structures procedural content for step-by-step extraction
• Product and Review — E-commerce visibility in both traditional and AI search

The Impact on SEO Services and Strategy

What’s Changing for SEO Agencies

The role of SEO professionals is evolving:

From keyword targeting to topic authority. Optimizing for individual keywords becomes less important than building comprehensive topical authority that makes your content the go-to source for an entire subject area.

From content volume to content depth. The “publish more articles” approach loses to the “publish better articles” approach as AI Overviews satisfy simple queries and only surface the most authoritative sources for complex ones.

From traditional rankings to multi-platform visibility. SEO now encompasses visibility across Google, AI Overviews, ChatGPT, Perplexity, and other AI platforms. Tracking and optimizing for these multiple surfaces requires new tools and methodologies.

From technical fixes to strategic thinking. Technical SEO fundamentals remain important, but the strategic layer—what content to create, how to position it, how to build authority—becomes the primary differentiator between effective and ineffective SEO programs.

What’s Staying the Same

Despite the changes, core SEO principles remain intact:

• Great content wins. The bar for “great” is rising, but the principle hasn’t changed.
• Technical foundations matter. Site speed, crawlability, mobile experience, and structured data still determine whether your content can compete.
• Backlinks signal authority. AI platforms rely on the same authority signals that Google uses. High-quality backlinks remain a primary trust indicator.
• User experience determines engagement. Bounce rates, time on page, and conversion rates still influence rankings and will influence AI citation decisions.
• Local SEO is defensible. Local search is one of the areas least disrupted by AI, since it requires real-world information that AI can aggregate but not replace.

Strategic Recommendations for 2025

Immediate Actions

1. Audit your content for AI Overview exposure. Identify which of your pages are being summarized by AI Overviews and losing traffic. Prioritize enhancing these pages with original analysis, experience-based insights, and depth that AI can’t fully capture.

2. Implement structured data aggressively. Schema markup helps both Google and AI systems understand your content. Organization, Article, FAQ, HowTo, and industry-specific schemas should be implemented across your site.

3. Monitor AI search visibility. Start tracking whether your content appears in ChatGPT, Perplexity, and AI Overview citations. This is an emerging metric that will become standard in SEO reporting.

4. Strengthen author authority. Publish under real author names with verifiable credentials. Link author bios to professional profiles, publications, and credentials. AI systems use these signals to evaluate source trustworthiness.

Medium-Term Strategy

1. Build a proprietary data advantage. Invest in original research, surveys, case studies, and data analysis that only your organization can produce. This type of content is both AI-resistant (it can’t be generated by AI) and AI-attractive (AI systems cite original data sources).

2. Develop multi-format content. Text content that AI can summarize is vulnerable. Video, interactive tools, podcasts, and visual content provide value that AI can’t fully replicate in a text summary. Repurpose your best content across formats.

3. Invest in brand search. As AI mediates more discovery, direct brand searches become more valuable. Build brand recognition through PR, thought leadership, social media, and offline channels so that people search for you by name.

4. Explore GEO as a discipline. Generative Engine Optimization is emerging as a distinct practice within SEO. Start developing expertise now.

Industry-Specific AI Search Impact

Different industries face different challenges and opportunities from AI-driven search changes:

Professional Services (Legal, Financial, Healthcare)

These industries benefit from strong E-E-A-T requirements that AI amplifies. Content from verified professionals with credentials carries more weight in AI citation decisions. Healthcare providers and law firms that publish expert-authored content are better positioned for AI search than those relying on generic marketing copy.

The YMYL (Your Money, Your Life) classification that applies to these industries means Google applies extra scrutiny—which, counterintuitively, protects established, credible providers from being displaced by low-effort content farms.

E-commerce

Product search is evolving. AI shopping assistants can compare products, read reviews, and make recommendations. E-commerce businesses need product pages with rich structured data, genuine reviews, and detailed specifications to be accurately represented in AI-generated product comparisons.

Local Businesses

Local search remains one of the most AI-resilient categories. People searching for nearby businesses need real-time information—hours, availability, location, reviews—that AI aggregates from your Local SEO presence. Maintaining accurate, comprehensive local listings becomes even more important as AI tools surface this data in conversational responses.

Businesses with strong Manhattan or borough-specific local presence are well-insulated from the broader AI disruption affecting national informational content.

Measuring SEO Performance in an AI World

New Metrics to Track

Traditional SEO metrics (rankings, organic traffic, conversions) remain essential but need supplementation:

• AI citation rate: How often your content is cited in AI Overviews, ChatGPT, and Perplexity responses for target queries
• Brand mention sentiment in AI: How AI platforms characterize your brand when users ask about you
• Traffic by source type: Distinguish between traditional organic, AI Overview clicks, and AI search engine referrals
• Zero-click visibility: Impressions for queries where AI Overviews appear (tracked in Search Console)

Adapting Reporting Frameworks

Client and stakeholder reports should evolve to capture AI-era performance:

1. Traditional organic performance — Rankings, traffic, conversions (the established baseline)
2. AI visibility score — Manual or tool-based tracking of AI citations across platforms
3. Content authority metrics — Backlink acquisition, brand mentions, E-E-A-T signals
4. Channel diversification — Traffic from AI referral sources as a percentage of total organic

The Bottom Line

AI is the most significant structural change to search since mobile overtook desktop. But it’s not an extinction event for SEO—it’s a forcing function for quality. The websites and brands that have always invested in genuine expertise, original content, and strong technical foundations are best positioned for this shift.

The sites at risk are those that relied on thin content, keyword stuffing, and volume over quality. AI Overviews and AI search engines are, in effect, raising the floor for what qualifies as useful content. That’s a positive development for users and for the businesses willing to invest in truly helpful content.

For a practical look at whether AI might make SEO obsolete, read Will AI Replace SEO? The Truth.