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SEO in the Age of AI Mode: Will Small Businesses Survive Google’s Next Move?

SEO used to feel like a race to the summit: stack backlinks, polish keywords, climb the rankings, and grab the clicks.

But the summit is shifting under our feet. Google’s AI Overviews, its first wave of “AI Mode”, are already rewriting the rules. And the data is sobering:

 

This doesn’t mean rankings and clicks are gone. Algorithms still run, and traditional SEO still matters, especially for commercial, local, and navigational searches. 

But it does mean the old race to the top is no longer the whole game.

Google is moving toward a world of reasoning engines, RAG (Retrieval-Augmented Generation), page embeddings, and user embeddings. In this new paradigm, the question isn’t “How do I climb the rankings?” It’s “How do I make my content retrievable, trustworthy, and useful enough for the AI to even pull me into the conversation?”

That’s the new battleground. And here’s where small businesses must decide: adapt now, or risk becoming invisible tomorrow.



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Mafê Mollo

Founder

What Are Reasoning Engines, RAG, & Embeddings?

To discuss the “AI Mode” future, it helps to understand some technical building blocks currently emerging in 2024-2025.

Reasoning Engines

These are systems that, beyond simple keyword matching or static ranking, can interpret, synthesise, and reason over content.

They may combine world knowledge, context (user’s past interactions, user embeddings), up-to-date facts, and retrieved relevant documents to generate answers. Rather than relying purely on fixed ranking signals, they “think” when asked.

RAG (Retrieval-Augmented Generation)

  • RAG is a technique where a large language model (LLM) first retrieves relevant pieces of content (documents, passages) from some corpus, then augments its generation using that retrieved content. This helps ensure outputs are grounded in real data, both accurate and relevant.
  • In particular, Google’s Vertex AI “grounding with search” and grounding via enterprise data are work in this direction: the model first pulls in facts/data, then uses those facts to generate answers. 

 

Embeddings: Page, Query, User Embeddings

  • Page embeddings: numeric vector representations of pages or documents in “semantic space.” They represent meaning beyond exact keyword matches. When you query, matching is done via similarity in embedding space.
  • User embeddings: capture the signals about a user: their history, preferences, behavior. That means results may be personalized not just by location or device, but deeply by what past content the user liked, clicked, etc.
  • Query embeddings + task-type embeddings: modern models like those in Vertex AI can “tag” embeddings by task (e.g. “question answering”, “document retrieval”, “fact verification”), improving relevance between query and answer. 


These tools are increasingly central to state-of-the-art search / AI systems. 

For instance, Google’s embedding models now support task types to improve quality in RAG systems. 

What Changes With AI Mode?

When AI Mode dominates search, the game flips:

  • No More “10 Blue Links” → AI delivers direct answers.
  • CTR Collapse → Users get answers without clicking. In tests, only ~8% always click through AI overviews (Exploding Topics, 2025).
  • Trust & Authority > Keywords → AI won’t pull from whoever has the most backlinks; it’ll pull from whoever is most reliable.
  • Personalisation Runs Deep → With user embeddings, your “best answer” may differ completely from someone else’s.

Why Big Companies Will Dominate (Unless You Outsmart Them)

Will Big Companies Have an Advantage?

Yes, in many ways, big players are likely to benefit first and more easily in this new paradigm. 

Here’s why:

  1. Data scale / content breadth
    Large companies typically have vast archives of content. They generate many documents, whitepapers, FAQs, user-generated content, etc. This rich corpus gives them more material to be retrieved and embedded by RAG systems.
  2. Brand strength & trust (E-E-A-T)
    When an AI model retrieves and integrates information, it needs to trust sources. Big brands have stronger brand signals, more visibility, more external validation. They’re more likely to be picked in grounding and source attribution. This enhances visibility in AI Mode.
  3. Technical & infrastructure capacity
    Building embeddings, maintaining vector databases, ensuring content is structured for retrieval, testing RAG pipelines, staying up-to-date with AI developments costs money, both in engineering and content creation. Big firms can hire specialists; SMEs often cannot.
  4. Up-to-date / authoritative content
    For AI Mode, freshness, factual accuracy, relevance, and “trusted” content become even more critical. Large players often have more resources (lawyers, researchers, editors) to maintain that.
  5. Ability to experiment with proprietary data & personalisation
    Big companies can build their own user embeddings, use private data, invest in personalisation, offering experiences tailored more deeply. They also have budget for AI/ML R&D (Artificial Intelligence / Machine Learning Research & Development).

The SEO Landscape in 2025: Supporting Data

Google’s Dominance

  • Market Share: Still 89%–92% globally (slight drop from 2023).
  • Search Volume: Over 13.7 billion searches daily, exceeding 5 trillion annually.
  • User Needs: Local business queries, product searches, and real-time updates remain Google’s core strength.

 

AI Tools Are Growing

  • ChatGPT: Over 1 billion daily queries and 700M+ weekly active users.
  • Gemini: 450M+ monthly users, integrated directly into Google Search.
  • Others (Perplexity, Copilot, Grok): Together gained 0.13% of search traffic, a 4× YoY growth.

Do Small Businesses Still Have a Place?

Even with these advantages for big players, small businesses aren’t automatically doomed. There are niches, strategies, and contexts in which they can still shine.

Where Small Businesses Can Compete

  • Hyper-niche content / local focus – If you focus on very specific, localised, or underserved queries, your content may be among the few available for retrieval in that niche. Big players often generalise; small players can master the niche.
  • Speed & agility – Small businesses can respond faster, for example, producing new content in response to customer questions, new local events, trends, or shifts. Big companies move slower due to layers of process.
  • Authenticity, brand voice, trust in micro-communities – Small businesses often have more direct relationships with local customers, more authentic voices, better capability to build trust and community, which may help both for user embeddings and for human trust.
  • Partnerships and collaborations – SMEs can collaborate, co-create content, use syndication, guest contributions to amplify reach without needing huge budgets.

 

What Becomes Harder

  • Breaking into the retrieval corpus – If AI Mode relies on curated corpora or ground-truth datasets, being selected (or found) becomes harder.
  • Investing in the technical infrastructure – Embeddings, vector search, task-type embeddings, grounding, maintaining authoritative data, these all require investment.
  • Competing on breadth and freshness – Big players often have content covering many topics extensively. To match, SMEs must be very smart about which topics to tackle.

 

So, small businesses will have a place, but it will be more demanding. It won’t be enough to do “old-SEO + hoping for the best”.

 

Let’s rephrase it, so we can understand better!

 

Where You Can Win:

  • Hyper-Niche Focus → Dominate long-tail or local queries.
  • Agility → Publish faster, react quicker, adapt without red tape.
  • Authenticity → Build trust through real voice, case studies, customer stories.
  • Partnerships → Co-create with aligned businesses to punch above your weight.

 

What Gets Harder

  • Breaking into retrieval corpora (the sources AI trusts).
  • Matching breadth of content that big players own.
  • Building the tech stack (vector databases, structured data, semantic signals).

What Experts are Saying Now: Trends & Concerns

Several trends and debates are already underway in 2024-2025 that point to this AI Mode future, or at least glimpses of it.

  • AI Overviews / Search Generative Experience (SGE): As noted by Exploding Topics and others, Google is placing more AI summaries or overviews in SERPs. These reduce clicks, altering CTR dynamics. 
  • Task-type embeddings: Google’s Vertex AI recently introduced embeddings that are optimized by task (question answering, fact verification, etc.). This improves RAG system quality but raises technical threshold.
  • Grounding & retrieval before generation: Google’s “grounding with search” for its Gemini models, and grounding with enterprise data or custom corpora, are forces pushing toward that reasoning engine model. 
  • SME / small business challenges in content & resources: Reports like “Is SEO Worth It for Small Business in 2025?” and “How Small Businesses Are Hiring SEO Trends 2025” highlight that while small businesses recognise the need for SEO/AI tools, lack of expertise, budget, and scale remain big obstacles. 

Best Practices to Future-Proof Your SEO Now

Don’t wait for the AI switch to flip. Start adapting today:

Best Practices for Small Businesses (and Anyone) to Start Now

Even before full AI Mode arrives, you can begin preparing. Here are actionable strategies:

Area

What to Do

Content Strategy

Focus on depth over breadth. Pick a few narrow but high-value topics (including long tail / intent-driven queries). Create content that answers user questions fully, clearly, with updated data. Use FAQs, schema, structured data.

Use Embeddings & Semantic Signals

If possible, optimise content around semantic relevance, not just keywords. Explore tools / plugins / platforms that allow you to test embeddings similarity, or vector search. Tag content so it can be retrieved for questions. For instance, use structured Q&A formats.

Authority, Trust & Freshness

Keep content accurate, updated, well-sourced. Build brand signals: citations, reviews, user feedback. Local case studies help. Freshness matters for grounding systems.

Technical Readiness

Improve site speed, mobile UX, core web vitals. Ensure content is well structured: head tags, sections, metadata. Use internal linking well. Consider how your site architecture supports retrieval of relevant content.

User Experience, Personalization

Collect and use first-party data (where privacy permits). Understand user behaviour on your site: what they search for, dwell time, what helps them. If possible, develop basic user profiles, personalize or segment content.

Monitoring & Experimentation

Watch trends: how Google’s AI Overviews evolve; how task-type embeddings are used; any announcements re new search modalities. Use A/B testing. Measure not just rankings, but CTR, dwell time, queries where users stay in SERP vs click.

Key Takeaway

RAG doesn’t care about your backlinks. It cares if your content answers the question, right now, better than anyone else.

SEO and AI Mode FAQ

Will SEO exist in 2030?

Yes, but not as rankings. SEO will mean making your content retrievable and trustworthy for reasoning engines.

 

What is RAG in simple terms?

RAG = Retrieval-Augmented Generation. The AI fetches facts, then generates an answer grounded in them. Think “Google + ChatGPT in one.”

 

Can small businesses still win with SEO in the AI era?

Yes, if they stop trying to out-volume big players and instead go narrow, authentic, and community-driven.



Conclusion: Prepare, But Don’t Panic

Google’s AI Mode isn’t the death of SEO, it’s the death of lazy SEO.
Big companies will dominate with scale, but small businesses can still punch above their weight with sharper strategy, niche focus, and speed.

Don’t wait until you’re invisible.


Book a strategy session with Chama today and let’s future-proof your SEO before the AI tide rises.