How Google’s New AI Mode Actually Thinks — Inside the System That Ranks, Synthesises, and Answers

Key Takeaways

Google’s AI Mode uses Retrieval-Augmented Generation (RAG) to synthesise data, not just display links.
It employs agentic reasoning — breaking complex user requests into smaller, goal-based actions.
Ranking now depends on trustworthiness and structured data, not keyword stuffing.
Carter Media helps brands optimise for AI discovery, not just search visibility.

The Search Engine That Thinks

In 2025, Google quietly flipped the internet.
Traditional search results are being replaced with AI-generated answers — long-form, contextual summaries that combine dozens of sources into one unified, conversational response.

This is Google’s AI Mode, sometimes referred to as “agentic AI” — a system that doesn’t just search, but reasons.

It’s the most dramatic shift in search since PageRank was invented, and it’s changing the rules of SEO, content strategy, and digital trust.

From PageRank to DeepRank — The Evolution of Search

For 25 years, Google’s algorithm ranked pages by links and keywords. PageRank rewarded popularity. Then came RankBrain and BERT, which introduced contextual understanding and natural language processing.

Now, AI Mode introduces a third dimension: synthesis.
Instead of showing ten blue links, the model reads, interprets, and assembles a single, dynamic answer drawn from multiple sources — company websites, market reports, news outlets, and social media sentiment.

As Google puts it, the system “synthesises information from various public data points” to deliver a reasoned response, not a list of options.

That means the future of visibility depends less on how often you post — and more on how machine-readable, factual, and trusted your data is.

Retrieval-Augmented Generation (RAG): The Engine Behind AI Mode

What It Does

Retrieval-Augmented Generation is the architecture that powers AI Mode. It’s a two-step intelligence system:

Retrieval: Google’s AI searches across indexed web data, academic databases, business directories, and news outlets to find relevant, high-authority information.
Generation: The AI then uses a large language model (LLM) to generate an answer that synthesises the retrieved information into a clear, human-readable explanation.

Unlike static SEO algorithms, RAG continuously adapts to user context — weighing brand reputation, relevance, and sentiment in real time.

What It Means for Marketers

Your website isn’t just competing for clicks — it’s competing for inclusion in the AI’s synthesis layer.
The AI doesn’t cite everything; it chooses the most trustworthy signals to build its narrative.

That’s why E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) now determines whether your content becomes a source of truth — or disappears behind an AI-generated paragraph.

Agentic AI — How Google’s AI Mode “Thinks”

AI Mode uses a technique called query fan-out.
When a user types a complex query like:

“Find a sustainable jewellery brand in Australia that’s family-owned, offers ethically sourced diamonds, and delivers nationally.”

The system breaks this into multiple sub-tasks:

Identify family-owned Australian jewellers
Analyse product pages for “ethically sourced” claims
Verify delivery reach through customer reviews and listings
Rank based on E-E-A-T, customer sentiment, and media coverage

Each sub-query runs in parallel, retrieving fresh, factual data from authoritative sources. The model then synthesises everything into one contextual answer.

This is what makes Google’s AI Mode agentic — it performs reasoning, decision-making, and planning on behalf of the user.

Why “Ranking” Is No Longer a Formula

AI Mode has no single “ranking score.” It’s a dynamic weighting system that evaluates dozens of contextual features depending on the query type:

Factor	Weighted More When…	Example
Longevity & Heritage	The query values trust or history	“Most established jewellers in Australia” → Wallace Bishop ranks higher.
Sentiment & Reviews	The query implies quality or satisfaction	“Best customer service jewellers” → Positive review-weighted brands rise.
Topical Authority	The query targets an industry or trend	“Sustainable jewellery brands” → Frequent mentions in credible eco outlets matter.
Freshness	The topic involves trends or pricing	“New luxury watch releases 2025” → Up-to-date content is prioritised.

For the first time, Google’s AI ranks ideas, not just URLs.

Why Data Integrity Is the New SEO Strategy

The AI Mode era demands more than optimised copy. It demands optimised truth.

Here’s what Google’s AI weighs when evaluating brand data:

Structured markup (schema, product metadata, and accessibility tags).
Transparent About pages (brand heritage, founders, mission statements).
Consistent NAP data (Name, Address, Phone) across platforms.
Author pages that establish real expertise.
Verified, review-backed sentiment (no fake testimonials).

These are machine-readable trust signals — and they form the foundation of AI-driven visibility.

At Carter Media, our AI SEO audits now focus on this synthesis layer — ensuring that your content isn’t just visible to users, but understood by machines.

The End of Clicks — And the Rise of Citations

Zero-click results are the new normal. AI-generated summaries answer the query directly, often without a user ever leaving the page.

So how do brands win?
By becoming the cited source — the voice that the AI quotes, summarises, or uses as its foundation.

Google’s AI Mode now displays small footnote-style citations below AI summaries. Brands mentioned in those snippets will capture residual trust, authority, and recognition.

That’s why we call this new discipline Agent Optimization — optimising for AI assistants and agentic systems, not just traditional search.

Carter Media’s Framework for AI-Ready SEO

We’ve evolved our approach to meet the new era of AI-powered discovery:

1. AI-Readability Audits

We evaluate your site’s technical structure, schema markup, and content clarity to ensure your data is ingestible by AI systems like Google’s RAG pipeline.

2. E-E-A-T Enhancement

We help you build author credibility, transparent business pages, and review strategies that reinforce expertise and trustworthiness.

3. Structured Data Mapping

From product listings to local business schemas, we implement markup that connects your data directly to AI search contexts.

4. Brand Mention Strategy

We target authoritative publications, directories, and forums to strengthen your digital footprint — making your brand more “discoverable” by AI.

5. AI-Safe Content Creation

All Carter Media content is written for both humans and algorithms — factually correct, citation-rich, and semantically layered for machine interpretation.

The Future — Visibility in the Age of AI

Search has become symbiotic. Google’s AI Mode no longer crawls; it comprehends.
It reads between the lines of your content, assesses your credibility, and curates a personalised, synthesised answer for every user.

In this world, truth and transparency outperform tactics.
And Carter Media is already building for it — creating content ecosystems designed to be trusted, cited, and surfaced by intelligent search.

💡 Future-Proof Your Visibility

Be part of the synthesis, not the silence.
📩 hello@cartermedia.au | 🌐 cartermedia.au

Sources

Google Search Central — How the Ranking Process Works (2025)
Google Cloud — Retrieval-Augmented Generation (RAG) Explained (2024)
The Keyword — AI in Search: Going Beyond Information to Intelligence (2025)
StartupHub.ai — Google Search Agentic AI Goes Global (2025)
ADMA — From PageRank to DeepRank: Attracting AI-Driven Traffic (2025)
ScienceDirect — Explainable Neural Network-Based Approach (2024)
Vellum AI — The Ultimate LLM Agent Build Guide (2025)