As consumers increasingly shift from traditional search results to AI assistants that deliver direct, conversational answers, brands must rethink how they create and position content. Earning visibility now depends on clarity, authority and usefulness, not just keywords or rankings. Organizations that adapt quickly will be the ones AI tools surface as definitive, trusted sources.
Below, Forbes Communications Council members share the key approaches they’re using to ensure their brands become the answer users are looking for—not just another link.
“We’re shifting from producing content to producing verifiable identity signals. As AI assistants pull answers from structured context, we model our expertise so it’s machine-readable, using graph-based relationships, provenance and clear authorship. The goal isn’t just to rank; it’s to become the trusted identity an AI can confidently reason over.” – Hope Frank, Gathid
1. Creating Educational Content That AI Deems Worth Citing
Double down on content that actually teaches something, making blogs more intentional, educational and genuinely useful. AI pulls from high-quality sources, so that means being clear about the message behind every piece. Content built to inform, not just mimic, performs better with humans and AI models, making it something worth citing rather than just another link to scroll past. – Brana Webb, Grasshopper Bank
2. Building Structured FAQs To Provide Clean, Trustworthy Answers
We’re building structured FAQs so AI assistants can pull clean, trustworthy answers. As privacy protections grow, our own AI tools give us rich first-party insight into the real questions people ask. We use that data to refine content, helping external AI assistants surface our brand first. – Annie Austin, Oregon’s Mt. Hood Territory
3. Leveraging Proprietary Data To Become A Primary Source Of Truth
One way I’m adapting content strategy is by leaning into proprietary data creation that AI wants to surface. AI favors sources that offer original insights, not recycled information. By investing in proprietary datasets such as industry trends, benchmarking, customer insights and product performance, I position brands as a primary source of truth so content is cited, not just indexed. – Krystle Craycraft, NyTex Partners
4. Expanding Multichannel Visibility To Help AI Surface Brand Information
Appealing to AI engines means more content in more places. Optimizing your website is no longer enough. A multichannel strategy should include your website, with a robust FAQ page. It should also incorporate Google Business Profile, local business listings and social media. In addition, since AI can effectively read visual media, photos and videos should be increased wherever it makes sense. – Esther Bonardi, Yardi Systems
5. Balancing Content Volume And Authority Across AI-Sourced Channels
Success comes from being found in multiple channels with content that is relevant, authoritative and structured in a way that attracts AI to source your thought leadership. There is value in volume, but that cannot usurp quality. The specific channels are important to consider. For example, YouTube is one of the top sources for AI, so focus on the most sourced channels for content first. – Clay Tuten, KeyMark Inc.
6. Prioritizing Actionable Insights And Net-New Knowledge To Clarify Brand Expertise
Developing actionable insights about brand expertise and permission, prioritizing net-new knowledge and generating clear, information-based answers to questions are the top approaches we are using and sharing with clients. Brands can test high-value keywords and category questions inside major LLMs to illuminate how brand expertise is being interpreted and where their opportunity lies. – Caroline Kennedy, Material
7. Answering Real Customer Questions With Clear, Expert Guidance
We build content around the real questions customers ask, using clear keywords and practical solutions. By providing direct, expert guidance tied to real workflows and outcomes, we position ourselves as the trusted source AI tools surface. – Shirin Ali, CMiC
8. Optimizing Owned And Earned Channels For AI-Driven Discovery
Develop content for your owned channels as your target audience would search for it. Also, recognize that AI is pulling information from more than your owned channels, so third-party validation is key. Be strategic in your public relations engagements, as AI is using news outlets to develop direct answers. – Kimberly Osborne, Old Dominion University
9. Structuring Data For AI Readability Through Vector-Friendly Formats
It’s important to understand that AI systems categorize data using vector databases, as opposed to the keyword methodology of search engines to process, score and leverage data. Markdown or JSON formats give your data a more consumable structure so AI can surface your work more often and more accurately. Add these files to your site’s resource section or somewhere not publicly visible. – Shaun Walsh, Peak Nano
10. Strengthening Text-Based Authority Across Trusted AI Content Sources
Make sure you have strong content that the LLMs are pulling from—this means Reddit, Wikipedia, mentions in trusted sources and strong influencer content. For how important video has become in the world of social, the rise of AI search has made text equally important—so don’t forget about those captions and tags! – Keith Bendes, Linqia
11. Prioritizing Clear, Honest Messaging That AI Can Easily Trust
We prioritize clarity and honesty in our messaging. By offering straightforward, transparent insights, we make it easy for AI assistants to extract and synthesize information, ultimately recognizing our voice as a credible, primary source that leaders can rely on for answers. – Meredith McEuen, Chartwells Higher Education
12. Publishing Model-Ready Q&A Content With Structured Claims And Citations
Adapt by creating model-ready Q&A content for AI assistants. Through answer engine optimization, publish authoritative, single-topic pages with clear claims, citations and structured metadata so assistants can deliver complete answers. Each entry uses first-party data, case studies and update logs for freshness. Align queries to audience needs using analytics tools to ensure trust and measurable impact. – Anshuman Dutta, Cognizant
13. Crafting Crisp, Intent-Based Answers Built For AI Interpretation
I’m shifting content toward crisp, authoritative explanations that directly answer intent-based questions that are structured so AI can easily surface and cite them. By prioritizing clarity, credibility and first-party expertise over keyword volume, we position our brand as the definitive answer, not just another result. – Kurt Allen, Notre Dame de Namur University
14. Aligning Cross-Channel Messaging To Build Unified Brand Authority
We are working to tighten cross-functional alignment so every channel speaks with one clear, consistent voice. When our earned, owned, social and internal messaging reinforce the same story, we build true subject-matter authority, positioning our brand as the trusted answer AI surfaces. – Caroline Johns, Saatva
15. Providing Machine-Readable Identity Signals To Establish Trusted Expertise
We’re shifting from producing content to producing verifiable identity signals. As AI assistants pull answers from structured context, we model our expertise so it’s machine-readable, using graph-based relationships, provenance and clear authorship. The goal isn’t just to rank; it’s to become the trusted identity an AI can confidently reason over. – Hope Frank, Gathid | Gathered Identities
16. Enhancing Content Quality To Influence Buyers Before They Reach The Website
The need for quality and relevant content for a buyer has never been more important. Research has shown the buyer’s journey now starts before someone has even visited a website. Having a strong content strategy helps drive SEO and GEO initiatives to ensure you get noticed and presented by these AI engines. – Joe Ariganello, Veracode
17. Treating Content As Reputation Capital To Build Consistent AI Trust
Content is treated as reputation capital rather than just a traffic play. The content strategy is shaped by deciding in advance where the brand will speak, acknowledge or stay silent—and by holding that judgment consistently over time. Treating answers as reputation assets builds sustaining trust that AI can rely on through discipline and consistency. – Toby Wong, Toby Wong Consulting
18. Developing Topic Clusters That Strengthen AI Understanding And Credibility
We’re shifting from publishing standalone articles to building topic clusters that AI can easily understand and trust. Each cluster answers core and related questions in clean, structured formats while we strengthen off-site authority through expert mentions and citations. This helps AI choose our brand as the reliable answer. – Lauren Parr, RepuGen
19. Using Consistent Messaging And Topic Clusters To Reinforce Expertise
Consistent messaging across our repurposed content is essential. To establish and maintain our position as experts in key focus areas, we must deliver unified messaging, terminology and demonstrated expertise through our digital content using topic clustering. This approach strengthens our visibility across both traditional search and generative AI platforms, reinforcing our brand as an expert. – Victoria Zelefsky, Anne Arundel Economic Development Corporation
20. Anchoring Answers In Real-World Proof To Build AI-Recognized Credibility
Frame content as direct answers anchored in real-world proof: real people, named outcomes and offline moments. AI can surface facts, but it cannot match lived results. Stay close to people, the market, places and tangible impact in every story. – Marie O’Riordan
