AI is now embedded in how customers research, evaluate and compare brands, and CMOs are already restructuring teams, workflows and measurement models around that reality. Marketers are feeling the impact most acutely in content marketing and SEO. If there’s one thing just about everyone agrees on, it’s this:

Original, high-quality content is essential.

Great content has always been important, and some of us have been banging the drum for quality over quantity since the dawn of content marketing as a discipline. Even so, it’s still nice to be vindicated at last. Now, in the AI era, quality is no longer just a differentiator. It is the minimum requirement for visibility.

But even publishing great content isn’t enough. The internet is littered with brilliant content no one ever sees (an eternal frustration of marketers everywhere who are desperate to prove ROI).

Instead, a successful content marketing strategy stands on three pillars:

  • Quality content: Original, valuable assets targeted to the needs of your audience
  • Distribution: Getting your content to existing audiences via owned channels (email, social media, etc.)
  • Amplification: Helping unknown prospects discover your content (search, paid advertising, etc.)

These pillars are even more critical in the age of AI, as consumers increasingly use GenAI platforms like ChatGPT and Perplexity to research brands and products.

While traditional content marketing focused on publishing and distribution, in the AI era, amplification plays a new role: ensuring content remains visible in AI-generated discovery environments where traffic and attribution are increasingly fragmented.

AI adoption is  happening, but  it’s  uneven

Let’s look at AI adoption for a moment. Despite the noise, AI adoption is not yet universal. The UK Government’s 2026 AI Adoption Research found that only 16% of UK businesses are currently using AI, with a further 5% planning adoption. Nearly 80% are not yet actively using AI in operations.

Among adopters, the majority use AI for text generation and natural language processing, while only a small fraction use more advanced or agentic systems. Crucially, 84% of AI-using businesses still apply human oversight to outputs.

Globally, adoption is rising but remains far from saturated. The Microsoft AI Diffusion Report 2025 H2 estimates that around 16% of people worldwide use generative AI tools, with adoption growing steadily but unevenly across regions.

The implication for CMOs is clear: AI is influencing buyer behaviour, but organisational maturity remains mixed. Governance, amplification, and strategic integration are inconsistent. That creates both risk and opportunity.

AI search is reshaping discovery

Consumers increasingly use generative AI tools such as ChatGPT and Perplexity to research brands and products. Meanwhile, Google’s AI Overviews and generative search features are reshaping how information is surfaced.

Research from Bain & Company suggests that roughly 60% of searches now end without a click to a website. Zero-click search and AI-generated answers mean more buyers are gathering information without ever landing on your site.  Traditional attribution models struggle to account for this shift.

But this does not mean your content is losing value. If an AI Overview or ChatGPT response references your content, you have still influenced perception. You may have shaped preference. You may have accelerated the sales cycle. You may have reduced future customer acquisition costs by building early trust. You just cannot measure that influence using legacy traffic metrics alone.

For CMOs, the challenge is not only adapting distribution and amplification strategies to AI search. It is evolving measurement models to reflect how influence now works.

Here’s how to do it:

Phase 1: Benchmark your AI visibility

Before you reinvent your strategy and start optimising your content, you need to examine and benchmark your brand’s current visibility in AI search.

Gather intelligence

  • Review your last 100 leads to see which (and how many) content pieces they touched before converting.
  • Ask your sales and support teams to identify common questions from prospects and customers on calls.
  • Interview typical customers to find out what questions, concerns, and objections they usually encounter at each stage of the buying journey.

Audit  your AI brand mentions

  • Test your AI visibility by tracking how often your brand appears in AI-generated responses related to these customer queries, plus other industry or key topics.
  • Track your competitors’ AI mentions and compare the results.
  • Identify content gaps where your brand’s content and expertise should be represented but isn’t.

TIP: 

It’s not currently possible to capture data on genuine user queries, conversations and clicks in GenAI platforms like ChatGPT. However, monitoring tools like Peec AI and Otterly.ai run test queries to simulate your brand’s likely visibility in the various AI platforms.

Phase 2: Optimise your content

Your content needs to work for humans and machines simultaneously. Work with your SEO and content teams on the following:

Improve your content structure

  • Add schema markup to key pages. While invisible to LLMs, schema can still have an indirect influence via search and other third-party resources LLMs draw upon.
  • Structure the information and ideas within long form content as self-contained “chunks” that also work as standalone answers or snippets, ready for AI to extract.
  • Implement FAQ sections or adopt a Q&A format where possible, making it easier for AI systems to extract clear answers to specific user queries. Focus on structuring your Q&As as follow-up questions to emulate the way people interact with AI systems.
  • Ensure fast loading times and clean HTML structure for efficient AI crawling.
  • Organise your headings logically (H1, H2, H3) so that AI can correctly follow the hierarchy of information.

Amplify your authority signals

  • Develop consistent brand messaging across all your content.
  • Publish original proprietary research containing relevant insights AI systems can’t get from any other source—so they have to reference your content.
  • Build authority around topic clusters rather than targeting individual keywords.
  • Differentiate your content by including expert quotes and original insights exclusive to your brand.
  • Strengthen your content’s credibility with rigorous fact-checking to maintain a high level of factual accuracy backed by trusted authoritative sources.
  • Zero in on what your target audience cares about and what’s going to make them convert once they arrive on your page.

TIP: 

Look for ways to diversify your content. Experiment with different formats (video, audio, interactive) to see how each impacts AI discovery differently. You can also publish favourable product comparisons or create conversational content designed to mirror the kinds of questions and phrases people are likely to use in AI prompts

Phase 3: Measure what matters in the AI era

Traditional metrics tell an incomplete story. The usual attribution models can’t track zero-click interactions in AI-generated answers and AI Overviews. However, you should still capture information on those website visitors who do click through.

Set up your tracking tools

  • Separate LLM referral traffic from general referral traffic in Google Analytics.
  • Implement Urchin Tracking Module (UTM) codes across all your content channels to identify the source of each click. (NB: While ChatGPT supports UTM tracking, not all AI platforms currently do.)
  • Monitor LLM bot crawling of your website using SALT’s new Cloudflare methodology.

Update your KPI dashboard

  • Track mentions in AI-generated responses to monitor how often your brand appears in answers relative to your competitors.
  • Expand share of voice metrics to include your presence in Google AI Overviews etc. for industry-relevant searches.
  • Assess the quality of AI-driven traffic by focusing on engagement metrics such as time-on-site and scroll depth, rather than volume.
  • Compare performance across AI models, such as ChatGPT, Claude, Perplexity, Copilot, and Google AI Overviews.

The way ahead

Content marketing in the AI age isn’t about abandoning everything that came before. It’s about adapting and extending your approach to incorporate AI search.

Distribution and amplification haven’t become less important; they’ve become more sophisticated.

The most effective content strategy would be to invest in long-term, evergreen assets packed with value and topical depth. When properly optimised for AI discovery, high quality and strategic content will only grow in value.

Ready to understand how AI systems are consuming your content?

If you’re ready to go beyond legacy metrics and finally understand when, where, and how AI systems consume your content, SALT.agency can help.

Our Cloudflare-powered AI visibility solution shows you exactly when generative AI bots access your site, how often your content is referenced in AI responses, and where your brand appears or gets omitted in AI-generated discovery. That insight feeds smarter amplification strategies, tighter governance, and measurable impact on pipeline and CAC. 

If you want to see exactly when AI consumes your content, and turn that visibility into growth,  get in touch.