The world of search is changing fast. The rise of AI search tools like ChatGPT, Perplexity, Bing Chat, and Google’s own AI Overviews means that users no longer always click through to websites. Instead, they often get an answer directly in the chat or summary. This shift presents both risks and opportunities for small businesses that depend on visibility through search.
With Google’s AI-Powered search result now having over 1 billion users, AI search such as GEO and AEO is not something you should overlook.
Contents
In this post, we’ll walk through:
- What “AI Search” really means
- How it’s different from traditional SEO
- The threats small businesses are facing
- The opportunities to get ahead
- A practical “to-do” list for small businesses
- Predictions & what to watch next
Let’s start by defining our terms.
What Is “AI Search”?
When most of us say “search,” we think of Google (or Bing) and the classic list of blue links. But “AI search” refers to systems that generate responses using language models, sometimes along with citations or links, rather than simply ranking web pages.
Examples and forms:
- Chatbots / conversational AI (e.g. ChatGPT, Bing Chat) — users ask a question, and the model returns a synthesized answer.
- Answer engines / AI Overviews in search engines (e.g. Google’s AI Overviews) — for certain queries, Google will show an AI-generated summary at the top of the results.
- Hybrid models — tools that combine retrieval from the web + generative summarisation.
- Zero-click search experiences — where users get what they need without clicking through to a site.
Because the model tries to “answer” the user directly, the old pattern of “user types query → get list of pages → click one” is being disrupted.
How AI Search Differs from Traditional SEO
Below is a comparison of key differences and how that changes what we need to optimise for:
Factor | Traditional SEO | AI Search / Answer Engines |
Traffic model | Users click through to pages, generating visits | Users may get answers without clicking (zero-click) |
Ranking signal emphasis | Backlinks, on-page SEO, domain authority, content relevance | Freshness, authority citations, structure, “source value” |
User interaction | Users scan a page, click more links | Users ask follow-ups, may expect conversational answers |
Opportunity for snippets | Featured snippets, structured data, “Position 0” | Being cited within AI’s answer, being used as source material |
Keyword targeting | Focus on exact or related keywords | Focus shifts to intent, semantic relevance, question formulation |
A few specific emerging features to pay attention to:
- AI Overviews: Google’s AI Overviews are already showing up in many queries.
- Zero-click search: more users are getting answers directly, without clicking.
- Generative Engine Optimization (GEO): optimising to be included in AI-generated answers and summaries rather than just traditional rankings
- “Big Brand Bias”: research suggests AI models tend to prefer authoritative sources and brands when selecting material for answers.
- Feedback loops & citation bias: AI models depend on which sources they cite, so being included as a trusted citation is critical.
Because these models sometimes summarise multiple sources, even a smaller site can “get noticed” if it has high-quality, well-structured, authoritative content.
The Threats Facing Small Businesses
- Loss of click-throughs
When users get the answer immediately, they may never visit your page. That means fewer visits, fewer leads, fewer conversions. Many websites are already seeing declines in organic traffic in certain verticals. - Authority and brand bias
AI models often “trust” larger or more established sites. Small businesses may struggle to break into the citation circle. - Hallucinations & misinformation
Generative models sometimes make factual errors or misinterpret data. If your content is pulled into an answer, you risk misrepresentation. - Over-saturation & content clones
Many marketers will be using the same AI tools. That raises the risk of generic content or duplication, which weakens distinctiveness and value. - Uncertainty & rapid shift
The rules are shifting. What works today may not tomorrow. Businesses relying solely on one channel (Google organic traffic) are vulnerable
The Opportunities for Small Businesses That Adapt
- Niche authority & unique insights
AI struggles with deep, specific knowledge or experiential content. If your business shares insights, case studies, original data, or domain expertise, that can stand out. - Becoming a trusted citation
If your content is referenced in AI answers (with citation), that gives you indirect visibility. You become part of the “source mix” AI uses. - Optimising for intent & questions
Structuring your content to answer questions directly, with concise answers plus elaboration, positions you better for AI. - Leverage semantic SEO & structured data
Proper use of schema markup, FAQ schema, heading hierarchy, “speakable” content helps models parse your content better. - Hybrid content + formats
Using infographics, videos, podcasts, or interactive elements helps diversify how AI may pick up your brand. - Diversified traffic strategy
Don’t put all your eggs in one basket. AI search, social media, email, partnerships — a multi-channel approach helps.
What Small Businesses Should Do: A Practical To-Do List
Here’s a step-by-step guide:
1. Audit existing content
- Try using a tool such as Agency Dashboard, which has a free trial.
- Find your top-performing pages.
- Evaluate whether they already answer clear questions directly (i.e. short summary at top).
- Add structured headings (H2, H3) with question phrases.
- Mark up FAQ schema or “question/answer” blocks.
- Ensure your content is clean, authoritative, with supporting sources and references.
2. Build content around user questions
- Use tools like “People Also Ask,” ChatGPT itself, or AI prompt research to find common user queries.
- Write content in a question/answer format: short answer, then deeper detail.
- Use subheadings like “What is X?”, “How to do X?”, “Why X matters?”
3. Use structured data & markup
- FAQ schema, Q&A schema, “speakable” schema where possible.
- Use standard schema types (Article, BlogPosting, WebPage).
- Signal to crawlers which parts are concise answers.
4. Cite and reference sources
- When you make a claim or fact, link to trusted sources.
- When you use stats or data, show methodology or source.
- This helps AI models see your content as trustworthy.
5. Repurpose content to other formats
- Turn articles into short video scripts, infographics, slide decks, social posts.
- Use transcripts and captions (text content helps AI).
- Visual content “tags” (alt text, captions) can be parsed too.
6. Monitor AI-driven traffic & visibility
- Track referrals from chatbots or AI tools (if possible).
- Use brand mentions, citations, or “mentioned in answer” alerts.
- Monitor organic traffic dips and correlate with AI release dates.
7. Stay agile & experiment
- Test small articles optimised for AI vs classic SEO and compare performance.
- Keep up with emerging features: Google AI Mode, new SERP layouts, AI overviews expansion.
- Be ready to pivot strategy based on what’s working.
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