Artificial intelligence isn’t just tweaking search results. It’s having a significant impact on the rules of visibility. With AI-generated answers in Google’s AI Overviews / AI Mode, ChatGPT, and other emerging platforms, the way people find, evaluate, and choose brands is shifting fast.

For marketers, this is both a challenge and a huge opportunity. The brands that adapt early will be the ones that keep showing up in buying journeys.

Here are five strategies to help your brand respond.

1. Understand the New Visibility Game

AI is fundamentally changing how people discover brands. In traditional search, you could win with a mix of page-one rankings, ads, and content spread across the web. In AI-driven search, visibility has become binary – you’re either in the answer or invisible.

This is a behavioural shift as much as a technical one:

• People no longer scan through ten results. They take the AI’s shortlist as the starting (and often ending) point.
• The “research phase” is compressed. Fewer tabs, more trust in the first result (although this can be misplaced).
• Brand discovery now happens through curated, AI-chosen sources rather than wide-open SERPs.

(read part 1 and 2 of our series for more on these)

Why it matters: Your competition is no longer every site on Google. It’s the handful of entities AI deems relevant enough to mention. Success now depends on being one of those chosen few, and that means rethinking your brand’s approach to search presence, not just your keyword rankings.

2. Reverse-Engineer the AI’s Source List

Once you grasp the new visibility model, the next step is getting into the AI’s trusted dataset. Every AI answer is stitched together from a set of recognised, high-authority sources, and you can track down which ones matter for your industry.

Practical steps:

• Search your target queries in AI Overviews, ChatGPT (with browsing), Perplexity, and other AI tools. Note the domains that keep appearing.
• Classify these sources:
• Authoritative publishers (industry blogs, news sites)
• Review platforms (Clutch, G2, Trustpilot, Capterra)
• Comparison listicles (independent blogs, affiliate sites)
• Secure placement through:
• PR outreach to relevant publishers
• Paid or affiliate partnerships where allowed
• Profile optimisation on review/comparison sites
• Keep monitoring – AI data sources shift as models update.

Why it matters: Even if you dominate traditional SEO, if you’re absent from these ‘source nodes’, you won’t show up in AI’s answers. Reverse-engineering and infiltrating them is how you bridge the gap between your current visibility and AI-era visibility. Whilst this can be done manually, there are plenty of 3rd party tools out there that can help you take this first step, some of which we’ll come on to now.

3. Monitor and Measure Your AI Visibility

Knowing if and how you appear in AI-generated answers is the first step to improving your visibility. Just like SEO analytics transformed keyword strategy, a new wave of AI visibility tools is emerging to help brands track their presence in AI search.

Practical steps:

• Use tools like Trakkr or AthenaHQ to:
• Track where your brand appears in AI-generated answers
• Benchmark against competitors
• Identify which data sources AI pulls from
• Analyse sentiment in AI outputs
• Create a visibility dashboard to monitor inclusion over time.
• Cross-reference AI visibility data with traffic and conversion metrics to see real impact.
• For Shopify merchants only – Shopify’s knowledge base app can help you fulfil a lot of these ambitions.

Why it matters:
AI visibility is not guaranteed, even if your traditional SEO is strong. Without measurement, you won’t know when (or why) you drop out of an AI’s dataset. Tracking presence and sentiment gives you an early-warning system and a blueprint for getting back into the AI’s trusted circle.

4. Prepare for AI-Native Shopping

Ecommerce is on the brink of possibly its biggest shift yet. With integrations like Shopify’s upcoming OpenAI plugin, shoppers will soon search conversationally (‘show me eco-friendly trainers under £100’), and get curated product lists pulled directly from live feeds.

Practical steps:

• Optimise your product feed like it’s a ranking asset:
• Use clear, relevant titles and descriptions
• Add detailed attributes (materials, style, price range, sustainability tags)
• Ensure consistent, clean data formatting
• Treat feed optimisation as an ongoing process, review regularly for gaps.
• Monitor emerging AI shopping plugins and integrations for your ecommerce platform.
• Test conversational search readiness by running AI queries for your category.

GPT users have already reported seeing results like the below, so this process is well underway:


Why it matters: In an AI-driven shopping interface, the quality of your product feed will determine whether you appear in results at all. This is like SEO for ecommerce feeds – relevance, clarity, and completeness will decide your visibility.

5. Build Content That’s AI-Friendly, Not Just Human-Friendly

AI doesn’t just look for keywords. It prioritises structured, clear, and authoritative content that answers questions directly. If your content isn’t easy for AI to interpret, it’s far less likely to be included in generated answers.

Practical steps:

• Structure content with clear Q&A formats to match conversational queries.
• Use bullet points, numbered lists, and definitions to make information scannable.
• Build topical authority by covering related questions and subtopics in depth.
• Implement proper schema markup to help AI parse your content accurately.
• Audit and fix broken links, outdated pages, or incomplete metadata.

Why it matters: AI wants to give confident, complete answers, and it pulls from sources that make that easy. The more structured and authoritative your content, the more likely it is to be surfaced, regardless of traditional keyword rankings.

Final Thoughts

The future of search isn’t about gaming the algorithm. It’s about being the answer the algorithm trusts.

That means:

• Inclusion > Ranking
• Authority > Volume
• Relevance > Broad reach

AI search is reshaping discovery into a high-stakes shortlist where only the most trusted, relevant, and well-structured sources make the cut. Brands that adapt their content, feeds, and visibility strategies now will be the ones the algorithms, and their customers, keep coming back to.