- Lane Scott Jones
- Sep 15
- 7 min read
Updated: Sep 28
Two years ago, I thought I had content strategy figured out. I'd spent years building SEO playbooks, running high-performing content programs and watching our work steadily climb search rankings. I'd helped Zapier build a content team with 450% ROI, led by SEO traffic to our blog.
AI taketh away. The credit, the click, the relationship with the reader, all of that is bypassed in AI search engines and chatbots.
I've spent the last 12+ months knee-deep in that shift, reworking our content strategy, testing new content formats and having a lot of hard conversations about what we stop doing. Here's what I've learned about not just surviving, but winning, in the era of AI-powered search and generative engines.
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TL;DR: AI content strategy
AI is changing how content is discovered and consumed. Here’s how to keep your content seen and trusted by readers and AI:
Accept AI engines influence search and citations
Focus on irreplaceable content that AI can’t replicate
Map high-value use cases to keyword gaps
Experiment with LLM-friendly content alongside human-facing pages
Build a distribution engine and make strategic trade-offs
Focus | Quick tip |
Irreplaceable content | Share proprietary insights, templates or unique POV |
Use cases | Show real-world examples and success stories |
LLM content | Add structured data, process maps or code snippets |
Distribution | Syndicate content, engage communities, collaborate with experts |
"With AI-generated content taking the internet by storm, readers and search engines alike crave genuine narratives and unique firsthand experiences. Sharing personal experiences and insights not only humanizes your content, but also adds a unique value that cannot be found elsewhere. As a result, your site becomes a one-of-a-kind source of knowledge amidst an ocean of reshared, curated content, allowing you to build trust and authentic connections with your readers while strengthening your expertise." - Judit Ruiz Ricart, blog strategy expert at Wix
Learn more:
How to build an AI content strategy for AI-powered search
AI is changing the game for content. Readers aren’t just searching, they’re asking AI tools, chatbots and generative engines, which can surface answers without ever visiting your site. That means your content needs to do more than rank, it needs to be irreplaceable, cite-worthy and structured for both humans and AI.
Here’s how I’ve approached building an AI content strategy that keeps your content visible, valuable and ready for whatever the next wave of AI brings.
01. Accept that the content playing field has changed
Google didn't die when TikTok search blew up, and it's unlikely to die now. But now that people can get what they need from generative AI tools, things will change. Ranking on page one still matters (both for SEO and GEO), but it's no longer the only, or even primary, measure of visibility.
As marketers, we need to ensure AI engines are citing us, talking about us and pulling from our content when they generate answers.
It's a hard pill to swallow, especially since AI engines aren't always citing us or even acknowledging the existence of our content. But accepting this shift, and proactively signaling your expertise and trustworthiness, is the first step toward staying visible in an AI-driven search landscape.
02. Shift from "findable" to "irreplaceable" content
Traditional SEO rewarded content that matched queries and was optimized for keywords, backlinks and structure. That all still matters for GEO, but we need to go from high information gain to content optimization that's literally irreplaceable, something AI chatbots can't reproduce. This is where demonstrating experience, expertise, authority and trustworthiness (EEAT) become critical.
In practice, that means:
Surfacing proprietary data: Share internal usage patterns, industry benchmarks or anonymized customer insights and gate them so AI can't grab it.
Anchoring content in your brand's unique point of view: Emphasize the human behind the content can go a long way here.
Offering templates: Provide detailed workflows, examples, scenarios or website templates that can't be scraped from public sources.
Sure, AI will be able to find your content. But it'll be much more likely to give you that link, and qualified leads are much more likely to click through.
03. Treat use cases as a core asset
One of the most effective GEO strategies we're using is mapping our highest-value use cases directly to keyword and question gaps. This ensures that when someone asks an AI tool, "How do I…?" in a domain where we're experts, our brand has a reason to be cited.
For example, in my case, that might mean showcasing how folks are using Zapier to solve specific problems across departments. Especially if you can get folks to share that content, you can teach the AI that the answer to "How do I…?" aligns with whatever you're selling.
Pro tip: Encourage user-generated content and customer stories—they’re a goldmine for fresh content ideas and give AI engines more authentic signals to cite when surfacing your brand.
04. Experiment with content designed specifically for LLMs
We've started piloting machine-readable content layers—pages designed to be easily parsed by large language models (LLMs), even if they aren't flashy to human readers. Think structured datasets, highly formatted process maps and embedded code snippets.
This approach doesn't replace human-friendly content, it complements it. While the human-facing page builds trust and engagement, the machine-readable layer makes sure AI sees the full depth of your expertise and authority.
05. Build a distribution engine
You can talk about your own products or services all you want, but AI wants to know that other people are talking about it too. That means focusing on off-site marketing as much, if not more, than on-site marketing.
Some things we've been exploring at Zapier:
Content syndication: Repurposing high-value content to run on partner platforms and communities.
Community engagement: Participating early in relevant discussions on platforms like Reddit and LinkedIn, ensuring our expertise is part of the source material AI tools reference.
Influencer collaboration: Partnering with domain experts whose content is likely to feed into generative answers.
The goal is to get your content, and your business, into the conversations (and datasets) that AI is training on.
Learn more:
06. Make strategic trade-offs
The hardest part of spearheading our GEO strategy wasn't deciding what to add—it was deciding what to cut. Every hour your team optimizes content that AI will never cite is an hour we're not investing in assets that could define our visibility for years.
For us, this has meant pausing or sunsetting lower-impact content formats, redirecting resources to things like proprietary research, use case development and offsite marketing, and generally being ruthless about aligning content work with the realities of AI.
It's all about focus.
07. Build for resilience, not just reach
Just as SEO evolved over the years, and continues to evolve, GEO will too. We're still in the early days, and the landscape is shifting constantly. Just when we thought we understood Google's plans with AI Overviews, AI Mode was launched, and before we could fully adjust, Web Guide followed.
That's why we've built regular checkpoints into our process at Zapier: tracking which topics and pages are showing up in AI results, testing new content formats and channels and sharing cross-team insights in real time.
And that's really what it comes down to: expect change, embrace it and adapt.
Your AI content strategy roadmap
Here’s a quick overview of the 7 key steps to building an effective AI content strategy, highlighting the actions to take and the results you can expect.
Strategy | Key actions | Takeaways |
Accept the changing content landscape | Recognize how AI-powered search changes visibility; focus on being cited by AI tools | Signal authority and expertise to AI; visibility is no longer only about ranking |
Shift from “findable” to irreplaceable content | Share proprietary data, anchor content in your unique POV, provide templates/workflows | Demonstrate expertise and trustworthiness; create content AI can’t replicate |
Treat use cases as a core asset | Map high-volume use cases to keywords/question gaps; showcase real-world applications | Positions brand as authoritative; teaches AI the correct context for answers |
Experiment with LLM-friendly content | Pilot machine-readable layers (structured datasets, process maps, code snippets) alongside human-facing pages | Signals expertise to AI; complements human-facing content; reinforces authority |
Build a distribution engine | Syndicate content, engage communities, collaborate with influencers | Expand reach and credibility; off-site references increase trust signals for AI |
Make strategic trade-offs | Pause low-impact content; redirect resources to high-value content and research | Focused investment in assets that build long-term authority and visibility |
Build for resilience, not just reach | Track AI results, test new formats, share cross-team insights | Demonstrate expertise and adaptability; ensure content remains credible and authoritative as AI evolves |
Meet the expert
Lane Scott Jones built and scaled content programs at B2B SaaS companies including Zapier, Campaign Monitor and Emma. She’s grown teams from zero to 20+, driven 450% ROI and 4.5M+ monthly visitors and managed $2M+ in annual spend all while positioning content as a core driver of business growth. Her work has been featured in Forbes, CMO and MarTech Advisor and she’s spoken at events hosted by Exit Five, Superpath, Digital Summit and Tech Ladies.
AI content strategy FAQ
What is AI content strategy?
AI content strategy is the approach of using artificial intelligence to plan, create and distribute content that aligns with both user intent and AI-driven search results. It goes beyond traditional SEO by considering how generative engines pull answers. Think of it like building a marketing plan that connects your business expertise to the questions people are asking in real time.
Does SEO penalize AI content?
No. Google and other search engines don’t automatically penalize AI-generated content. What matters is whether the content is original, accurate and helpful. Adding layers like expert review, content analytics and real-world examples helps prove experience and trustworthiness. AI can support the process, but human oversight makes the difference.
How to use AI for content ideas?
AI tools can help you uncover trending questions, keyword gaps and new formats that resonate with your audience. For example, you might use AI to generate marketing ideas or brainstorm “how-to” topics. Pair this with customer input or user-generated content to build assets that AI is more likely to cite.
Which AI tool is best for content?
There isn’t a single best tool, it depends on your goals. Some are better for drafting, others for research and some for scaling distribution. When evaluating options, look for SEO features like keyword optimization and organic marketing insights or integrations with channels like LinkedIn marketing and advertising. Also, consider whether they play nicely with your existing systems (like what is a content calendar or CMS platforms).
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