Search Results

Google’s AI technology is reshaping how search results appear and how users find information. For enterprise advertisers, understanding how to rank well in Google AI overviews is no longer optional. It’s a key part of staying visible and competitive in an increasingly AI-driven search landscape. If you want your brand to stand out, you need to adapt your strategies to work with AI-powered search features, not against them. This post offers practical tips and clear examples to help you improve your AI visibility and work effectively with an AI search agency or your internal team. You’ll also learn about generative engine optimization , a new approach that can boost your presence in AI-generated content. What is Google AI Overview? Understand How Google AI Overviews Rankings Work Google AI overviews are summaries generated by Google’s AI to provide quick, relevant answers to user queries. These overviews often appear at the top of search results, making them prime real estate for visibility. To rank here, you need to: Provide clear, concise answers to common questions in your niche. Structure your content with headings and bullet points for easy scanning. Use authoritative sources and data to back up your claims. For example, if you advertise cloud services, create content that answers specific questions like “What are the benefits of cloud computing for enterprises?” in a straightforward way. This increases your chances of being featured in AI overviews. Focus on Content Quality and Relevance Google’s AI is designed to favor content that is not only high quality but also highly relevant to the user's intent and needs. This alignment between the content and the user's search queries is crucial for achieving better visibility in search engine results. To improve your chances of ranking higher and gaining more organic traffic, it is essential to implement effective strategies that resonate with both the AI algorithms and the human audience: Firstly, write content that directly addresses user needs. This means conducting thorough research to understand what your target audience is searching for and what questions they are asking. Utilize tools like keyword research and analytics to identify common queries and pain points. By crafting content that provides clear, valuable answers to these questions, you can enhance user engagement and satisfaction, which in turn signals to Google that your content is relevant and useful. Secondly, avoid fluff or overly technical jargon that might confuse readers. It is important to communicate your ideas clearly and concisely. Use straightforward language that is accessible to a broad audience, and avoid unnecessary complexity that could alienate or frustrate users. This not only improves readability but also encourages users to spend more time on your page, which is a positive indicator to search engines about the quality of your content. Moreover, regularly updating your content is vital to keeping it current and accurate. The digital landscape is constantly evolving, and information can quickly become outdated. By revisiting and refreshing your content on a consistent basis, you ensure that it remains relevant to your audience's needs and reflects the latest developments in your field. This practice can significantly enhance your content's credibility and authority, making it more likely to be favored by Google’s AI. A compelling case study from a tech company illustrates the effectiveness of these strategies. The company focused on updating their FAQ pages, ensuring that the answers were clear, concise, and user-focused. As a result of these enhancements, they experienced a remarkable increase in their AI overview appearances by 30% within just three months. This significant boost not only improved their visibility in search results but also demonstrated the importance of aligning content with user intent and maintaining a commitment to quality and relevance. Use Structured Data to Help Google Understand Your Content Structured data, or schema markup, helps Google’s AI better understand your website content. This can improve your chances of appearing in AI overviews and rich results. Implement schema for FAQs, products, reviews, and articles. Use tools like Google’s Structured Data Testing Tool to verify your markup. Keep your structured data accurate and up to date. For instance, an e-commerce advertiser saw a 25% increase in AI-generated snippets after adding product schema to their pages. Optimize for Generative Engine Optimization Generative engine optimization (GEO) is a new frontier in SEO focused on optimizing content for AI-generated summaries and responses. Use natural language that AI can easily parse. Include clear, factual information that AI models can extract. Anticipate questions your audience might ask and answer them directly. Working with an AI search agency experienced in GEO can help you tailor your content to these emerging AI patterns, improving your overall AI visibility . Person reviewing AI-generated search snippets on a laptop screen Image caption: Analyzing AI-generated search snippets to improve content strategy. Build Authority Through Backlinks and Partnerships Google’s AI values content from trusted sources. Building backlinks from reputable sites signals authority and trustworthiness. Reach out to industry publications for guest posts. Collaborate with influencers or experts for interviews or quotes. Share case studies and original research that others want to reference. A B2B advertiser increased their AI overview rankings by securing backlinks from three major industry blogs, boosting their domain authority and trust signals. Monitor and Adapt Using AI Analytics Tools Tracking your performance in AI-driven search results requires specialized tools. Use AI analytics platforms that track AI overview appearances. Monitor changes in click-through rates from AI snippets. Adjust your content strategy based on data insights. Regular monitoring helps you stay ahead of algorithm changes and refine your approach to maintain strong AI visibility . Partner with an AI Search Agency for Expert Guidance Navigating the complexities of Google’s AI search features can be challenging. An AI search agency can provide: Expertise in generative engine optimization . Customized strategies based on your industry and goals. Ongoing support to keep your content aligned with AI updates. Choosing the right agency means finding one with proven results and a clear understanding of AI’s impact on search. Summary Ranking in Google AI overviews requires a focused approach that combines clear content, structured data, and strategic partnerships. By understanding how Google’s AI works and applying generative engine optimization techniques, you can improve your AI visibility and attract more qualified traffic. Use analytics to track your progress and consider working with an AI search agency to stay competitive in this evolving landscape. Frequently Asked Questions (FAQ) What are Google AI Overviews? Google AI Overviews are AI-generated summaries that appear at the top of search results, providing direct answers to user queries by synthesizing information from multiple sources. How is ranking in Google AI Overviews different from traditional SEO? Traditional SEO focuses on ranking web pages in search results. Ranking in AI Overviews means your content is selected, summarized, and cited within the AI-generated answer itself. What factors influence inclusion in Google AI Overviews? Key factors include: High-quality, authoritative content Clear structure and formatting Strong topical relevance to the query Trusted sources and domain authority Alignment with user intent What types of content perform best for AI Overviews? Content formats that work well include: FAQs and Q&A-style content Step-by-step guides List-based articles (e.g., “Top 10…”) Definitions and concise explanations Comparison and decision-making content How important is content structure for AI Overviews? Very important. Content with clear headings, bullet points, and concise sections is easier for AI systems to extract and summarize, increasing the chances of being featured. Do backlinks still matter for AI Overviews? Yes. Backlinks remain a strong signal of authority and trust, which influences whether your content is considered a reliable source for AI-generated summaries. How can brands optimize for both SEO and AI Overviews? By combining traditional SEO best practices with AI-focused strategies: Create structured, intent-driven content Build strong domain authority Use clear, concise language Focus on expertise and credibility How do you track performance in Google AI Overviews? Brands can monitor: Appearance in AI-generated summaries Changes in organic traffic and click-through rates Visibility for high-intent queries Share of voice in AI-driven search results What are common mistakes to avoid? Writing overly long or unstructured content Ignoring user intent behind queries Publishing low-quality or generic content Failing to establish authority and trust How can brands get started optimizing for AI Overviews? Start by identifying key questions your audience is asking, then create structured, high-quality content that directly answers those queries. Continuously refine based on how your content appears in AI-generated results.

Welcome to the new era of search. For years, the goal was simple: get your website to the top of Google’s blue links. Today, with AI assistants like ChatGPT, Perplexity, and Google’s own Gemini powered AI Overviews answering questions directly, the game has changed. The new prize isn’t just a ranking, it’s becoming a trusted source. This is where LLM citations come in. An LLM citation is a reference an AI model makes to a source when it generates an answer. Getting your brand cited means you are the authority the AI trusts. It’s the ultimate signal of relevance, and it’s what we at Busylike focus on with our Generative and Answer Engine Optimization (GEO/AEO) strategies . This guide will walk you through everything you need to know to start earning those valuable LLM citations . Google Ranking vs. AI Visibility: What’s Changed? Traditional Google ranking means appearing in the list of search results. AI visibility, however, means being featured directly within the AI generated answer. This is a critical distinction. A standard search results pa ge might show on average, 8.7 organic links on desktop and 8.5 on mobile, but an AI answer often cites far fewer sources, sometimes only three or so. Th is creates a winner take all environment where being the source is everything. Understanding Platform Specific Citation Behavior Not all AI platforms handle LLM citations the same way. This is called platform specific citation behavior, and it’s crucial to understand. Google AI Overviews (SGE) typically synthesizes information from a few top sources and lists them at the end of the generated answer. If this is a priority, see our How to Rank in Google AI Overviews guide . Bing Chat is very diligent, often adding numbered footnotes to individual sentences that link back to the source web pages. Perplexity AI was built around transparency, so it provides numerous hyperlinked source numbers with almost every statement. ChatGPT , in its default mode, does not cite sources at all, generating text from its vast training data. This makes it harder to track but underscores the need for your brand’s information to be part of its foundational knowledge. Why Per Model Tracking is Essential Because each model behaves differently, you can’t use a one size fits all approach. Per model tracking involves monitoring your brand’s presence and LLM citations separately across each major platform. For teams struggling with inconsistent ChatGPT visibility, see Why your brand doesn’t show up in ChatGPT and how to fix it . You might discover that Bing, with its live web search, frequently cites your latest blog posts, while ChatGPT, with its knowledge cutoff, has an outdated view of your company. This granular insight allows you to tailor your strategy. For example, a brand that is invisible on ChatGPT might need to focus on getting mentioned in sources like Wikipedia that are heavily weighted in training data. Crafting Content That Earns LLM Citations So, how do you create content that AI models want to cite? It comes down to a combination of structure, substance, and authority. Start with the Answer: Answer First Formatting Answer first formatting is a simple but powerful technique. It means structuring your content to provide a direct, concise answer in the opening sentence or paragraph, followed by supporting details. For templates and examples, see Structuring content for AI models to effectively cite your brand . Traditional articles often build up to the answer, but AI and featured snippet algorithms prefer content that gets straight to the point. This creates self contained answer blocks that are easy for an LLM to extract and use, increasing your chances of getting cited. Structure for Scannability: Listicle and Table Structures Organizing information into lists and tables makes it more digestible for both humans and machines. A search engine can easily pull a numbered list for a “how to” query or a table for a product comparison. Content formatted this way is significantly more likely to be chosen for a featured snippet. Think about it, if an AI needs to list the top five benefits of a product, a page with a clear bulleted list is a perfect source. The Foundation of Trust: E-E-A-T Signals E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. It’s a framework Google uses to evaluate content quality. An E-E-A-T signal is anything that demonstrates these qualities. This could be an author bio with credentials, original photos showing product use, or citations from other reputable websites. See Snowflake: Turning Thought Leadership into Scroll‑Stopping Stories for a concrete example of E‑E‑A‑T in practice. AI platforms are also learning to prioritize sources with strong E-E-A-T. One report notes that platforms like ChatGPT and Perplexity are more likely to cite sources that exhibit strong expertise and trust signals. Beyond Keywords: Optimizing for Entity Density Modern search engines think in terms of entities (people, places, concepts) and their relationships, not just keywords. To build this rigor, use our guide on Mastering the entity strategy to establish your brand as a trusted source for LLMs . Entity density is about how frequently and thoroughly your content covers the relevant entities connected to a topic. An article about electric cars should naturally mention entities like Tesla, lithium ion battery, and Elon Musk. Content with high entity density signals to an AI that you have a comprehensive understanding of the topic, making your page a more reliable source for an answer. Staying Relevant: The Importance of Freshness Signals For many queries, up to date information is critical. A freshness signal tells search engines that your content is recent and relevant. This can be the publication date, the frequency of updates, or even new inbound links. A Google algorithm update in 2011 made freshness a significant factor, impacting around 35% of all searches. For AI models connected to the web, like Bing Chat, fresh content is essential. If you have the most recent statistic or quote, you have a higher chance of earning the LLM citation. Become the Source: The Power of Original Research Publishing original research, like a survey or data analysis, is one of the most effective ways to build authority. It turns you into the source that everyone else cites. This strategy naturally attracts backlinks and media mentions, which are powerful E-E-A-T signals. According to one survey, 39% of marketers have published original research, with most finding that it met or exceeded their expectations for impact. Backing It Up: Handling Quantitative Claims with Care A quantitative claim is any statement involving numbers or data. These claims are powerful but require validation. Always cite your sources for statistics. An AI is more likely to trust and repeat a specific number if it can see where that number came from. AI systems tend to cite concrete facts and figures from trusted sources, as it makes their own answers appear more grounded and reliable. How AI Discovers and Validates Your Content Earning LLM citations isn’t just about what you write, it’s also about how easily AI systems can find, understand, and trust it. Watch the below video to start learning about this: Finding the Needle in the Haystack: Passage Level Retrieval and Chunking Modern search technology can pinpoint a specific passage or “chunk” within a long article that directly answers a query. This is called passage level retrieval. This means that even if your page covers a broad topic, a single, well written paragraph can be pulled out to answer a very specific question. To take advantage of this, use clear headings (H2s, H3s) to break your content into logical, focused sections. How One Question Becomes Many: Query Fan Out When an AI receives a complex question, it often breaks it down into multiple smaller queries behind the scenes. This process is called query fan out. For example, if you ask, “What are the best restaurants near the Eiffel Tower?”, the AI might internally search for “restaurants near Eiffel Tower”, “top rated restaurants Paris”, and “reviews for restaurants 7th arrondissement”. By creating focused content that answers these potential sub questions, you increase your chances of being included in the final synthesized answer. Speaking the Language of Search: Schema Markup Schema markup is a form of structured data you add to your website’s code to help search engines understand your content. It explicitly tells them what something is, for example, this is a product, this is its price, and here is its review rating. This clarity is invaluable for AI. While schema is not a direct ranking factor, it makes you eligible for rich results (like star ratings or FAQs in the search results), which can dramatically increase clicks. In fact, rich results now capture the CTR for rich results is 58.2% (vs 41% for non‑rich results) . Building Authority: Domain Authority and Backlinks Domain authority is a measure of your website’s overall credibility, driven primarily by your backlink profile. Backlinks are essentially votes of confidence from other websites. An analysis of 11.8 million Google results confirmed a clear trend: pages with more unique referring domains rank higher. This long term authority is a powerful signal to AI models that your content is trustworthy and worth citing. What Others Say Matters: Your Third Party Validation Profile Your third party validation profile is your reputation across the web. It includes customer reviews, press mentions, awards, and any other independent signals of credibility. A simple of your brand in a positive context, even without a link, contributes to your authority. Google’s own quality raters are instructed to research what others say about a site. A strong and positive external reputation is one of the most important factors for building the trust required to earn consistent LLM citations . For a deeper dive on why this matters, read How being cited by AI agents trumps digital visibility . Applying Your Strategy Across Your Site A successful GEO strategy isn’t applied uniformly. It must be adapted to the specific role of each page. A Plan for Every Page: Page Type Strategy A page type strategy means tailoring your approach for blog posts, product pages, category pages, and more. A blog post might be optimized for informational queries and featured snippets, aiming for around 1,500 words, as the average first page result is about 1,447 words long . In contrast, a product page should focus on conversion, integrating trust signals and product schema. Understanding the intent of each page type allows you to optimize it for its specific job. Optimizing Your Most Important Pages: Commercial Page Optimization Commercial pages, like product or service pages, have a dual goal: satisfy search engines and convert visitors. Pair these pages with The Rise of LLM Advertising: How Brands Win in the Age of AI Conversations to meet users inside AI answers. This requires a balance of rich, informative content and a seamless user experience. Technical details like page speed are critical. Google research has shown that 53% of mobile visitors will leave a site that takes longer than three seconds to load . These pages also need strong trust signals, like customer reviews and security badges, to build confidence with both users and algorithms. Protecting Your Brand in the Age of AI With AI generating answers for millions, a new risk has emerged: misinformation. What to Do About AI Lies: Hallucinated Citation Monitoring An AI “hallucination” is when a model makes up information. Sometimes this includes fake LLM citations that attribute false claims to your brand. Hallucinated citation monitoring is the process of tracking these instances. This can involve periodically prompting different AI models with questions about your brand and reviewing the answers for inaccuracies. In one infamous 2023 case, a lawyer used legal citations completely fabricated by ChatGPT, showing the real world consequences of these errors. Proactively monitoring for these issues is a new and essential part of brand reputation management. If you are serious about building a brand that thrives in the new age of AI search, you need a strategy that goes beyond old school SEO. You need a plan to earn trust and become the go to source for answers. The team at Busylike can help you build and execute a comprehensive GEO plan to secure your AI visibility. Frequently Asked Questions About LLM Citations What exactly is an LLM citation? An LLM citation is a reference or attribution a large language model gives to an external source when it generates an answer. This can be a direct link, a footnote, or a mention of the source’s name. How can I increase my chances of getting LLM citations? Focus on creating high quality, trustworthy content that demonstrates strong E-E-A-T signals. Use clear, structured formatting like lists and answer first paragraphs, and build your site’s overall authority through original research and a positive third party validation profile. Are all LLM citations clickable links? No. A citation can be a clickable link, like the footnotes in Bing Chat, or it can be a simple text of the brand or author within the AI’s response. Both contribute to AI visibility and brand authority. Why don’t I see LLM citations in ChatGPT? The default version of ChatGPT is designed to generate conversational text without explicitly citing sources from its training data. This platform specific behavior highlights why it is important to monitor different models, as platforms like Bing Chat and Perplexity provide very detailed LLM citations . Does traditional SEO still matter for getting LLM citations? Absolutely. Many of the principles of good SEO, like building domain authority, using schema markup, and creating helpful content, are foundational for being seen as a trustworthy source by AI models. Think of GEO as an evolution of SEO. What is the biggest mistake to avoid when seeking LLM citations? The biggest mistake is focusing only on keywords while ignoring trust and authority. Stuffing keywords into thin or generic content will not work. AI models prioritize content that is comprehensive, expert driven, and validated by other sources across the web.

Your team is probably seeing the same pattern we see across B2B SaaS, ecommerce, and growth-stage brands. Buyers aren’t always starting with Google, clicking through category pages, and comparing vendors on your site. They’re asking ChatGPT for recommendations, summaries, shortlists, and product explanations first. That changes what visibility means. If your brand isn’t cited, summarized correctly, or surfaced at the moment the model forms its answer, you can lose consideration before a prospect ever lands on your domain. Traditional SEO still matters, but how to rank in ChatGPT is a different operating model. The goal is no longer only to win clicks. The goal is to become a source the model can retrieve, trust, and quote. The brands that win here treat ChatGPT visibility like a media channel with its own content formats, authority requirements, and measurement model. They don’t publish generic blog posts and hope an LLM figures it out. They engineer citability, support it with technical signals, and tie the outcome to pipeline and revenue. Table of Contents From Search Clicks to AI Citations Map Conversational Intent and Define KPIs - Start with prompt audits, not keyword lists - Build KPIs that reflect actual AI visibility Create Prompt-Optimized and Citable Content - Write for extraction, not just for reading - Strengthen the page with visible proof of expertise - Formats that give LLMs clean material to cite Implement Technical and Authority Signals - Schema is a ranking input for AI retrieval - Authority has to exist beyond your own website Test and Iterate Your Presence in ChatGPT - Track prompts like a media portfolio - Respond fast when competitors displace you Measure ROI for Your GEO and AEO Programs - Why citation count alone is not a business metric - A practical GEO measurement model for CMOs Common Questions About Ranking in ChatGPT From Search Clicks to AI Citations The old search model rewarded ranking position and click-through. The new model rewards selection . When someone asks ChatGPT for the best payroll software for distributed teams, the most useful CRM for startups, or the right skincare routine for sensitive skin, the model doesn’t present a neutral list of ten blue links first. It assembles an answer. Your brand either makes it into that answer or it doesn’t. That’s why Generative Engine Optimization and Answer Engine Optimization now sit next to SEO, not underneath it. If you want a strong explainer on the discipline itself, this overview of what Generative Engine Optimization (GEO) is and how it works is a solid reference for framing the shift from search visibility to AI retrieval. The operational difference is simple. Search engines rank pages. LLMs often retrieve passages, compare sources, and then decide which brands deserve mention. That means your page architecture, your entity clarity, your external authority, and your answer formatting all influence whether the model uses you. AI visibility is partly about ranking, but mostly about being easy to trust and easy to quote. A lot of teams get stuck at this stage. They keep shipping content designed to be “good for SEO” in the old sense. Long intros. Soft claims. Buried answers. Thin author signals. No schema. No evidence that anyone outside the brand recognizes their expertise. That content can still exist on the site, but it rarely becomes the page an LLM wants to cite. A stronger model is to treat every important page as a candidate source. Category pages should answer category questions. Product pages should define use cases, trade-offs, and buyer fit. Educational pages should resolve specific prompts directly. If you want a practical view of what that looks like in execution, Busylike has a useful breakdown on LLM citations and how brands get cited in AI answers . The winning mindset is less “how do we publish more content?” and more “which assets should the model trust when a buyer asks an intent-rich question?” Map Conversational Intent and Define KPIs Keyword research still has value, but it’s no longer enough. Buyers don’t prompt ChatGPT the same way they search Google. They ask comparative questions, layered follow-ups, constraints, and context-heavy requests. Start with prompt audits, not keyword lists A strong GEO program starts with a recurring prompt audit. According to Ekamoira’s implementation guide for ranking in ChatGPT , teams should query ChatGPT with 20-30 core brand-related prompts weekly , map the top 5 competitors’ citations , and use that baseline to target more than 10% share of voice . That’s useful because it forces your team to stop guessing. Build a prompt set around the ways buyers ask for help: Category discovery prompts like “best [software category] for mid-market finance teams” Use-case prompts such as “tools for reducing support backlog with AI” Comparative prompts like “Brand A vs Brand B for remote onboarding” Problem-led prompts such as “how to reduce churn in subscription ecommerce” Trust-check prompts like “is [brand] good for enterprise security requirements” Don’t stop at head terms. Add the messy prompts that reveal buying context. Questions with constraints are often where weaker competitors disappear because they haven’t published for that nuance. Build KPIs that reflect actual AI visibility Most dashboards are still built for sessions, rankings, and assisted conversions. That leaves a blind spot. GEO needs its own scorecard. Start with a simple operating set: Metric Definition How to Use It Citation count The number of times your domain appears in tested ChatGPT outputs Track by prompt cluster and page type Share of voice Your citation frequency versus competitors in a defined query set Use it to spot category ownership and exposure gaps Citation sentiment Whether the model frames your brand positively, neutrally, or omits key strengths Review manually for brand positioning risk Page-level citation source Which specific URLs get cited Helps identify what content format actually wins Attributed referral traffic Visits from cited AI links using tagged URLs Connects visibility to measurable site behavior Practical rule: If you can’t tie prompt clusters to specific pages and outcomes, you don’t have a GEO program yet. You have observation. The biggest shift for CMOs is this. Prompt mapping is not just content planning. It’s demand mapping. It tells you where the market is asking questions, where competitors dominate the answer layer, and where your brand can earn commercial visibility before a click happens. Create Prompt-Optimized and Citable Content Pages don’t get cited because they’re long. They get cited because they’re extractable. Write for extraction, not just for reading One of the clearest patterns in AI retrieval is passage-level selection. A model often doesn’t need your whole article. It needs the strongest block inside it. According to Go Fish Digital’s analysis of ranking in SearchGPT , leading with a direct answer in the first 40-60 words and using Q&A or FAQ structures improves citability, and FAQ pages yield 28% higher inclusion rates in AI-generated answers. That should change how your team writes. Instead of opening with context, lead with the answer. Instead of saving the recommendation for the middle of the article, put it immediately below the heading. Instead of giant paragraphs, break the page into short, semantically clean sections. A citable page usually has these traits: Answer-first openings that resolve the prompt quickly Tight headings that match real user questions Short paragraphs that isolate a single idea Explicit comparisons that help the model distinguish options FAQs that mirror follow-up prompts Clear claims supported by evidence or observable expertise If your content team needs a better handle on the user side of prompting, this guide to mastering prompt engineering is useful context. Better prompts reveal the types of answers your pages need to satisfy. Strengthen the page with visible proof of expertise LLMs don’t only parse words. They infer credibility from what surrounds those words. That means author bios matter. Credentials matter. Firsthand experience matters. Product screenshots, implementation notes, original frameworks, and direct explanations from operators all help a page feel more source-worthy than generic reworded content. A common failure mode is publishing polished but anonymous material. It reads fine. It ranks nowhere in AI. The model has no strong reason to trust it over a branded domain, a known publication, or a page with explicit subject-matter signals. Use visible trust cues: Author identity with role and relevant expertise Primary-source references when making factual claims Specific examples from operations, implementation, or customer questions Clear revision habits so pages don’t look abandoned Internal links to supporting pages that deepen the topic For teams redesigning content around retrieval rather than classic blog flow, Busylike’s guide on structuring content for AI models to effectively cite your brand gives a practical page-level framework. A short walkthrough helps here: Formats that give LLMs clean material to cite Not every format performs equally well. FAQ pages often work because they align with how prompts are asked. Product comparison pages work because they force specificity. Glossaries can help when category terms are confusing or contested. Thought leadership can contribute too, but only if it contains original points and clean passages the model can lift from. The best citable content feels less like an essay and more like a well-structured answer system. What doesn’t work well: Slow, narrative intros that bury the useful part Keyword-stuffed copy built for old SEO templates Thin listicles with no unique expertise Overdesigned pages where important text is hard to parse Claims with no visible support If you’re serious about how to rank in ChatGPT, content strategy has to become retrieval strategy. Implement Technical and Authority Signals Even strong content gets ignored when the technical layer is weak or the authority layer is missing. LLMs need help understanding what your page is, who it’s about, and why it deserves trust. Schema is a ranking input for AI retrieval This is one of the most actionable technical advantages available right now. According to Try Analyze’s study on how to rank on ChatGPT , pages using structured data such as ItemList, Product, HowTo, or FAQ schema achieve a 49% Top-3 citation rate in ChatGPT responses versus 29% for pages without it, based on 65,000 prompt citations . That’s a 20 percentage point uplift , and schema-equipped pages were nearly 1.7 times more likely to rank in top positions. That matters because schema doesn’t just decorate the page. It clarifies entities, relationships, and content type in a way LLM retrieval systems can use. Prioritize schema on pages with commercial intent and answer density: Product pages for features, fit, and use cases FAQ pages for direct retrieval opportunities How-to pages for instructional prompts Author pages where Person schema can reinforce expertise Category pages that define the market clearly Also cover the basics. Keep HTML clean. Avoid hiding important copy inside awkward interactive elements. Make sure relevant bots aren’t blocked. Fast page delivery still helps because a page that’s difficult to fetch or parse is harder to use. Authority has to exist beyond your own website The retrieval layer favors brands that show up consistently across the web in trustworthy contexts. That includes publisher mentions, expert commentary, review environments, community discussions, and pages that establish the brand as a recognized entity. A practical off-site program includes: Earned mentions in reputable industry publications Forum presence where subject-matter experts answer real questions Review signals that reinforce legitimacy Consistent entity references across profiles and directories Thoughtful guest contributions on sites buyers already trust Entity strategy becomes operational, rather than abstract. Your brand, product, founder, and category terms need to connect clearly across the web. If they don’t, the model has less context for retrieval and less confidence in citation. For teams building that identity layer deliberately, Busylike’s article on mastering the entity strategy to establish your brand as a trusted source for LLMs is a useful companion to technical implementation. The trade-off is straightforward. On-site optimization is under your control and can move quickly. Authority building takes longer, but it compounds and protects your visibility over time. Test and Iterate Your Presence in ChatGPT A GEO program drifts if nobody monitors it. Prompt behavior changes. Competitors publish new assets. Authority signals strengthen or fade. The model’s answers shift as retrieval patterns evolve. Track prompts like a media portfolio Treat prompt clusters like campaign groups. Each cluster should have a clear owner, a set of target pages, and a recurring review cadence. According to Wellows’ citation analysis on ranking in ChatGPT , analysis of 65,000 citations found that branded domains maintain average ranks 11.1 points superior to competitors when they have strong authority signals, and tracking citation deltas daily across related prompts is important for measuring position changes and displacement events. That’s why weekly checks aren’t enough for high-value prompts. Build a testing sheet that captures: Prompt cluster Current cited domains Your cited page Framing of your brand Change from prior check Category prompt Competitor set URL if cited Positive, neutral, absent Gain, hold, loss Comparison prompt Competitor set URL if cited Accurate or incomplete Gain, hold, loss Problem prompt Competitor set URL if cited Useful or weak Gain, hold, loss This doesn’t need to be elaborate at first. The point is to create a record of movement. Respond fast when competitors displace you When you lose a citation, don’t jump straight to rewriting everything. Diagnose the likely cause. Sometimes the issue is page format. A competitor added a tighter FAQ block. Sometimes it’s freshness. Sometimes they earned stronger external mentions. Sometimes your own page still ranks, but the model now prefers another passage on the page or a different URL on your domain. Watch for displacement events the same way paid teams watch impression loss. They reveal where market pressure is actually happening. Useful tests include: Rewriting the opening answer block Adding a missing comparison section Improving author or source attribution Refreshing stale examples Adding clearer internal links to supporting pages One operating option in this market is Busylike, which monitors brand presence across LLMs and helps teams test changes in citation patterns. The value of any platform or agency here isn’t the dashboard itself. It’s whether it shortens the feedback loop between visibility loss and corrective action. Measure ROI for Your GEO and AEO Programs Teams often stop measurement too early. They track whether the brand was cited, maybe whether traffic rose, and call it success. That’s incomplete. Why citation count alone is not a business metric A citation can be commercially powerful, but only if it contributes to discovery, consideration, or conversion. CMOs need a model that connects AI visibility to business outcomes, not just awareness signals. That’s why GEO should be measured like a performance channel with assist behavior. According to Datapins’ analysis of ranking on ChatGPT , brands that track UTM parameters in ChatGPT-cited links see a 15-20% uplift in attributable referral traffic , and beta testers have reported 2.3x higher conversion rates from cited sources after recent OpenAI updates. Early data is still developing, but the directional takeaway is clear. AI citations can drive measurable commercial value when you instrument them correctly. A practical GEO measurement model for CMOs Start with a measurement stack that ties prompt visibility to site behavior and downstream outcomes. Metric Definition How to Measure Citation count Total appearances of your brand or domain in target ChatGPT prompts Manual prompt audits or LLM monitoring tools Share of voice Your portion of citations across a defined competitor set Compare citation frequency by prompt cluster Attributed referral traffic Visits from AI-cited links to your site Use tagged URLs and review in analytics platforms Citation-to-conversion rate The rate at which AI-referred visits turn into leads or sales Compare conversions from tagged AI traffic segments AI-influenced revenue Revenue connected to sessions or journeys that included AI-referred traffic Use CRM and analytics attribution models Citation quality Whether the model frames your brand in the right category and use case Manual qualitative review of outputs This creates a more useful reporting chain: Visibility . Are you cited in the prompts that matter? Quality . Is the model describing the brand accurately? Traffic . Are those citations producing attributable visits? Conversion . Do those visits become leads, demos, purchases, or pipeline? Revenue impact . Does AI visibility influence outcomes worth scaling? A lot of executive skepticism disappears once you show this sequence clearly. For broader planning, Busylike’s overview of GEO and AEO strategies for brand visibility with generative and answer engine optimization is useful for aligning content, technical work, and measurement in one operating model. The trade-off is that attribution won’t be perfect. Some influence remains invisible because users may read a recommendation in ChatGPT and convert later through another channel. That’s normal. The answer isn’t to ignore ROI. It’s to combine direct attribution with directional evidence from prompt share, branded demand, referral quality, and pipeline movement. Common Questions About Ranking in ChatGPT Question Answer How long does it take to rank in ChatGPT? It depends on your current authority, technical setup, and whether you already have pages that match prompt intent. Brands with strong entities and clean content architecture usually move faster than brands starting from generic blog content. Is traditional SEO enough? No. It still matters, but it doesn’t fully solve citation visibility. ChatGPT rewards pages that are easy to extract from, clearly structured, technically understandable, and supported by authority signals beyond the site. What pages should be optimized first? Start with high-intent pages. Product pages, category pages, solution pages, comparison pages, and FAQ assets usually have the strongest commercial upside. Can great content rank without schema? It can, but you’re making retrieval harder than it needs to be. Schema helps the model understand content type and entities more reliably. Do brand mentions off-site matter if they don’t send traffic? Yes. Off-site mentions help validate expertise and entity presence, which can influence whether the model sees your brand as a trustworthy source. What usually blocks performance? Weak page structure, buried answers, missing trust signals, low authority, stale content, and poor measurement discipline. Should teams treat ChatGPT like a search engine? Partly. It’s better to treat it like a retrieval and recommendation layer that sits between the user question and the click. That framing leads to better content and better KPIs. The brands that win in ChatGPT don’t rely on one trick. They combine prompt research, answer-first content, schema, authority building, and rigorous measurement. That’s what turns AI visibility from an interesting experiment into a repeatable growth channel. Frequently Asked Questions What does it mean to rank in ChatGPT? Ranking in ChatGPT means your brand is included, mentioned, or recommended within AI-generated answers when users ask relevant questions, rather than appearing as a traditional search result link. How does ChatGPT decide which brands to mention? ChatGPT selects brands based on relevance to the prompt, clarity of available content, authority signals, and how consistently a brand is associated with specific topics across trusted sources. Is ranking in ChatGPT the same as SEO? No. SEO focuses on ranking web pages in search engines, while ranking in ChatGPT focuses on being part of the answer itself, where only a limited number of brands are typically included. What is the role of content in ChatGPT visibility? Content is the foundation of visibility, as AI models rely on existing information to generate responses, making it critical to publish clear, structured, and authoritative content aligned with user intent. How can I improve my chances of being mentioned in ChatGPT? You can improve your visibility by creating high-quality, structured content, strengthening your brand’s authority, maintaining consistent positioning, and ensuring your content directly answers common user questions. What types of content work best for ChatGPT visibility? Content that performs well includes FAQs, guides, comparison pages, use-case content, and clear explanations that AI systems can easily interpret and reuse. Does brand authority matter for ChatGPT rankings? Yes, brands that demonstrate strong authority, credibility, and consistency across multiple sources are more likely to be selected and recommended in AI-generated answers. How long does it take to see results? Initial improvements may appear within weeks, but meaningful increases in visibility and mentions typically develop over one to three months as content is indexed and reinforced across sources. How can I track my brand’s visibility in ChatGPT? You can track visibility by monitoring prompts relevant to your category, analyzing how your brand is mentioned, and measuring share of voice and sentiment in AI-generated responses. What are common mistakes brands make? Common mistakes include relying only on traditional SEO tactics, creating unstructured or generic content, lacking clear positioning, and not monitoring how AI platforms represent their brand. If your team needs a working GEO program, not just a checklist, Busylike helps brands improve visibility across ChatGPT and other AI environments through content structuring, entity strategy, LLM monitoring, and AI-first media planning tied to measurable business outcomes.

For over two decades, digital advertising has been built around a simple idea: drive the click, optimize the conversion, and scale what works. Performance marketing has rewarded immediacy—what happens after the impression, after the click, after the session. But in the AI search era, that model is no longer sufficient. Today, platforms like ChatGPT, Google AI Overviews, Perplexity AI, and Claude are fundamentally changing how users discover brands. Instead of navigating through search results, users ask questions and receive synthesized answers. These answers are constructed by aggregating, interpreting, and prioritizing content from across the web. The interface has shifted from links to language. This creates a new layer of competition. Brands are no longer just competing for clicks—they are competing to be included in the answer itself. Reddit Ads win in the AI Search Era In this environment, paid media takes on a new role. It doesn’t end at driving traffic; it influences the content ecosystem that AI systems learn from and reference. The discussions, mentions, and narratives generated through paid campaigns can persist, compound, and ultimately shape how your brand appears in AI-generated responses. This is where Reddit becomes uniquely powerful. Unlike most advertising platforms, Reddit sits at the intersection of paid media, organic discussion, and long-term content persistence. It enables brands to not only drive bottom-of-funnel performance today, but also build the kind of contextual, high-trust signals that influence AI discovery tomorrow. The New Customer Journey: From Search to AI to Community The traditional digital customer journey followed a predictable path. A user searched for a keyword, evaluated a set of links, visited a website, and made a decision. Marketers optimized each step of that funnel with increasing precision. That journey has now evolved into something far more layered and iterative. Today, a typical path looks like this: a user starts with a prompt on an AI platform, receives a synthesized answer, explores the sources behind that answer, seeks validation through community discussions, and only then moves toward a decision. The process is no longer linear. It is recursive and influenced by multiple layers of trust. Community-driven platforms now play a central role in this journey. Among them, Reddit stands out as one of the most influential. It functions as a living database of user experiences, opinions, and comparisons across nearly every category. Whether someone is researching software, evaluating products, or exploring services, there is almost always a Reddit thread capturing real user perspectives. This matters because users trust other users more than they trust brands. AI systems are designed to reflect that trust. When generating answers, they prioritize sources that demonstrate authenticity, diversity of opinion, and contextual depth. Reddit delivers all three at scale. As a result, Reddit is no longer just a discovery platform. It has become a validation engine that influences both human decisions and AI-generated outputs. Why Reddit Content Dominates AI Citations Why Reddit Content Dominates AI Citations To understand why Reddit plays such a central role in AI-generated answers, it’s important to look at how AI systems evaluate and prioritize content. These systems are designed to surface information that is not only relevant, but also trustworthy, nuanced, and grounded in real-world experience. Reddit consistently performs well across these criteria, which is why it is so frequently cited. Authenticity at Scale Reddit content is created by real users sharing genuine opinions, experiences, and feedback. Unlike branded content, which is often optimized for messaging and positioning, Reddit discussions tend to be unfiltered and balanced. This authenticity makes them highly valuable for AI systems trying to generate credible answers. Depth and Context Reddit threads often go far beyond surface-level information. A single discussion can include multiple perspectives, detailed explanations, follow-up questions, and real-world use cases. This layered structure gives AI models richer context to work with, enabling more nuanced and informative responses. Subreddits as Intent Clusters Each subreddit functions as a focused hub of interest and intent. Whether it’s SaaS tools, consumer electronics, or niche categories, Reddit organizes discussions in a way that mirrors how users think and search. This makes it easier for AI systems to map queries to relevant conversations. Engagement as a Quality Signal Upvotes, comments, and ongoing interaction act as strong indicators of content value. Threads that receive sustained engagement signal relevance and usefulness, which AI systems can interpret when selecting sources. Long-Term Content Persistence Unlike most social content, Reddit threads remain searchable and continue to generate engagement over time. This persistence makes them highly accessible to both users and AI systems long after they are created. The Strategic Implication for Advertisers The takeaway is clear: conversations on Reddit are not just influencing users—they are shaping AI outputs. For advertisers, this means that participating in Reddit discussions can directly impact how their brand is represented in AI-generated answers. It is not just a media channel, but a long-term visibility engine. Core Reddit Ad Formats Driving BOFU Performance Reddit’s advertising formats are designed to integrate seamlessly into the user experience. Unlike interruptive formats on other platforms, Reddit ads succeed when they feel native to the platform’s conversational environment. Promoted posts appear directly within subreddit feeds and resemble organic content. This allows brands to introduce ideas, questions, or narratives in a way that feels natural. When executed well, these posts can spark meaningful engagement and drive high-intent traffic from users who are already evaluating options. Conversation-driven formats encourage users to participate directly in discussions. These ads are built to generate replies, opinions, and shared experiences. This type of engagement is particularly powerful at the bottom of the funnel, where users are looking for validation before making a decision. Carousel and creative formats provide more structure, allowing brands to communicate key features, comparisons, or use cases in a visual format. While Reddit is primarily text-driven, these formats can reinforce differentiation and clarity during the decision stage. High-impact placements, such as takeovers, offer broader visibility across the platform. While often associated with awareness, they can also strengthen credibility and category presence when combined with strong engagement strategies. What makes these formats effective is not just their design, but their alignment with intent. Reddit users are actively searching for answers, not passively consuming content. This creates a unique environment where ads can directly influence decisions. The Reddit Ads Flywheel The Reddit Ads Flywheel The real advantage of Reddit Ads is not limited to campaign performance. It comes from a compounding system where paid media generates lasting value over time. This system can be understood as the Reddit Ads Flywheel. Step 1: Targeted Paid Exposure The flywheel begins with precise targeting. Brands identify high-intent subreddits where users are already discussing relevant topics. Instead of broad audience targeting, the focus is on contextual relevance. Step 2: Engagement and Conversation Once the ad is live, users begin to interact. They comment, ask questions, and share opinions. This transforms the ad into a dynamic discussion that adds depth and credibility. Step 3: Creation of a Persistent Content Layer Unlike most paid media, the content generated through Reddit Ads does not disappear. Threads remain searchable, continue to attract engagement, and become part of Reddit’s long-term content ecosystem. Step 4: AI Ingestion and Citation AI platforms continuously analyze publicly available content. Reddit threads—especially those with strong engagement—are frequently incorporated into this process. Discussions initiated by ads can later appear in AI-generated answers and recommendations. Step 5: Compounding Trust and Discovery As these threads surface in AI answers and search results, new users encounter the brand in a more organic and trusted context. Instead of seeing an ad, they see real conversations, which increases credibility and conversion likelihood. Step 6: Long-Term Performance Impact The final stage is where everything compounds. Initial media spend continues to generate value through ongoing visibility, AI citations, and community validation. This reduces acquisition costs over time while strengthening brand presence. The Key Takeaway Every Reddit campaign should be viewed not just as a short-term performance effort, but as a long-term investment in AI visibility and brand perception. Here is a video which gives you context about if reddit ads perform in 2026: Reddit vs Other Paid Channels in the AI Era Most paid channels were not designed for an AI-driven discovery environment. Search ads are effective at capturing intent, but they do not create lasting content that influences AI systems. Social ads can generate engagement, but that engagement is often short-lived and not structured for long-term discovery. Display advertising offers scale, but lacks depth and interaction. Reddit stands apart because it combines performance marketing with content creation and community validation. It produces discussions that persist, evolve, and become part of the broader information ecosystem. In the AI era, this is a critical advantage. Visibility is no longer just about impressions—it is about being included in the sources that shape decisions. Strategic Playbook: How to Win with Reddit Ads To succeed with Reddit Ads, marketers need to move beyond traditional campaign thinking and adopt a more holistic approach. The first step is targeting intent rather than demographics. Subreddits function like keyword clusters, allowing brands to engage users based on what they care about, not just who they are. The second step is designing for discussion. Ads should feel like contributions, not interruptions. Asking questions, presenting comparisons, and inviting opinions can significantly increase engagement. The third step is aligning content with AI discovery patterns. Topics like best tools, comparisons, and recommendations are more likely to be referenced by AI systems. The fourth step is integrating paid and organic efforts. Paid campaigns can spark conversations, but sustained engagement is necessary to maintain visibility and credibility. The fifth step is expanding measurement frameworks. In addition to traditional metrics, brands should track AI-related indicators such as citation frequency, share of voice, and sentiment across platforms. From Media Buying to AI Influence The rise of AI search is redefining what it means to succeed in media buying. It is no longer just about efficiency and performance—it is about influence. Reddit enables brands to operate at this new level. It allows them to participate in authentic conversations, generate meaningful content, and shape how they are perceived by both users and AI systems. This requires a shift in mindset. Campaigns should not be viewed as isolated efforts, but as contributions to a larger ecosystem of information and perception. In this context, Reddit Ads are not just a tactic. They are a strategic tool for building long-term visibility and authority. Conclusion: The Future of Performance Media As AI continues to reshape how people search, discover, and decide, the definition of performance marketing is expanding. The most effective strategies will not just optimize for conversions. They will optimize for presence within AI systems. Reddit Ads offer a unique advantage by combining immediate performance with long-term impact. They generate conversations that persist, influence AI outputs, and build trust over time. In a world where AI-generated answers are becoming the primary interface for information, this dual impact is critical. The brands that win will be those that understand how to operate across both dimensions—conversion and conversation, performance and perception, paid media and AI influence. Because in the end, the most effective ads are not just the ones that get clicked. They are the ones that get remembered, discussed, and recommended. And increasingly, that journey begins on Reddit. Frequently Asked Questions Why are Reddit Ads effective in the AI search era? Reddit content is frequently used by AI models as a source of authentic, experience-driven insights. Advertising on Reddit helps brands influence not only users directly, but also the content that AI systems may later reference and surface. How does Reddit impact AI-generated search results? AI platforms often rely on forums like Reddit for real-world opinions, reviews, and discussions. Threads with strong engagement can shape how brands are described, compared, and recommended in AI-generated answers. What makes Reddit different from other advertising platforms? Reddit is community-driven and conversation-based. Instead of polished brand messaging, it prioritizes honest discussions, making it a powerful environment for building credibility and influencing perception. What types of Reddit Ads perform best for AI visibility? High-performing formats include: Sponsored posts that blend into discussions Educational or value-driven content Community-relevant storytelling Problem–solution oriented messaging How do Reddit Ads contribute to the “AI visibility flywheel”? Reddit Ads can spark engagement and discussions, which generate organic content. That content may then be picked up by AI models, increasing your brand’s visibility in AI-generated responses over time. Can Reddit Ads influence purchase decisions? Yes. Reddit users often share detailed experiences and recommendations. When combined with advertising, this creates a powerful mix of paid and organic influence that impacts both human users and AI outputs. How should brands approach creative on Reddit? Brands should focus on authenticity, transparency, and value. Content that feels overly promotional tends to underperform, while helpful, honest contributions are more likely to resonate. How do you measure the success of Reddit Ads in the AI era? Key metrics include: Engagement (comments, upvotes, discussions) Traffic and conversions Brand mentions in Reddit threads Visibility and sentiment in AI-generated answers What are common mistakes brands make with Reddit Ads? Using overly polished or sales-heavy messaging Ignoring community norms and tone Not engaging with comments or discussions Treating Reddit like a traditional ad channel How can brands get started with Reddit Ads for AI visibility? Start by identifying relevant communities, understanding their culture, and creating content that adds value. Combine paid placements with active participation to build credibility and long-term impact.

Search has long been a cornerstone of how we find information online. Traditional search engines rely on keywords and indexing to deliver results, but the rise of AI search is changing this landscape. Instead of typing keywords and sifting through pages of links, users now interact with AI models through prompts—natural language inputs that guide the AI to discover and present information in new ways. This shift from keyword search to prompt-based discovery is reshaping how digital marketing professionals approach visibility and engagement. AI Search Optimization and Prompt-Based Discovery What Is Prompt-Based Discovery? Essentials for AI Search Optimization Prompt-based discovery uses natural language prompts to interact with AI models that understand context, intent, and nuance. Unlike traditional search engines that match keywords to indexed pages, AI search systems interpret the meaning behind a prompt and generate responses that synthesize information from multiple sources. For example, instead of typing “best running shoes 2024,” a user might ask, “What are the top running shoes for marathon training this year?” The AI understands the context—marathon training, current year—and provides a tailored answer rather than a list of links. This approach transforms search from a retrieval task into a discovery process. Users receive concise, relevant, and often personalized information without needing to refine queries repeatedly. How Prompt-Based Discovery Changes Digital Marketing Digital marketers must rethink how they achieve AI visibility in this new environment. Traditional SEO focuses on keywords, backlinks, and page rankings. With AI search optimization, the focus shifts to: Content quality and relevance: AI models prioritize content that answers specific questions clearly and accurately. Contextual information: Content that provides detailed context, examples, and explanations performs better. Structured data: Using schema markup helps AI understand and extract key information. Geo relevance: For local businesses, integrating geo-specific details improves chances of appearing in location-based AI responses. Marketers need to create content that anticipates user prompts and delivers value in a conversational, informative style. This means moving beyond keyword stuffing to building trust and authority through clear, helpful content. Examples of Prompt-Based Discovery in Action Example 1: Local Restaurant Search A user asks, “What are the best vegan-friendly restaurants near me with outdoor seating?” Traditional search engines might return a list of restaurants with those keywords. An AI search system understands the full prompt, including dietary preference, location, and seating preference, and provides a curated list with summaries, reviews, and directions. This highlights the importance of geo data and detailed content for restaurants aiming to improve AI visibility. Example 2: Product Recommendations Instead of searching “smartphones under $500,” a user prompts, “Which smartphones under $500 have the best battery life and camera for travel?” AI search synthesizes product specs, reviews, and user feedback to generate a ranked list with explanations, helping users make informed decisions quickly. Marketers in e-commerce can optimize product descriptions and FAQs to answer such detailed prompts. Challenges of AI Search and Prompt-Based Discovery While AI search offers many benefits, it also presents a number of significant challenges that must be carefully considered and addressed: Content discoverability: One of the primary challenges associated with AI-driven search is the issue of content discoverability. AI models, particularly those that utilize machine learning algorithms, often prioritize content from authoritative and well-established sources. This bias can inadvertently marginalize smaller websites and emerging voices, making it increasingly difficult for them to gain the visibility they need to reach their target audiences. As a result, valuable insights or innovative perspectives from lesser-known creators may remain hidden, limiting the diversity of information available to users and stifling the growth of smaller entities in the digital landscape. Bias and accuracy: The accuracy of AI-generated responses is heavily influenced by the training data that underpins these models. If the training data contains biases or reflects outdated information, the AI's outputs can perpetuate these inaccuracies, leading to misleading or skewed results. This is particularly concerning in sensitive areas such as health, finance, and social issues, where incorrect information can have serious consequences. Continuous monitoring and updating of training datasets are essential to mitigate these risks and ensure that AI systems provide reliable and current information to users. User trust: Establishing user trust in AI-generated answers is another significant challenge. Unlike traditional search results where users can easily verify sources, AI responses often lack transparency regarding their origins. This can lead to skepticism among users who may question the validity of the information presented to them. To build trust, it is crucial for developers and organizations utilizing AI search technologies to implement mechanisms that enhance transparency, such as citing sources or providing context for the information shared. This transparency can help users feel more confident in the reliability of AI-generated content. Geo-specific nuances: AI systems must also grapple with the complexities of geo-specific nuances in language and culture. Accurately interpreting location-based prompts requires a deep understanding of regional dialects, idioms, and cultural references, which can vary significantly even within the same language. Misinterpretations can lead to irrelevant search results or miscommunication, particularly in a globalized digital environment where users from diverse backgrounds interact. Developers must invest in refining AI capabilities to better understand and respond to these nuances, ensuring that users receive contextually relevant and appropriate information. Given these challenges, it is imperative for digital marketers to actively monitor emerging AI search trends and adapt their strategies accordingly. By staying informed about the evolving landscape of AI and search technologies, marketers can better position their content to remain trustworthy and accessible. This proactive approach will not only enhance the visibility of their content but also contribute to a more equitable digital ecosystem where diverse voices can thrive, ultimately enriching the user experience. AI Search is similar to Text Based Games from the 80s Preparing for the Future of Search To succeed in the era of prompt-based discovery, digital marketing professionals should: Focus on user intent: Understand the questions users ask and create content that answers them clearly. Incorporate geo data: Use location-specific keywords and structured data to improve local AI visibility. Build content depth: Provide detailed, well-organized information that AI can easily interpret. Engage with AI tools: Experiment with AI content generation and analysis tools to optimize for prompt-based queries. Monitor AI search trends: Stay updated on how AI models evolve and adjust strategies accordingly. By embracing these practices, marketers can ensure their brands remain visible and relevant as AI search continues to grow. Frequently Asked Questions (FAQ) What is prompt-based discovery in AI search? Prompt-based discovery refers to how users find information by asking full questions or instructions in AI platforms, rather than typing short keywords. AI systems then generate direct answers based on those prompts. How is prompt-based discovery different from traditional search? Traditional search relies on keywords and links. Prompt-based discovery is conversational and intent-rich—users describe what they want, and AI delivers synthesized answers instead of a list of results. Why is prompt-based discovery important for brands? Because it represents high-intent moments. Users are often closer to making decisions, and AI typically provides a limited number of recommendations—making visibility in those answers critical. How can brands optimize for prompt-based discovery? Brands should: Identify common prompts in their category Create content that directly answers those prompts Use clear, structured formats (FAQs, lists, guides) Reinforce their expertise and positioning What types of prompts should brands focus on? High-value prompts include: “Best [product/service] for…” “How to choose…” “What is…” or “How does…” Comparisons (e.g., “X vs Y”) Recommendations and use cases How do AI models decide which brands to include in answers? AI models prioritize content that is relevant, structured, authoritative, and aligned with the user’s intent. Strong entity signals and consistent positioning also increase selection likelihood. What role does content play in prompt-based discovery? Content is the foundation. AI systems rely on existing content to generate answers, so brands need to publish high-quality, intent-driven content that can be easily interpreted and reused. How can brands measure success in prompt-based discovery? Key metrics include: Visibility in AI-generated responses Share of voice across targeted prompts Frequency of brand mentions and citations Traffic and conversions from AI-driven interactions What are common mistakes brands make? Focusing only on keywords instead of user intent Creating generic or unstructured content Ignoring how real users phrase prompts Not monitoring AI platform outputs What is the future of prompt-based discovery? Prompt-based discovery will become the dominant way users interact with information online. Brands that align their content and strategy with this shift will gain a significant competitive advantage.

In this compelling episode of the Founders in LA podcast, host Ethan Cole sits down with Vadi Efe, the visionary CEO and founder of Busylike. As the landscape of digital engagement shifts, Vadi provides an insider’s look at how Busylike is revolutionizing the B2B marketing sphere by building a high-trust bridge between forward-thinking brands and elite video creators. The discussion dives deep into the platform’s mission to move beyond traditional advertising, focusing instead on authentic storytelling and scalable video content that drives real business results. Founders in LA podcast in 2026 In 2026, the Founders in LA podcast, hosted by Ethan Cole, PhD, has solidified its reputation as the essential audio chronicle of the "Silicon Beach" ecosystem, specifically focusing on the intersection of product management and entrepreneurial grit. Known for its organic, one-take conversation format, the show has shifted its 2026 programming to highlight the rise of Agentic AI and decentralized media within the Los Angeles startup scene, featuring guests who are transitioning from traditional software to voice-based and blockchain-integrated platforms. The podcast’s influence is currently peaking alongside major local industry milestones, such as LA Tech Week and the Inc. Founders House L.A. event in Santa Monica this April, where the community gathers to discuss the exact themes of financial sustainability and creator-led ecosystems you mentioned in your CNN Turk interview. Watch the interview here: https://www.youtube.com/watch?v=sft16ToJ6Ek Vadi Efe , CEO of Busylike, is the guest on the Founders in LA podcast. Busylike matches brands with audio and video creators for B2B marketing. They work with podcasters and YouTube channels to facilitate ad placement, branded content, and sponsorship opportunities. Vadi Efe's journey as an entrepreneur started with a music platform and later included a chat platform, which was acquired. He moved to California to explore entrepreneurial opportunities. Busylike addresses the challenge of connecting brands with niche content relevant to their target audience. They received funding from Sunstone Investments and are part of the Long Beach Accelerator. Networking and collaboration with industry experts were key to securing funding. Vadi Efe highlights the importance of creating value to attract investors. Los Angeles, being the entertainment and tech capital, offers unique experiences, such as encounters with celebrities like Tim Ferriss and impromptu Green Day concerts.

In an exciting development for the digital advertising industry, Sunstone Management has announced an investment of $150,000 in Busylike , a rapidly emerging podcast ad marketplace. Sunstone Management is a diversified private capital firm based in Irvine, California that invests in early-stage tech entrepreneurs. Sunstone Management Busylike Investment This injection of funds will boost the overall funding of Busylike (formerly Businesswise) to $250,000, enabling the company to enhance its capabilities and create added value for brands with a B2B target audience. The objective is to foster partnerships between brands and B2B creators who are professional opinion leaders, capable of making a remarkable impact and assisting brands in expanding their client base. Sunstone Management in 2026 In 2026, Sunstone Management is celebrating its second decade by doubling down on its unique "Public-Private-Partnership" (P3) model and a major corporate restructuring. Under the leadership of CEO John Keisler, the firm has transitioned its core operations into the Sunstone Investment Group, which includes specialized arms like Sunstone Cities for government consulting and Sunstone Venture Partners for early-stage tech. A major highlight of the year is the 2026 Sunstone CSU Startup Launch, the premier pitch competition across all 23 California State University campuses, which will award $200,000 in seed funding this May at CSUN. Additionally, the firm is heavily focused on "Space Beach" and clean energy logistics, utilizing its Sunstone Stage in Irvine to bridge the gap between diverse startup founders, academic institutions, and municipal leaders to foster equitable economic growth throughout Southern California. Busylike plans for 2026 Busylike aims to revolutionize the way brands connect with their B2B audience by leveraging the power of influential B2B creators. In today’s digital landscape, where trust and credibility play a pivotal role, partnering with opinion leaders and professionals in a specific niche can significantly impact a brand's growth potential. With the investment from Sunstone Management, Busylike will be able to expand its ad marketplace and implement key enhancements to deliver an exceptional user experience. The startup will be part of Long Beach Accelerator 's 6th cohort. The infusion of capital will facilitate the development of cutting-edge technologies, advanced targeting algorithms, and seamless collaboration tools, ensuring that brands can identify and collaborate with the most suitable B2B creators. B2B creators, as professional opinion leaders, hold a wealth of knowledge and expertise in their fields. Their content creation skills, coupled with their extensive network of industry professionals, provide brands with an invaluable resource for establishing credibility and driving growth. Busylike recognizes the potential of these creators and aims to empower them by connecting them with brands that share their vision and values.

Imagine having a creative partner who never sleeps, constantly brainstorming fresh ideas, and tailoring ads that resonate perfectly with your audience. That’s exactly what generative AI brings to the table in ad creation. If you’re aiming to push your brand’s digital advertising to the next level, this technology is a game-changer. Let’s dive into how generative AI is transforming ad creation and how you can harness its power to craft compelling, effective campaigns. Why Generative AI is a Must-Have for Modern Ad Creation You’ve probably noticed how digital ads have become more personalized and engaging over the years. That’s no accident. Generative AI uses advanced algorithms to analyze data, predict trends, and create content that speaks directly to your target audience. It’s like having a creative team that’s data-driven and lightning-fast. Here’s why you should care: Speed and Efficiency: AI can generate multiple ad variations in minutes, freeing up your team to focus on strategy and optimization. Personalization at Scale: Tailor ads to different demographics, locations, and user behaviors without manually creating each version. Cost-Effective Creativity: Reduce the need for expensive photo shoots or video productions by generating visuals and copy digitally. Data-Backed Decisions: AI learns from past campaign performance to improve future ad content, boosting ROI. By integrating generative AI into your ad creation process, you’re not just keeping up with the competition—you’re setting the pace. Generative AI in Ad Creation: Revolutionizing Digital Advertising How Generative AI Enhances Audio and Video Ad Campaigns Audio and video ads are the heart of immersive digital marketing. But producing high-quality content can be time-consuming and expensive. Generative AI changes the game by automating parts of the creative process while maintaining a human touch. Audio Ads Voice Synthesis: AI can generate natural-sounding voiceovers in multiple languages and accents, perfect for global campaigns. Scriptwriting Assistance: Need catchy taglines or engaging scripts? AI drafts them based on your brand tone and audience insights. Sound Design: Create background music or sound effects tailored to your ad’s mood without hiring a composer. Video Ads Automated Video Editing: AI tools can assemble clips, add transitions, and sync audio to visuals quickly. Dynamic Visuals: Generate animations or modify existing footage to fit different platforms and audience segments. Personalized Video Content: Deliver customized video ads that change based on viewer data, increasing engagement. These capabilities allow brands to launch diverse, high-impact campaigns faster and with less overhead. AI-assisted video editing interface on a computer screen Practical Tips for Integrating Generative AI into Your Ad Strategy Ready to jump in? Here’s how to make the most of generative AI for ad creative: Start Small and Experiment Begin with a pilot project—maybe a single campaign or ad format. Test different AI tools to see which align best with your brand’s voice and goals. Leverage Data Wisely Feed your AI with quality data from past campaigns, customer insights, and market trends. The better the input, the smarter the output. Maintain Human Oversight AI is powerful but not perfect. Always review and tweak AI-generated content to ensure it fits your brand identity and messaging. Focus on Multichannel Consistency Use AI to create cohesive ad variations across platforms—social media, streaming services, podcasts—while adapting to each channel’s unique style. Measure and Optimize Continuously Track performance metrics closely. Use AI’s predictive analytics to refine your ads in real-time and maximize impact. By following these steps, you’ll build a robust, AI-enhanced ad creation workflow that drives results. The Future of Digital Advertising with Generative AI The digital advertising landscape is evolving fast, and generative AI is at the forefront of this transformation. As AI models become more sophisticated, expect even more personalized, interactive, and immersive ad experiences. Imagine ads that adapt instantly to your mood, location, or even the weather outside. Or campaigns that generate fresh content daily, keeping your brand always relevant and engaging. This isn’t sci-fi—it’s happening now. For brands looking to stay ahead, embracing generative AI is not optional; it’s essential. It empowers you to create smarter, faster, and more impactful ads that resonate deeply with your audience. If you want to explore how generative AI can elevate your campaigns, check out this resource on generative ai for ad creative. Unlocking Growth with AI-Powered Ad Marketplaces One of the most exciting developments is the rise of AI-driven ad marketplaces. These platforms connect brands with a vast network of creators and AI tools, streamlining the entire ad production process. Here’s how they help: Access to Diverse Talent: Tap into a global pool of creators who use AI to produce unique content. Integrated AI Tools: Use built-in AI features for scriptwriting, video editing, and audio production all in one place. Faster Time to Market: Launch campaigns quickly with automated workflows and real-time collaboration. Scalable Campaigns: Easily scale your ads across multiple channels and formats without extra hassle. By partnering with an integrated media agency that leverages these marketplaces, you can supercharge your digital advertising efforts and drive significant growth. Generative AI is not just a buzzword—it’s a powerful tool reshaping how brands create and deliver ads. By embracing this technology, you unlock new levels of creativity, efficiency, and personalization that can set your campaigns apart in a crowded digital world. So why wait? Dive into the future of ad creation today and watch your brand’s story come alive like never before.

The campaign we have developed for PayPal  Europe for a regional product launch aimed to promote international commerce by empowering small business owners and individuals to sell abroad. The objective was clear: to increase PayPal’s penetration in cross-border transactions and highlight the role of global commerce in reducing economic deficits. To bring this vision to life, we crafted a comprehensive campaign featuring podcast-style interviews , merchant success stories , video content , and step-by-step guides  that made selling abroad accessible to entrepreneurs. This campaign culminated in a major launch event and a press conference, with ongoing support through digital channels and a microsite that provided all the necessary resources for small businesses to succeed in international markets. PayPal in 2026 - News and Updates In 2026, PayPal is navigating a significant "reset year" defined by a leadership transition and a pivot toward agentic commerce. Following a disappointing fourth-quarter performance in 2025 that saw stock prices tumble, the company appointed Enrique Lores (formerly of HP) as CEO, effective March 1, 2026, to revitalize its core branded checkout business which has faced stiff competition from Apple and Google. To regain its edge, PayPal is aggressively integrating with AI ecosystems, launching "Instant Checkout" partnerships with OpenAI (ChatGPT), Microsoft Copilot, and Google, allowing AI agents to discover products and complete transactions securely using the PayPal wallet. While traditional retail growth has slowed, the company is seeing bright spots in Venmo and its stablecoin, PYUSD, which reached a circulating supply of over $3.6 billion, signaling PayPal's intent to remain the foundational "trust layer" for the next era of digital and blockchain-based finance. Storytelling Through Podcast-Style Interviews At the heart of this campaign was storytelling. We conducted podcast-style interviews with small business owners who had successfully integrated PayPal into their operations to grow their businesses internationally. These interviews offered firsthand accounts of the challenges and triumphs of cross-border commerce, providing valuable insights to other entrepreneurs looking to expand their reach. The podcast-style format allowed us to engage audiences with authentic stories that highlighted the transformative power of PayPal’s international commerce tools. These interviews, coupled with relatable experiences, showcased how easy and effective it could be for small business owners to sell abroad with PayPal. We used these stories as a key part of the online marketing strategy, leveraging them across digital platforms to reach target audiences. Success Stories of PayPal Merchants We further enhanced the campaign by producing videos  of five successful merchants who had significantly grown their businesses with PayPal’s cross-border payment solutions. These merchants came from diverse industries, ranging from e-commerce to handmade goods, and each shared their unique journey of expanding their business internationally using PayPal. The videos highlighted how PayPal’s seamless integration enabled these merchants to reach new markets, increase their revenue, and streamline their payment processes for international customers. By focusing on real success stories, we demonstrated PayPal’s tangible impact on small businesses, building trust and credibility among potential users. Step-by-Step Guides to Selling Abroad To make the process of selling abroad even more accessible, we developed step-by-step guides  that outlined the essential steps entrepreneurs needed to take to successfully expand into international markets. These guides covered everything from setting up a PayPal account for cross-border transactions to managing currency conversions, shipping logistics, and customer service for international buyers. These guides were a critical part of the campaign, offering practical resources for small businesses to navigate the complexities of global commerce. The content was structured to be clear and actionable, ensuring that even first-time sellers felt confident in taking their businesses abroad. Microsite and Launch Event The entire campaign was housed on a microsite  we created, which served as a central hub for all the resources entrepreneurs needed to get started with international commerce. The microsite featured the podcast interviews, success story videos, step-by-step guides, and additional content to support small business owners throughout their journey. This digital platform allowed PayPal to maintain an ongoing relationship with users and provide continued support long after the campaign’s initial launch. We introduced the campaign at a major launch event  and press conference , where PayPal's leadership highlighted the importance of cross-border commerce in reducing economic deficits and creating new opportunities for entrepreneurs. The event attracted significant media attention and helped position PayPal as a champion for small businesses looking to expand internationally. Empowering Entrepreneurs and Expanding PayPal’s Reach Our campaign for PayPal successfully mobilized small entrepreneurs to embrace cross-border commerce, increasing PayPal’s penetration in the international market. Through authentic storytelling, real-life success stories, and practical guides, we empowered small businesses with the tools and confidence to grow their operations globally. The combination of engaging content, digital marketing, and a high-profile launch event resulted in increased awareness of PayPal’s international commerce solutions, driving adoption among small business owners across the region. The campaign reinforced PayPal’s position as a leader in the global payments space and demonstrated how the platform could help entrepreneurs overcome the barriers to international selling.

In a world where screens and streams fuel wanderlust, Turkish Airlines has taken a bold step in content marketing with its immersive podcast series, Widen Your World  - part of Turkish Airlines Series. More than just an audio show, the podcast serves as a passport to discovery, inviting listeners to wander through bustling Turkish bazaars, soar above Cappadocia’s surreal landscape, and taste the richness of Anatolian cuisine—all from the comfort of their headphones. Launched and operated by Podmuse (part of Busylike ) and Inflow Network ,  also with the creative contribution of DDB , the Turkish Airlines Series  podcast combines expert storytelling with high-quality production, making it a standout in the travel audio and video landscape. It doesn’t simply promote destinations—it captures the essence of travel itself: the people you meet, the flavors you savor, and the memories that linger long after the journey ends. Transporting Listeners Through Sound At the heart of the series lies its ability to transform audio into an evocative journey. When listeners tune in, they’re not simply hearing about Istanbul—they’re strolling through the Grand Bazaar, surrounded by the scent of roasted chestnuts and the melodic calls of vendors. In the Cappadocia Chronicles  episode, they can practically feel the morning chill as hot-air balloons drift over the honeycomb hills, painting the sky with vibrant hues of orange and pink. The immersive soundscapes extend beyond iconic landmarks. Listeners are transported to quaint village squares, where the rhythmic clang of a blacksmith’s hammer mingles with the soft murmur of locals sipping tea. They are swept away to coastal towns where waves crash against ancient stone harbors, or to sunlit orchards where the rustle of olive branches evokes the timeless rhythm of rural life. Narrated by award-winning Hollywood voice artist John Raynar , each episode carries a sense of gravitas and warmth. His voice guides listeners through the labyrinthine streets of ancient cities, over the sunlit waters of the Mediterranean, and into the intimate kitchens where generations-old Turkish recipes are prepared with care. The podcast’s original music and cinematic sound design, created with meticulous attention to detail, complete the sensory experience, making it easy to forget you’re not actually in Türkiye. Authentic Stories, Real Voices What makes Widen Your World  stand out is its ability to weave authentic voices into its episodes. Through collaborations with travel influencers, creators, and adventurers, the series offers a personal and relatable perspective. In the video interview-style episode Influencer-Recommended: How Influencers Navigate Landmark Destinations , travel storyteller Nicole Ghelbi  takes listeners on a guided exploration of Türkiye’s hidden gems. Her vivid descriptions of serene coastlines and lively local markets paint a portrait of a country both dynamic and timeless. Similarly, in A Life on the Road , filmmaker Tristan Zhou  shares candid reflections on the realities of a nomadic lifestyle—capturing both the creative freedom and the solitude that come with it. These real-life narratives give Widen Your World  an intimate and personal edge, offering listeners more than just travel tips—they provide a glimpse into the transformative power of exploration. Hearing travelers describe the goosebumps they felt when witnessing the ethereal sunrise over Mount Nemrut or the warmth of being welcomed into a stranger's home for tea makes the experience feel tangible and relatable. Bridging Cultures Through Food and Tradition No journey to Türkiye is complete without tasting its cuisine, and the podcast ensures listeners get a mouthwatering introduction to its culinary wonders. The Culinary Quests  episode invites food enthusiasts to savor the country’s rich flavors—from the flaky layers of a perfect börek to the bold, aromatic spices of a simmering pot of lamb stew. But the culinary storytelling goes beyond mere descriptions of dishes. Listeners are introduced to the people behind the food: the grandmother who still hand-rolls her yufka dough, the market vendor who shares family recipes passed down for generations, and the chefs who reinvent tradition with modern flair. Beyond Türkiye: A Global Perspective While Turkish culture and heritage take center stage, Widen Your World  also embraces a broader, global view. Episodes such as Exploring the Jewels of the Mediterranean  transport listeners to sun-soaked shores, from the ancient streets of Barcelona to the idyllic islands of Santorini and Capri. With Turkish Airlines connecting these destinations through seamless flights, the podcast subtly underscores the brand’s role as the bridge between cultures and continents. The tech-savvy traveler is not forgotten either. In Tech Tools and Tips for Travelers , the podcast explores cutting-edge travel technology, helping listeners stay connected, navigate new cities, and enhance their journeys with the latest gadgets and apps. From smart luggage with built-in tracking to translation devices that break language barriers, the episode offers practical insights for modern globetrotter. The Art of Production: Crafting an Immersive Experience Producing a podcast that captures the essence of travel requires more than compelling narration—it demands craftsmanship. Each episode features bespoke musical compositions, original soundscapes, and carefully layered effects that make the listening experience feel almost cinematic. Listeners hear not only the rhythmic beat of darbuka drums during a festival celebration but also the faint echo of footsteps in a centuries-old caravanserai. In addition to audio episodes, the podcast occasionally steps into the visual realm. Select video interviews, moderated by seasoned host BJ Cunningham , bring viewers face-to-face with adventurers and creatives. The combination of audio and video content gives Widen Your World  a dynamic, multi-dimensional appeal, catering to both podcast enthusiasts and visual storytellers. Expanding Horizons in 2025 and Beyond As the podcast gains momentum, Turkish Airlines shows no signs of slowing down. With plans for more interviews, enhanced video content, and deeper explorations of Turkish culture, the series is set to become a flagship for the airline’s content marketing strategy. Future episodes will continue to offer a balance of practical travel insights and immersive storytelling, ensuring that whether listeners are planning their next journey or simply dreaming of faraway places, Widen Your World  will be their guide. Episodes exploring off-the-beaten-path destinations, eco-tourism initiatives, and even behind-the-scenes glimpses into Turkish Airlines’ sustainability efforts are on the horizon, promising to enrich the podcast’s content offering even further. Turkish Airlines Series  stands out for its authenticity, quality, and emotional resonance. It does more than promote destinations—it captures the heart of what it means to travel: the thrill of discovery, the beauty of connection, and the stories we carry home. With every episode, Turkish Airlines reminds its listeners that the world is vast, beautiful, and waiting to be explored. And sometimes, all it takes is a pair of headphones and a little imagination to begin the journey. Listen / Watch on Spotify Listen on Apple Podcasts Listen on Castbox

In collaboration with the Intel AI Marketing team, we are proud to be the creative and production partner behind Intel on AI—a podcast series and YouTube channel that brings together leading voices from across the tech ecosystem to explore the ever-evolving landscape of artificial intelligence. With Season 5 now live, the series continues its mission of connecting audiences with the people, stories, and innovations shaping the future of AI. Telling the Story of AI in Real Time As AI shifts from experimental to essential, Intel recognized the need to not only build the infrastructure powering this transformation, but to also showcase the minds and organizations driving real-world implementation. The Intel on AI podcast was designed to do exactly that: offer a platform for candid, timely conversations between industry leaders who are not just observers of AI, but active participants in its advancement. Busylike stepped in to help Intel execute this vision with a clear focus on content strategy, narrative structure, guest curation, and high-end production. Season 5 reflects this alignment—it’s not just a series of interviews, but a narrative journey through the impact and promise of AI across industries. Designing for Reach, Relevance, and Engagement This podcast isn’t just another content piece on the AI bandwagon—it’s built for decision-makers who want substance over hype. To reach this audience, Intel on AI was produced in a dual-format approach. Each episode is filmed for YouTube and also distributed as an audio podcast, giving the series a wide digital footprint while preserving the intimacy and immediacy of a conversation. From healthcare to telecom, enterprise IT to device design, the episodes spotlight individuals and organizations applying AI in high-stakes, high-impact environments. The guest lineup was intentionally curated to offer a range of perspectives—from startup founders and corporate executives to technologists and policy advisors. These aren’t abstract discussions; each guest brings concrete examples of AI strategies and solutions in the field. Season 5: AI in Action, Across Every Industry Season 5 of Intel on AI kicks off with a clear focus: to spotlight real-world applications of artificial intelligence through the voices of leaders who are making it happen. Across this season, guests unpack how AI is influencing not just the future, but the now—transforming how companies operate, how decisions are made, and how innovation scales. From enterprise networks and intelligent devices to healthcare breakthroughs and edge computing infrastructure, each episode provides a window into where AI meets reality. Two standout conversations capture this spirit especially well. In the opening episode, Luke Norris, founder and CEO of KamiwazaAI, challenges conventional thinking with a bold idea: that the computing stack built for the internet era won’t support the future of AI. As he explains, we’ve reached an inflection point where traditional infrastructure is too rigid, too slow, and too costly for the kinds of workloads AI demands. Luke walks through what it means to adopt an AI-native mindset—one that views infrastructure not as a bottleneck, but as a strategic advantage. The conversation touches on startup agility, hardware-software co-design, and the opportunity to rethink how businesses scale intelligence from the ground up. Another memorable episode features Peter Shen, Head of Digital and Automation at Siemens Healthineers. In this discussion, Peter offers a rare look into how AI is actively reshaping clinical workflows and diagnostics—from the use of multimodal AI in medical imaging to deploying edge solutions in hospitals around the world. He discusses the real barriers healthcare systems face—like data interoperability and the regulatory frameworks surrounding AI-enabled devices. Peter also shares his perspective from the global stage, including his presentation at CES and his testimony before Congress. The result is a grounded, insightful take on how AI can improve patient outcomes when deployed with purpose and precision. These episodes, along with the rest of the season, reflect a recurring theme: AI is no longer just a buzzword—it’s becoming core infrastructure. And the leaders featured on Intel on AI aren’t just talking about the future. They’re building it. Intel on AI key visual Production with Purpose Behind the scenes, Busylike managed the full spectrum of production and creative services. From shaping interview questions and managing logistics to editing, motion design, and publishing, the process was optimized for both storytelling and scalability. Each episode is tailored for digital-first consumption, with companion assets that include social-friendly clips, SEO-optimized YouTube descriptions, and promotional support across Intel’s LinkedIn and marketing channels. What makes the show stand out is its tone—conversational, smart, and never overly technical. The aim was to create something that resonates with CIOs, CMOs, product leaders, and innovation officers who want to understand not just what AI is, but what it does in the real world. Early Impact and Growing Momentum While the season is still ongoing, the impact has already been felt. Viewership on YouTube has seen a marked increase over previous seasons, especially in regions like North America, EMEA, and APAC. Social engagement is also up, thanks to guests actively sharing episodes within their networks, adding additional reach and credibility to each conversation. Audience feedback shows that the podcast is resonating particularly well with senior-level professionals in tech, marketing, and operations—exactly the demographic Intel set out to engage. Perhaps most importantly, the content is creating value beyond the podcast itself. It’s being used in sales enablement, internal training, and as a showcase of Intel’s ecosystem partnerships and thought leadership. Looking Ahead New episodes will continue to roll out in the coming months, with future topics exploring AI’s role in cybersecurity, robotics, and ethical governance. Each episode will follow the same storytelling-first formula: real people, real technology, real impact. For Intel, the Intel on AI podcast is more than just a marketing channel—it’s a platform for influence, connection, and insight. And for Busylike, it’s an opportunity to help shape the way AI stories are told—authentically, intelligently, and with purpose. You can watch Intel on AI on the Intel YouTube Channel or listen on your favorite podcast app. New conversations are on the way—and the future of AI is just getting started. Intel on AI YouTube Channel Listen / Watch on Spotify Listen on Apple Podcasts

In partnership with the Snowflake Analytics Marketing team, Busylike has been proud to help bring Snowflake’s voice to life across social platforms—transforming complex ideas about data, AI, and analytics into engaging, mobile-first storytelling. Our collaboration focuses on producing social-first video content that amplifies Snowflake’s thought leaders and showcases the brand’s innovation culture. By designing content that performs natively across LinkedIn and other executive channels, we’ve helped Snowflake strengthen its presence and relevance among data professionals and business decision-makers around the world. From Data to Dialogue: Making Analytics Human The Analytics Marketing Department at Snowflake drives conversations around one of the most dynamic topics in tech: how data fuels transformation. To support that mission, Busylike partnered with the team to design a content strategy that makes complex data narratives simple, visual, and human. Each piece of content—whether a quick executive insight or a highlight from Snowflake’s AI School—was crafted with clarity and motion in mind. These videos aren’t just static updates; they blend interviews, key visuals, and subtle animation to bring Snowflake’s perspective on AI, analytics, and data strategy to life in a way that feels personal and easy to consume. Mobile-First by Design Every asset produced was built for the modern attention span. We optimized video content for vertical viewing, ensuring that Snowflake’s stories look and feel native on mobile platforms. Clean motion graphics, dynamic text treatments, and precise editing keep viewers engaged while highlighting key takeaways—whether it’s about data innovation, product evolution, or the people behind the platform. This approach not only increased content completion rates but also improved shareability across executive LinkedIn channels, helping Snowflake’s leaders reach a broader and more relevant audience. Building a Digital Presence for the Data-Driven Era Our ongoing content series covers three key storytelling pillars: Data and AI Innovation  – Insightful clips that break down how Snowflake enables modern analytics and machine learning workflows. Product and Platform Highlights  – Short, visually engaging stories that showcase new features, partnerships, and customer success. Life at Snowflake  – Authentic, culture-driven videos spotlighting the people, values, and initiatives that make Snowflake thrive, including the AI School  series. Together, these streams of content work in harmony to elevate Snowflake’s voice as both a product leader and a trusted educator in the AI and data space. Early Impact Since the launch of the new content approach, Snowflake’s executive social presence has seen a significant increase in engagement—particularly in key regions across North America and EMEA. The mobile-first videos have driven stronger click-through and completion rates, while comments and shares from peers in the industry have amplified visibility and credibility. The combination of smart storytelling and tailored motion design has helped Snowflake stand out in a crowded digital landscape, positioning its leaders as both innovators and educators in the evolving world of AI and analytics. Looking Ahead Busylike continues to partner with Snowflake’s Analytics Marketing team to explore new ways of bringing data stories to life. Future content will expand into emerging themes like responsible AI, data governance, and the next frontier of data-driven business intelligence—always with the same guiding principles: clarity, creativity, and connection. For Snowflake, this collaboration isn’t just about content—it’s about community.And for Busylike, it’s about helping shape the future of how data stories are seen, shared, and understood.