SEO in the Age of AI: How LLMs, Agentic Systems, and New Search Behaviors Change the Game

Search Engine Optimization (SEO) has continually evolved with technology. Still, the rise of large language models (LLMs) and agentic AI systems is reshaping search and discovery faster than most businesses expected. In this deep-dive article, we unpack the insights from the Bright Commerce podcast episode “SEO in the Age of AI” (EP 15) with Brian Seaman of GoBeyond SEO, plus hosts Carlos Caneja and Judd Dunagan. We cover what changed, what still matters, and practical steps for companies that want to stay visible in an AI-first world.

Key takeaway: SEO no longer means optimizing for ten blue links. It now includes visibility across LLM-driven answers, local listings, and agentic interfaces that can act on behalf of users.

Table of Contents

• Why this moment matters: AI is changing search behavior
• How Google and other LLM-powered services are adapting
• The local business buffer: calls, GMB/GMBB, and booking calendars
• Are classic SEO tactics (content, technical, backlinks, CTR) still relevant?
• How to use LLMs responsibly when creating content
• Generative Engine Optimization (GEO): thinking beyond classic SEO
• Agentic AI and e-commerce: the technical and business implications
• Practical checklist: what to do this quarter to future-proof your SEO
• Tools and tactics the panel recommends
• FAQ: SEO, LLMs, and agentic AI
• Conclusion: adapt, measure differently, and focus on real-world signals

Why This Moment Matters: AI is Changing Search Behavior

The discussion opens with a blunt observation: search is changing. The “10 blue links” era is eroding. LLMs (ChatGPT, Gemini, Claude, Perplexity) and integrated search experiences answer user queries directly on the search surface, often before the user visits a site. That shift matters for anyone who depends on organic traffic, lead generation, or discovery.

One of the most striking stats in the episode comes from a March Semrush study: 60% of U.S. Google searches end without a click. That means the user found their answer inside the search surface or AI overview and didn’t need to navigate to a website. This changes how success is measured and what signals to optimize for marketers and SEO professionals.

Two implications stand out:

• Organic visits can shrink even when interest is high, and the user intent can be satisfied by the search or the LLM answer.
• Search engines control more of the user experience (and the funnel) than ever before, which has business model implications for publishers and advertisers.

How Google and Other LLM-powered Services Are Adapting

Google’s approach has been to evolve the search results experience: keep users on the page with richer answers, experiment with AI overviews (called SGE, Search Generative Experience in some of Google’s products), and test new ways to present links or actions. The hosts discussed how Google still provides links but gets fewer clicks because users immediately get what they need.

“Google doesn’t want anybody to go to your website anymore. Technically, they want to answer the question before they even get there.” Roundtable quote paraphrase

Other platforms such as OpenAI (ChatGPT), Anthropic (Claude), and Perplexity offer conversational or research-style interfaces that sometimes provide citations and links. These systems are becoming part of the discovery journey, especially for informational and comparative queries.

While Google still controls enormous traffic (and pays large sums to remain the default for platforms like Apple Safari), alternative LLMs are growing as a first stop for many users who want synthesized answers rather than raw links.

The Local Business Buffer: Calls, GMB/GMBB, and Booking Calendars

Local businesses have been partially shielded from the drop in website clicks because of two dynamics: first, Google often shows local packs or GMB (Google My Business) / GMBB listings that prominently display phone numbers and directions; second, Google has incorporated call-first advertising options like Local Services Ads (LSA) that focus on phone contact. The result? Many local conversions now happen via phone call or direct booking rather than website form fills.

Practical implications for local businesses and their SEO strategies:

• Track calls as conversions: If your analytics ignore phone calls, you’re missing the primary conversion signal for local searches. Use call tracking and integrate it into reporting.
• Optimize your Google profile: Reviews, accurate NAP (name, address, phone), service categories, and local citations matter more than ever.
• Offer immediate booking: A booking calendar can outperform forms because it secures a commitment and removes friction.
• Review velocity and reputation: A business with many positive reviews can outrank a competitor with a stronger website but weaker local signals.

Are Classic SEO Tactics (Content, Technical, Backlinks, CTR) Still Relevant?

Short answer: yes, but the way you apply them must change. The panel stressed that on-page optimization, backlinks, technical SEO, and user experience still matter. However, you can no longer rely on routine content volume or low-effort AI-generated posts to rank or attract traffic. Here are the main points from the discussion:

Content quality matters more than ever

When AI made summarization and content generation trivial, many sites fell into the trap of churning out low-value posts that were thin, generic, or inaccurate. The panel noted that sites that copy-paste AI output without editing are getting penalized or seeing ranking dips. Google rewards content with a unique perspective, proprietary data, local context, or original research.

Backlinks and citations remain signals.

Backlinks still influence rankings, but mentions, trusted directory listings, and local citations (A/V/ratings sites for law, health, and other verticals) now carry additional weight when LLMs crawl sources for answers. Getting featured in local press, industry sites, and authoritative directories improves the chances that LLMs will cite your brand in generated answers.

Click-through rate (CTR) still matters, with caveats.

CTR manipulation exists in the wild (paid services that increase clicks), and it can produce short-term gains but carries risk. The panel highlighted examples of black/gray hat tactics around SERP clicks. Meanwhile, with 60% of searches ending without a click, raw CTR for organic links is a less reliable KPI. Focus on conversion-type metrics (calls, bookings, qualified leads) rather than raw clicks alone.

Google Analytics and keyword volume data are imperfect

Traditional keyword research tools and platform estimates (nationalized volumes, rounded figures) are helpful for directional insight, but you shouldn’t treat them as exact. The hosts recommended using Google Search Console and Google Ads directly for the most reliable signal, recognizing that even those have limits in an AI-driven landscape.

How to Use LLMs Responsibly When Creating Content

LLMs are powerful productivity tools, but the panelists urged caution. Here’s a practical approach (their “LLM as intern” metaphor) you can adopt today:

1. Use LLMs to brainstorm structure, outlines, and headlines, but not to publish verbatim.
2. Ask the LLM to include a “penalty audit” prompt, such as “Rewrite to avoid sounding like AI and add unique data or an original example.”
3. Verify facts and statistics. LLMs can and do hallucinate numbers and sources.
4. Add proprietary data, case studies, screenshots, or local context that AI models can’t generate from public sources.
5. Mix outputs from multiple LLMs (Claude, ChatGPT, Perplexity) and human editing to create a curated final product.

Above all, treat the LLM as a starting point, not the final author. This practice reduces the risk of penalties and ensures your content adds value that generic AI-generated pages cannot match.

Generative Engine Optimization (GEO): Thinking Beyond Classic SEO

Generative Engine Optimization (GEO) is a term the panel used to describe optimizing for LLMs and AI-driven answers. GEO goes beyond keywords and links; it focuses on brand authority, mentions, structured data, and the signals LLMs use when composing synthesized responses.

GEO tactics to consider:

• Structured, authoritative content: Use schema, structured data, and explicit metadata so machines can extract facts reliably.
• Brand mentions and PR: Local press, industry roundups, directories (AVVO, Super Lawyers, trade publications), and consistent citations increase the chance LLMs cite you as a source.
• Evidence and proprietary numbers: Publish original research, internal studies, and localized statistics to create content that AI considers unique and credible.
• Optimize for intent rather than keywords: Write content that mirrors how people ask questions conversationally (use FAQ blocks, natural phrasing, and mobile-first formatting).

In short, GEO is about becoming the source an LLM trusts and cites when assembling answers. That requires an investment in reputation signals, not just technical optimization.

Agentic AI and E-commerce: The Technical and Business Implications

The panel dove into the agentic phase of AI systems that take action on users’ behalf. Examples include booking appointments, creating orders, repeating purchases, and scheduling calendar events. This evolution has clear implications for ecommerce, product discovery, and fulfillment.

APIs, MCP layers, and ecommerce readiness

Brian introduced the concept of an MCP (machine-composable/proxy) layer, an API surface designed explicitly for LLMs and agents to interact with your storefront. Practically, this means:

• Expose reliable APIs for product queries, stock levels, pricing, and user accounts.
• Support authenticated actions (order placement, subscription sign-up, payment) with secure verification steps.
• Design confirmation flows to avoid unauthorized purchases, such as a phone notification or two-factor confirmation, before an agent places an order.

Many ecommerce platforms like WooCommerce already have APIs that can be exposed. Still, businesses must control what agents can do without explicit human confirmation (and to what extent prior purchase history is required).

Fraud concerns and verification

Agentic systems introduce new fraud vectors: deepfakes, voice-cloned confirmations, and automated ordering by bad actors. The panel recommended risk-based verification (the first purchase requires human confirmation, repeat purchases can be agented), robust logs, and monitoring to detect unusual behavior.

Experience design and voice/AR devices

As AR glasses and voice devices become mainstream, experiences will move from a visible SERP to a heads-up, conversational, or visual overlay. That implies:

• Designing product descriptions and actions with conversational prompts and short summaries suitable for voice responses.
• Rich media and structured data should be used so agents can quickly compare and recommend products.

Practical Checklist: What to Do This Quarter to Future-proof Your SEO

Based on the panel discussion, here is a tactical checklist you can act on immediately.

Short-term (30-90 days)

• Audit and track phone calls as conversions for local/lead-gen businesses.
• Update and optimize Google Business Profile and local citations; solicit authentic reviews.
• Run a content audit: identify AI-generated or low-value pages and improve, consolidate, or remove them.
• Add structured data (FAQ, product, localBusiness schema) to key pages.
• Integrate booking calendars for B2B discovery pages where appropriate.

Mid-term (3-6 months)

• Create several high-quality content pieces that include proprietary data, case studies, or local insights.
• Implement an API or MCP layer for ecommerce if you want to be agent-ready.
• Build PR/brand visibility campaigns: scholarships, local partnerships, or unique data releases that can attract coverage and links.
• Test LLM-assisted drafting workflows: use Claude/ChatGPT to create outlines, then human-edit and add proprietary assets.

Long-term (6-18 months)

• Design a GEO strategy aligned with content, PR, technical, and product teams.
• Invest in UX suitable for voice and AR consumption, concise answers, clear CTAs, and verification steps for agentic actions.
• Monitor and iterate conversion models (calls, bookings, agent-confirmed orders) rather than just pageviews.

Tools and Tactics the Panel Recommends

• Google Search Console and Google Ads for direct keyword signal and performance tracking.
• MOZ or SE Ranking for keyword tracking and audits (use them as directional tools, not exact volumes).
• Call tracking platforms for local conversion measurement.
• LLMs (Claude, ChatGPT, Perplexity) are used as ideation tools to combine outputs and verify.
• Structured data and schema plugins for CMS to make your facts machine-readable.

FAQ: SEO, LLMs, and Agentic AI

Q: Is SEO dead now that LLMs answer questions?

A: No. SEO is not dead, but it’s changing. You must think beyond classic organic traffic metrics. Ranking still matters because LLMs and agents often pull from high-ranking sources. Additionally, local visibility, brand mentions, and machine-readable signals are becoming part of SEO’s expanded remit.

Q: Should I stop creating content because AI can answer questions?

A: No. But stop creating low-value content. Focus on unique perspectives, proprietary data, and content that helps users take action. Use LLMs to draft and iterate, but always add original insights and verification.

Q: Can LLMs replace keyword research tools?

A: Not entirely. LLMs can suggest keywords and conversational phrasing, but do not provide reliable search volumes or conversion estimates. Use Google Ads, Search Console, and established SEO platforms for volume and trend validation.

Q: How do I make my ecommerce site agent-ready?

A: Expose secure APIs for product data and orders, implement an MCP layer where agents can query and request actions, and design secure confirmation flows for purchases initiated by agents. Start with authenticated repeat-purchase flows and add features iteratively.

Q: Will LLMs show paid results or ads?

A: Likely yes in time. The panel discussed that monetization experimentation is happening across platforms. Expect ad formats and sponsored placements to evolve in AI-generated responses over time.

Q: How do I handle fraud when agents can buy for users?

A: Implement verification steps (notifications, confirmations), require an authenticated account for agent actions, and use behavior analytics to flag unusual orders. Start conservatively: allow agent-initiated suggestions for new users but require human confirmation for purchases until trust is established.

Conclusion: Adapt, Measure Differently, and Focus on Real-world Signals

The discussion clarifies that SEO is not a static list of tasks. The discipline must evolve to account for LLMs, generative search, and agentic behaviors. Successful companies will combine classic technical SEO and content best practices with new priorities: brand mentions, local signals, call tracking, booking readiness, and machine-friendly APIs.

Use LLMs to scale ideation and production, but invest in human editing, original data, and PR campaigns that create real signals an LLM will trust. Track conversions differently, measure calls, bookings, agent-confirmed purchases, and brand mentions alongside pageviews.

Finally, remember that this is an early stage in a long technological shift. Some tactics will become standard, and others will fall out of favor. What will remain constant is that businesses that focus on user intent, trustworthiness, and measurable outcomes will thrive regardless of how the surface of search changes.

For more insights and expert services, visit Bright Vessel and Bright Code.