No GPTs (generative pretrained transformers) were harmed in the making of this post, though they certainly helped. And, chances are, you found this article through one of them.

If you haven’t already, please go read the interview with Adam Landis, strategic advisor at Branch, on the shift from search engine optimization (SEO) to artificial intelligence optimization (AIO) first. It perfectly captures the strategic reality we’re facing: Search is no longer a page of blue links; it’s personalized AI responses. We don’t “Google” — we “ask” (em dash intended).

But that leaves the big question: How do you actually implement AIO?

After working with Branch customers, testing grading tools like HubSpot’s AI Search Grader and Gushwork and tracking emerging patterns in AI discovery, one thing is clear to me: Brands succeeding in AIO aren’t reinventing the wheel. They’re building on fundamentals and adapting for AI realities.

I’ve structured my learnings into this five-pillar AIO growth framework, a practical roadmap for brands who want to move beyond SEO and capture growth in an AI-first world.

• Pillar 1: Traditional search foundations
• Pillar 2: AI visibility and traffic intelligence
• Pillar 3: AI-native content architecture optimization
• Pillar 4: Establishment of authority via strategic community presence and external validation
• Pillar 5: Mobile growth optimization

The brands getting this right are building sustainable, competitive advantages. Researchers at Gartner expect that by 2026 traditional search engine volume will decline by 25%, with search marketing losing market share to AI chatbots and other virtual agents.

This blog will set you on the right path to weather this expected change. It has two sections: an AIO Growth Framework: Grab and Go followed by an AIO Growth Framework: Deep Dive with detailed examples. Use what works!

The Five-Pillar AIO Growth Framework: Grab and Go

Quick reference: AIO growth framework overview

While AI evolves daily, making yesterday’s learnings feel outdated, the fundamentals of discovery remain constant: Protocols, crawlers, and link structures still matter. What’s new is how answers surface.

 Quick start: If you only have 30 minutes today, focus on pillar 1 (technical SEO) and set up basic AI traffic tracking from pillar 2.

Pillar 1: Fix your SEO before anything else

If your SEO is weak, your AIO strategy will fail. AI relies on trusted, indexed sources, the same signals search engines use.

• Clean up technical SEO.
• Optimize for Core Web Vitals.
• Get your metadata and schema in place.
• Ensure crawlability of all key content.

Google Search Central is the most authoritative resource.

Pillar 2: Measure what you can

Unlike SEO, where you track impressions, clicks, and rankings, AI platforms like ChatGPT provide direct answers within the interface. But when users do click through to sources, those clicks are highly valuable. You can and should track them.

• Set up UTM parameters to identify AI traffic (example: utm_source=%chatgpt%).
• Monitor HTTP referrer data, which is often available for Perplexity, Claude, and Gemini.
• Run your site through HubSpot AI Search Grader, Peec.ai, Gushwork, or similar tools to check your current AIO readiness and visibility.

A detailed table of known UTMS and referrers is available here.

Pillar 3: Generate AI-native content

To get cited, make content extraction-ready:

• Break long-form text into bite-sized chunks (i.e., atomic content units for the tech-minded).
• Use clear headings, structured Q&A, and TL;DR summaries.
• Add meta descriptions and schema that AI can pull in real time (this matters for real-time data extraction via RAG systems).

Pillar 4: Build authority beyond your site

AI doesn’t just read your site content. It also checks where others reference you.

• Be active in industry communities like LinkedIn, Reddit, and Stack Overflow.
• Secure mentions in trade media, podcasts, and research reports.
• Publish original data or benchmarks that others want to cite.

Pillar 5: Turn AI discovery into growth

AI-driven clicks are high intent. Don’t waste them.

• If you have an app, make sure your universal and app links are nailed so users land in the app, not the homepage.
• Show contextual install web-to-app banners like Branch Journeys to AI-referred traffic.
• Feed AI referral data into your customer relationship management (CRM) system and ad platforms to retarget using the exact content that earned you the citation.

What next? Plan your implementation and future-proof your strategy

These five pillars work together as an integrated system. Here’s how to prioritize your implementation.

Start with the fundamentals that matter most right now (0-90 days):

• Fix technical SEO and implement basic schema markup.
• Convert your top 10 pages to AI-friendly format with Q&A structure.
• Set up AI traffic tracking using UTM parameters and referrer detection.
• Engage in two to three relevant communities where your audience asks questions.

Prepare for what’s coming next (12-24 months):

• Multimodal content optimization as AI systems process more images or video
• Real-time content freshness will become increasingly important for competitive citation rates
• Voice search optimization for conversational AI interactions

The key: Focus on foundational best practices that work across all AI platforms rather than chasing platform-specific tricks that may change.

The Five-Pillar AIO Growth Framework: Deep Dive

Pillar 1: Traditional search foundations

They’re required for AI trust signals.

If you visit Google’s AI Overviews pages, the very first recommendation from the search leader is: “The best practices for SEO remain relevant for AI features in Google Search (such as AI Overviews and AI Mode). There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary. That said, it’s always good to review the fundamental SEO best practices”.

This is proof that the fundamentals of discovery haven’t changed, because the way the internet works hasn’t changed. Protocols, crawlers, and link structures still form the backbone of the internet and therefore discovery. What’s new is how answers surface.

AI systems rely heavily on indexed, high-authority sites that search engines already trust. Your technical SEO foundation determines whether AI systems consider your content citation worthy.

Implementation checklist:

• Structured metadata: Title tags, meta descriptions, and Open Graph tags optimized for AI parsing
• Semantic HTML: Proper heading hierarchy (H1-H3), ALT text for images, comprehensive schema.org markup
• Content freshness: Regular updates with timestamps, new pages, FAQs, and announcements
• Technical excellence: Core Web Vitals optimization, mobile responsiveness, fast loading speeds

Why this matters: AI systems use the same trust signals as search engines. E-E-A-T (experience, expertise, authoritativeness, trustworthiness) remains essential because AI models reference content that search engines have already validated as trustworthy.

Bonus tip: You could run your site today through Hubspot AI Grader, Peec.ai, Gushwork, or other similar tools to get a good assessment on your current standing.

Once your technical foundation is solid, the next critical step is measuring your progress systematically.

Pillar 2: AI visibility and traffic intelligence

Track performance, measure business impact, and optimize systematically.

Unlike SEO, where you track impressions, clicks, and rankings, AI platforms like ChatGPT primarily operate in low-click environments. The answer often lives inside the chat. But when clicks do happen, they are extremely worthwhile and leave traces. You should by all means measure what’s available today; it’s valuable insight.

Step 1: Set up AI traffic detection

Understanding where your AI-driven traffic originates is crucial. I recommend a dual detection strategy:

1. UTM parameter tracking: Measure traffic by checking UTM parameters that AI platforms add on certain links.
2. HTTP referrer detection: Measure traffic by checking HTTP referrer headers to see where users came from.

AI platform detection patterns:

chatgpt.com, openai%

chatgpt.com, chat.openai.com

claude%, anthropic%

claude.ai, anthropic.com

perplexity.ai%

perplexity.ai

gemini%, google-ai%

gemini.google.com

copilot%, microsoft%

copilot.microsoft.com

Attribution note: Some users see URLs in AI responses and manually type them into browsers, appearing as “direct” traffic. Monitor unusual spikes in direct traffic to specific pages; they’re a strong indicator of AI influence.

Step 2: Monitor your AI visibility

Use automated tools:

• Free options: Use HubSpot’s AI Search Grader and Gushwork’s AI Search Grader for quick visibility scoring.
• Comprehensive tools: Peec.ai and Otterly.AI are options for detailed tracking and competitor analysis.
• SEO platform add-ons: SE Ranking’s AI Visibility Tracker, Ahrefs, and SEMrush are adding AI tracking features.

What these tools track:

• Brand visibility across multiple AI platforms
• Competitive benchmarking
• Citation frequency and quality
• Sentiment analysis

The bottom line: Put your data to work

Once you have tracking set up and visibility tools running, your analytics will reveal what actually works. Look for spikes in direct traffic to specific pages (usually AI citations), identify which content formats drive the most AI referrals, and double down on topics that generate citations. The content getting AI citations isn’t always your highest-ranking pages; AI systems trust different signals. Use that insight. Create more content like what’s already working, and you’ll see your AI visibility grow naturally.

Pillar 3: AI-native content architecture optimization

Create content that AI systems love to cite.

AI systems don’t rank pages. They extract answers. Your content architecture should facilitate easy AI parsing and citation. Think questions, not keywords.

Key strategy 

Think of your content like LEGO bricks. Each section should make complete sense even if AI pulls it out of context and serves it up in a chat response.

Step 1: Publish AI-friendly landing pages with deep linking

Your content should provide direct, actionable value and allow AI to link users straight to the answer — or even into your app.

Good example

A fashion brand creates a page titled “How To Style a Classic Trench Coat for Spring” with:

• Concise, numbered outfit ideas
• Clear section headings for each look
• A summary paragraph at the top
• Deep linking so AI can send users directly to “Outfit Idea 3” or open the shopping app to that exact product

Bad example

A fashion brand creates a generic “Spring Fashion Trends” post filled with long, dense paragraphs, unclear structure, and homepage links that force users to search again.

Step 2: Implement comprehensive structured data

Add Schema.org markup to make your content machine-readable:

• FAQ Page – For common questions
• HowTo – For step-by-step instructions
• Product – For detailed product information
• VideoObject – For video guides
  

Good example

An e-commerce site uses Product schema to show size guides, materials, and care instructions, making it easy for AI to extract and compare.

Bad example

An e-commerce site buries Product details inside long marketing copy, leaving AI guessing.

Step 3: Make content extraction friendly

Structure your content so each section works as a standalone answer:

• Use clear, descriptive headings that mirror real user questions.
• Put the direct answer first, then add details.
• Break content into 300-500 word sections (perfect for AI retrieval).
• Write in a conversational tone that naturally answers “who, what, when, where, why, how” questions. This also prepares content for voice search.
• Include specific data, examples, and related terms naturally.

Remember: Each section should work like a complete mini-article that makes sense on its own.

Good example

A software as a service (SaaS) company creates a two-factor authentication (2FA) setup guide with:

• A heading titled “What Is Two-Factor Authentication?” (matches how users ask)
• A direct answer first: “Two-factor authentication adds a second security step to your login process, requiring both your password and a code from your phone.”
• Each platform having its own 400-word section: “Enable 2FA on iOS,” “Enable 2FA on Android”
• Specific steps, screenshots, and troubleshooting tips in each section

Bad example 

A SaaS company creates a 2,000-word security guide that buries 2FA setup in paragraph 12, with no clear headings and steps scattered throughout dense text blocks.

Step 4: Remove access barriers

• Keep help docs and FAQs public (no logins or gates).
• Ensure your robots.txt isn’t blocking important pages.
• Use a clear URL structure that reflects content purpose.
• Optimize for fast loading speeds.

Good example

Stripe, a payment processing company, keeps its entire documentation public and searchable:

• No login is required to view API guides, troubleshooting, or implementation examples.
• Clean URLs like stripe.com/docs/payments/accept-a-payment are used.
• Pages are fast loading with clear navigation.
• Robots.txt allows crawling of all docs.

Bad example 

A fintech startup gates its knowledge base behind user accounts, uses generic URLs like /support/article/12847, has slow-loading pages, and blocks its help content in robots.txt, making it invisible to AI systems.

Creating AI-friendly content is only half the equation. AI systems also evaluate your credibility through external signals.

Pillar 4: Establishment of authority via strategic community presence and external validation

Build the authority signals AI systems use to prioritize sources.

AI systems don’t just look at your website. They evaluate your credibility by checking what others say about you. Your brand needs to be recognized as a trusted expert across multiple platforms where AI systems source information.

Step 1: Establish expertise where AI systems look

AI systems frequently reference community discussions and expert commentary from platforms like Reddit, LinkedIn, and Stack Overflow and industry publications.

Good example

A gaming brand maintains an active presence on Reddit’s r/gaming, providing verified answers to lore questions that get upvoted and become highly visible to AI systems.

Bad example

A gaming brand only posts promotional content on owned channels, ignoring community discussions where authentic expertise is valued.

Platform-specific community strategy

Key principle: Provide genuine value, not promotional content. AI systems (and communities) recognize and reward authentic expertise.

⚠️ Platform self-promotion caution 

Most platforms have strict community expectations around self-promotion that brands often underestimate. For example:

• Reddit: Communities are extremely sensitive to promotional content. Focus on contributing genuine value through individual accounts rather than obvious brand promotion. Always check individual subreddit rules before posting.
• Stack Overflow: It highly values technical expertise over product promotion. Only mention your product when it’s genuinely relevant to solving someone’s problem, and always disclose your affiliation.

General rule: Be transparent about brand affiliations, focus on helping rather than selling, and build individual expertise before any brand mentions.

It’s quality over quantity: This isn’t a call to spam the internet with more content. Quite the opposite. It’s an urgent call to tap into authenticity, creating content that’s genuinely useful, timely, and shareable. What does authentic content look like? AI systems prioritize content with clear author credentials, original data and research, transparent source citations, and genuine problem-solving value. Skip the keyword-stuffed fluff. AI systems can detect thin content that rehashes existing information without adding new insights.

This authenticity principle is particularly relevant to community engagement. Getting banned from these communities eliminates your AI citation opportunities. When in doubt, contribute value without mentioning your brand at all. Your expertise will still get attributed to you over time. AI systems increasingly reward depth over volume. A single well-researched industry study will earn more citations than dozens of rehashed “AI trends” listicles.

Step 2: Build consistent brand recognition through internal housekeeping

Make your brand easy to identify:

• Use your exact company name consistently across all platforms.
• Add context when needed: “Branch (the mobile linking platform)” rather than just “Branch.”
• Ensure you clearly identify key team members with your company.
• Maintain consistent messaging about what you do and how you help customers

Advanced brand recognition (B2B and product companies):

• Include structured data for organization, person, and product entities on your website.
• Link to authoritative external sources when mentioning other companies or concepts.
• Maintain consistent team member information across LinkedIn, your company website, speaker bios, and industry profiles.

Note: Advanced brand recognition tactics are particularly important for B2B and technical companies where expertise and product complexity matter. Consumer-focused businesses may prioritize customer reviews and social proof instead.

Step 3: Earn external validation

Build citation-worthy authority:

• Industry coverage: Secure mentions in trade publications and industry reports.
• Expert commentary: Provide quotes and insights for news articles and analyst research.
• Original research: Publish data studies that others want to reference and cite.
• Speaking opportunities: Present at conferences and participate in industry panels.
• Customer success stories: Collaborate on case studies with recognizable brands.

Authority-building actions:

• Contribute to industry surveys and benchmark studies.
• Participate in podcast interviews and expert roundtables.
• Write guest posts for respected industry publications.
• Provide product reviews and comparisons for trusted review sites.

Why this matters for AI citations

AI systems use external validation to determine source credibility. When multiple trusted sources reference your expertise, AI systems are more likely to:

• Cite your brand as an authoritative source
• Include your insights in synthesized responses
• Rank your content higher in retrieval systems
• Reference your team members as recognized experts

The multiplier effect

Strong community presence and external validation don’t just help with AI citations; they also improve traditional SEO, increase brand awareness, and generate quality leads through authentic relationship building.

Having said that, strong authority and great content mean nothing if you can’t convert AI-driven traffic into business outcomes.

Pillar 5: Mobile growth optimization

Convert AI discovery into mobile app engagement and growth.

The opportunity 

AI platforms are driving increasing traffic to your digital properties. It’s time to treat this channel as both an acquisition and engagement opportunity for mobile growth.

The problem most brands face

The broken flow:

1. ChatGPT cites your brand → user clicks → lands on website → has to find and download your app.
2. High-intent users, who cared enough to click in a low-click environment, get a friction-filled experience that wastes qualified traffic.

The optimized growth flow:

1. ChatGPT cites your brand → user clicks → either opens directly in your app (universal linking) OR sees a contextual install prompt based on their behaviour.
2. Smart targeting: Show install prompts based on traffic source (AI platforms) or user behavior insights
3. Complete conversion: Use AIO as an integrated growth channel, not just web traffic

Beyond the click: Data and retargeting opportunities

CRM integration:

• Export AI discovery data to your CRM systems for better targeting.
• If someone discovers a new feature via ChatGPT, convert that into an upsell via push notifications or email campaigns.

Implementation strategy

Technical setup:

• Universal link configuration: Ensure all AIO-optimized URLs route existing users directly to relevant app screens.
• Contextual install prompts using Branch web-to-app banners: Target users landing from AI platforms with specific install messaging like “Open in [app] to solve [specific problem].”

Advanced attribution:

• Full-funnel tracking: Measure from AI citation → web landing → app install → engagement.
• Platform performance: Identify which AI platforms drive the highest-value users.
• Content performance: Track which cited content generates the most valuable mobile growth.

The result: Transform AI discovery from random web traffic into a systematic mobile growth engine with full attribution and optimization capabilities.

Looking ahead: What’s next for AIO

Current priorities (next 12 months): 

Focus on traditional SEO foundations, schema markup implementation, and basic AI visibility monitoring. These fundamentals will remain critical as AI systems continue to rely on established trust signals.

Emerging considerations (12-24 months):

• Multimodal content: Image and video optimization will become table stakes as AI systems increasingly process visual content.
• Real-time freshness: Content update frequencies will become more critical for competitive citation rates.
• Automated monitoring: Manual citation tracking won’t scale; prepare for AI-powered competitive intelligence tools.

Future-proofing preparation:

• AI platform evolution: New AI search interfaces and citation methods will emerge; maintain flexible content architecture.
  Voice search integration: Conversational AI interactions will require content optimized for spoken queries.
• Real-time data integration: Consider APIs and structured feeds for dynamic, always-current content.
• Personalization engines: AI systems will increasingly customize responses by user context and history.

Risk areas: 

Platform-specific optimization strategies may shift as the AI landscape evolves. Focus on foundational best practices that transcend individual platforms while staying informed about emerging trends.

What next? Building a culture of AI-first discovery

The five pillars of this AIO growth framework are designed as an integrated system, not a one-time checklist. True success in AI-first discovery comes from continuous adaptation and strategic prioritization.

To begin, focus on strengthening the foundations that matter most right now. Ensure your technical SEO is sound, make your top content AI-native, set up initial traffic tracking, and begin building authentic authority within relevant communities.

As you build on these essentials, look ahead to emerging practices. Consider how multimodal content, real-time freshness, and voice search optimization will shape future discoverability.

The key is to focus on foundational best practices that work across all AI platforms rather than chasing platform-specific tricks that may change. AI-first discovery isn’t just a strategy; it’s a commitment to ongoing relevance in a constantly evolving landscape.

Want help with your AIO strategy? Branch is here to help!

This framework represents current best practices based on real-world testing with brands. As AI systems evolve, I expect these recommendations will need refinements based on customer results and platform changes.