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SEO vs AI SEO: How to Get Found (and Chosen) in the Age of Generative Search

By Mhairi Petrovic, founder of Out-Smarts Marketing and search specialist, with support from AI
Published: October 2025

TL;DR

Search isn’t dying; it’s rewriting its own rules. Generative AI platforms like ChatGPT, Perplexity, and Google’s AI Overviews have shifted discovery from lists of links to synthesized, conversational answers.

For healthcare care, and purpose-led organisations, this means visibility now depends on being cited as the trusted source, not just ranking well.

Winning in this new landscape means:

Keeping SEO fundamentals: Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T); structured content; and technical hygiene.
Creating content with clear, verifiable answers.
Maintaining accuracy, recency, and trust signals that AI engines can verify.
Tracking new KPIs like citations in AI Overviews and question-led engagement.

SEO hasn’t been replaced by AI SEO optimization; it’s expanded to include it.

From Found to Chosen: Understanding the New Search Ecosystem

For decades, SEO worked like a library: you searched for a keyword, and Google handed you a tidy stack of results. Strong keywords, credible backlinks, and technical consistency helped you climb that stack.

AI search has evolved that model. SEO is now like talking to an expert: you ask a question, and an answer appears in a conversational, summarized form, based by sources hidden behind the synthesis.

It’s powerful for users, but presents some high-stakes challenges for organisations. If your content isn’t chosen or cited by another source or page, you risk being written out of the digital conversation entirely.

Gartner estimates organic traffic could drop by 25% by 2026 as AI-driven search absorbs more queries into direct answers. Google’s rollout of Google AI Overviews confirms that discovery now happens within AI responses, not just on result pages.

Regardless, being found still matters. But being chosen, trusted, cited, and surfaced as the source, matters more.

The Common Ground: What Still Works Everywhere

Despite the changes, the foundations of search haven’t vanished. Both traditional SEO and AI SEO depend on:

1. Content quality and E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness remain non-negotiable. It’s still important to demonstrate your qualifications, cite credible data, and publish transparent editorial policies. (Google Search Central)

2. Structured content and schema: Use clear headings, consistent hierarchies, and schema markup (FAQ, Article, Organisation) to help crawlers and AI understand context and relationships.

3. Internal linking and topical depth: Build internal networks of content to prove subject mastery — this improves answer extraction and user navigation alike.

4. Credible citations: Link to reputable, verifiable sources. For example, a healthcare provider might link to Health Canada, Statistics Canada, and The Canadian Institute for Health Information (CIHI). Outgoing links strengthen your perceived authority in both human and AI evaluation.

Where Paths Split: SEO vs AI SEO

Traditional SEO Still Matters

Even as AI-driven discovery changes how people find information, strong SEO fundamentals remain the foundation for effective online presence. The tactics below still contribute to being seen, trusted, and technically sound enough for both search engines and AI systems to reference.

Keyword strategy: Align content around search intent, with natural inclusion of primary and secondary keyword phrases that match what users are actually looking for.
Technical excellence: Core Web Vitals, mobile responsiveness, indexability, and canonicalisation (choosing the preferred URL of a webpage for search engines to crawl and rank) remain key.
Backlink authority: Quality mentions on third-party sites and digital PR still correlate strongly with rankings.
Analytics: Track impressions, clicks, click-through rate (CTR), and conversions via Search Console and Google Analytics 4.

AI SEO Requires New Thinking

AI SEO calls for a shift in mindset, from optimising for algorithms to communicating with machines that think more like people. With the rise of generative search, The focus now is on clarity, credibility, and conversation: creating content that answers questions directly, proves its claims, and stays fresh enough to be trusted as a reliable source. Be sure to consider:

Answer-first design: Lead each key page with a concise, direct answer. Then expand into proof, data, and examples.
Conversational tone: Optimise for how real people ask questions — “How do I choose a safe care home?” not “senior care options BC.”
Data integrity: Cite verifiable, localised data (e.g. Government of Canada Open Data) and update regularly.
Recency signals: Add visible timestamps and change logs; freshness now outweighs static authority.

For example, a patient safety organisation could improve visibility in AI-generated results by refreshing FAQs with current incident data and linking to trusted sources such as Healthcare Excellence Canada.

Why Care and Purpose-Led Organisations Need a Different Playbook

Care and purpose-led organisations operate in a space where trust is everything. People turn to them for reliable guidance on health, safety, and wellbeing, so every word published carries weight. That’s why these sectors need a more deliberate approach to SEO and AI visibility: one that treats accuracy, transparency, and accountability as non-negotiable parts of the strategy. This includes:

Compliance and accuracy: Content must align with current standards and regulations such as PIPEDA and provincial health privacy frameworks.
Source transparency: Make author credentials, publication dates, and updates visible.
Ethical communication: Clarity, empathy, and transparency matter. Avoid jargon, always disclose sources, and explain limitations where appropriate.
Trust signals: Prominently display author bios, credentials, and review cycles. Include a “last updated” date and brief note on the relevant review processes.

These cues help AI systems and humans alike assess reliability, and reward it by using it in AI search results.

The Out-Smarts Dual-Optimisation Framework

The Out-Smarts Dual-Optimisation Framework is a practical roadmap for balancing traditional SEO with emerging AI search demands. It’s designed to help care and purpose-led organisations strengthen visibility, credibility, and compliance across both SEO ecosystems. Each phase builds on the last, from strengthening technical foundations to refining content, enhancing accessibility, and optimizing the right mix of SEO and AI-era performance metrics.

Here are a few activities we typically include in each phase of a Dual-Optimisation Framework project:

Phase 1 — Foundation Building

Audit content for keyword gaps and unanswered questions
Implement schema for Organisation, FAQ, and Article pages
Standardise architecture and fix technical errors
Publish E-E-A-T assets: bios, editorial policy, and review notes

Phase 2 – Content Evolution

Rewrite high-intent pages with an answer-first intro, followed by context and examples
Build FAQ clusters from site search data and “People Also Ask”
Add concise, citable definitions and sector data from sources

Phase 3- Technical and Accessibility Optimisation

Improve Core Web Vitals and ensure pages are scannable (short paragraphs, bullets, headings)
Include transcribed videos or downloadable summaries where relevant
Optimise for voice and assistive interfaces using clear Q&A blocks and pronounceable phrasing

Phase 4 – Monitoring and Adaptation

Continue tracking traditional SEO metrics (rankings, traffic, conversions)
Add new AI SEO metrics:
- Citations in Google AI Overviews and Perplexity
- Question-led traffic
- Engagement with FAQs and informational resources
Conduct quarterly content freshness checks and publish change logs to maintain authority and trust

Process in Practice: Building Sustainable SEO + AI Workflows

Sustainable SEO and AI optimisation rely on consistency, not one-off fixes. The process below outlines how to weave AI tools and traditional SEO practices into a single, repeatable workflow to keep your content accurate, empathetic, and visible across both human and machine audiences.

Plan: Map key customer journeys, from awareness to returning visitors,and identify what content each audience needs based on their search intent at different stages.
Draft: Use AI tools for ideation and outline support only. Keep all final writing and editing human-led to ensure tone, compliance, and empathy.
Review: Cross-check every fact, citation, and claim against credible Canadian sources. Maintain a reviewer-of-record system for document oversight.
Update: Schedule quarterly reviews for top pages. Replace outdated stats or guidance as soon as possible and update change logs publicly.
Measure: Use dashboards to track both classic SEO and new AI indicators — including brand mentions in AI platforms and referral patterns from answer engines.

This process shifts your SEO from a “set-and-forget” strategy to a live, measurable trust engine to be reviewed more often.

Measuring What Matters in the AI Era

Traditional metrics (impressions, click-through rate, rankings, and conversions) remain core indicators of reach and performance. But, AI-driven search introduces a new layer of visibility measured by trust and citation.

Measuring what matters for AI search includes:

Citations in AI results: Track how often your brand or content is referenced in AI Overviews or platforms like Perplexity. (This is currently a manual process, but one day it may be automated).
Referral traffic from AI tools: Use UTM parameters or referral data to identify visits originating from AI interfaces (like Chat GPT)
Question-led engagement: Monitor (via Search Console and GA4) which pages draw visitors through natural-language or voice-style queries.
Brand trust signals: Measure mentions and backlinks from credible publications; they reinforce authority in both human and AI evaluations.

In our evolving AI era, success isn’t just about clicks; it’s about being recognised as the source worth quoting.

Practical Checklist: Turning SEO and AI Uncertainty into Action

The gap between knowing what’s changing and actually doing something about it is where most organisations stall. To help, we’ve created this checklist to turn the shifting landscape of SEO and AI search into concrete, manageable steps, the kind your team can act on without overhauling everything at once. Each action strengthens visibility, accuracy, and trust, one update at a time:

Identify 10 top-performing pages to convert into answer-first format
Update schema (FAQ, Article, Organisation) and resolve any technical issues
Add visible author credentials and update stamps
Refresh data quarterly with relevant stats and link to current sources
Track both search visibility and AI citations
Document updates and keep a public change log

SEO Hasn’t Been Replaced

SEO hasn’t been replaced; it has evolved. In the age of generative search, clarity, transparency, and recency are what help healthcare, senior care, and patient safety organisations get found and chosen by both humans and AI.

What’s next for your organization? Keep your SEO fundamentals sharp. Lead with clear answers. Refresh often. Cite everything.

Do this well and your organisation won’t just stay visible; it’ll stay trusted.

Author: Mhairi Petrovic
Founder, Out-Smarts Marketing

Mhairi Petrovic is the founder of Out-Smarts Marketing, a digital marketing agency that helps care, senior care, and purpose-led organisations strengthen their online visibility with ethical, transparent strategies. With over 20 years of experience in SEO, online advertising, and digital strategy, she helps teams navigate the shift toward AI-informed marketing, ensuring their work remains discoverable, credible, and trusted in the age of generative search. Connect with her on LinkedIn.

Learn more about Out-Smarts Marketing