Today, we’re bringing you the latest in AI-powered marketing and business strategies. Here’s what’s inside:
🚨 AI Top Story: Learn why Rolling Stone and Billboard’s parent company is taking Google to court over AI Overviews.
🔧 AI Tool Of The Week: See how Spara uses AI agents to qualify leads, answer questions, and book meetings before reps even step in.
🌟 Creator Spotlight: Emilia Möller shares techniques on how to make one blog post multiply into eight AEO signals to boost visibility across AI search.
💬 Killer Marketing Prompt Of The Week: Turn a single keyword into dozens of natural-language questions and uncover new AEO opportunities your content can target.
🎥 YouTube Resource Of The Week: How to track, test, and scale visibility across ChatGPT, Gemini, Claude, and more.
Google Hit With Lawsuit Over AI Search Summaries
Publishers Push Back On Google’s AI Search Tool
Rolling Stone and Billboard aren’t usually in the same headline as Google, but this week they are. Their parent company, Penske Media, has filed a federal lawsuit claiming Google’s new AI Overviews are siphoning off their work. The allegation is straightforward: Google’s search feature pulls reporting from Penske titles, rewrites it into AI-generated summaries, and then serves those summaries directly to users at the top of search results. Instead of clicking through to the publisher, readers get the gist without ever leaving Google.
According to the filing, around one in five Google searches tied to Penske’s content now triggers an AI Overview. The result? A steep drop in traffic and a cut of more than one-third in affiliate revenue since late 2024. That’s not pocket change for a publisher, and it shows why this fight matters.
Google, for its part, defends the feature. The company insists that AI Overviews improve the user experience, broaden discovery, and actually send traffic to a wider range of sites. But with a 90% market share in U.S. search, it’s not hard to see why publishers feel backed into a corner. The lawsuit argues that Google’s dominance leaves them no choice but to accept these overviews or risk vanishing from search altogether.
If this feels familiar, it should. In our last newsletter we highlighted how Perplexity has started paying publishers for content that’s cited in its AI answers. That’s a very different approach from Google’s, and it underscores just how unsettled the rules of this new search economy really are. One company is testing compensation, the other is facing lawsuits.
It’s tempting to see this as just a publishing industry problem, but marketers should be paying close attention. If AI can repackage journalism and keep the clicks, the same can happen with your brand’s blog posts, guides, and whitepapers. For years, the playbook was simple: create valuable content, rank high in search, and let the traffic fuel leads and sales. That model looks shaky if the answer gets lifted and displayed before anyone visits your site.
So what now? First, don’t assume search traffic is guaranteed. Audit where your visitors come from and watch how summaries might already be reducing clicks. Second, focus on content AI can’t easily flatten — proprietary data, interactive experiences, community-driven conversations, and creative work people actively seek out. And finally, double down on owned channels like newsletters and events where you control the distribution, not Google.
The lawsuit will take years to wind through the courts, but the implications for marketers are immediate. Counting on Google to keep sending traffic is getting riskier by the day. The brands that adapt fastest will be the ones that still reach their audiences even when the search results stop playing fair.
🏛️ OpenAI Releases Official Statement Clarifying Roles of Nonprofit and Public Benefit Corporation - OpenAI outlines how its nonprofit and PBC divide power — useful context for marketers relying on its tools.
🎁 Google Unveils New AI Marketing Tools Ahead of Holiday Season - Google’s new AI features target holiday shopping, showing how automation is shaping peak-season campaigns.
📊 Woolley Marketing: Is your marketing AI investment delivering - A breakdown of four benchmarks: productivity, speed, scale, and quality — to judge if your AI spend is working.
🤖 8 Best AI Chatbot Builders (Pros, Cons, & Pricing Compared) - A side-by-side look at chatbot platforms, weighing features, pricing, and scalability for customer experience.
💬 How Conversational AI is Shifting SMS from a Marketing Tool to a Service Channel - AI is turning SMS into a service channel, not just marketing, expanding how brands connect with customers.
🎯 The Artificially Intelligent Enterprise - AI Isn’t Failing. It’s Maturing—Just Not at Hype Speed.
💡 AI CIO - The ChatGPT Moment
☕ AI Tangle - OpenAI & Oracle Make AI History With a $300B Cloud Deal
📻 AI Confidential Podcast - Days to Seconds: Harnessing Confidential AI Agents
Turning Leads Into Meetings With Spara
Spara is a new AI platform that runs sales agents across chat, email, and voice to capture and qualify inbound leads before they go cold. Its agents respond instantly, greet prospects, ask qualifying questions, answer common inquiries, and book meetings directly into calendars. By handling the early stages of sales, Spara ensures human reps spend more time closing and less time chasing.
Why It’s Gaining Traction
Many teams lose high-intent leads because response times are slow or follow-up is inconsistent. Spara addresses this by making every inquiry actionable, with no gaps in coverage. Backed by a $15M seed round and already working with mid-market and enterprise clients, it is positioning itself as an AI-driven SDR layer that integrates into existing sales workflows.
Key AI Features
Custom-trained models: Each instance is tuned on a company’s brand voice, sales scripts, and qualification rules.
Conversational intelligence: Agents can greet prospects, ask qualifying questions, handle FAQs, and adapt flows dynamically.
Lead qualification & routing with AI logic: Identifies intent, filters by ACV thresholds, and sends high-value prospects to the right human.
AI-powered workflow builder: Lets teams design conversational flows and logic using natural language, not rigid rules.
Multimodal response generation: Can insert supporting assets (PDFs, videos, decks) into conversations where context fits.
Enrichment via AI: Pulls contextual firmographic/demographic data to better inform routing and prep reps
Analytics with AI insights: Surfaces where conversations drop off and suggests optimisations, not just raw reporting.
Emilia Möller - Discover a framework for turning every blog into multiple AEO signals that improve how AI finds, cites, and trusts your brand.
Map Your AEO Wins
This prompt helps you transform a single keyword into dozens of natural-language questions that people might ask AI tools, search engines, or answer engines. By covering a broad spectrum of user intents, from beginner “what is” style questions to highly specific buyer-intent queries, you’ll generate a map of AEO opportunities around your target topic.
It’s designed to go beyond basic keyword expansion and ensure your content plan aligns with how LLMs summarise, cite, and recommend answers.
💡 Best ways to use it
Run the prompt for your core commercial keywords (e.g., “AI marketing platform,” “best project management tool”).
Use the questions to audit your content gaps — which user intents are you missing?
Prioritise questions that overlap with buyer intent + high-value citations.
Feed outputs into your content calendar, FAQ hub, or community strategy.
Prompt:
Act as an expert in Answer Engine Optimization (AEO) and advanced content strategy. Your task is to expand a keyword into a wide range of natural-language questions that real users might ask AI tools, search engines, or answer engines.
Take the keyword: [insert keyword]
Please generate at least 40 unique questions, covering a wide spectrum of user intents. Follow these instructions carefully:
Types of questions to include
Informational: what is, how does it work, why is it important
Comparative: [X vs Y], best options for specific use cases
Transactional/Buyer intent: best tool for [situation], top providers, pricing differences
Troubleshooting: common issues, how to fix, alternatives if [X] fails
Opinion/experience-based: pros and cons, user reviews, trust factors
Emerging/forward-looking: future trends, impact, predictions
Variety and depth
Include short, general questions (e.g. “What is [keyword]?”).
Include long, highly specific questions (e.g. “Which [keyword] platform offers the best integrations for small B2B SaaS companies with under 50 employees?”).
Mix beginner-friendly questions with advanced, expert-level ones.
Output format
Provide as a numbered list (1–40+).
Group the questions into categories by intent (Informational, Comparative, Transactional, Troubleshooting, Opinion, Trends).
Avoid repeating the same intent with slightly different phrasing. Each question must add unique value.
Optimization details
Phrase questions in natural, conversational language as a user would type or say them.
Aim for high diversity across the set — cover as many unique angles as possible.
Ensure some questions directly mirror real buyer research behavior.
Deliver the output in a clear, skimmable formatThe Playbook for Answer Engine Optimisation (AEO)
Explore how brands can track their visibility in AI answers and capture traffic that converts at multiples of traditional search.
Marketers…
