Use Cases for AI in Content Development

AI That Works With Me: 10 Use Cases & The Tools I Trust "What AI tools do you use day-to-day to get more done?" I get this question 5+ times every week, usually in LinkedIn DMs. Therefore, now's a good time to share my current AI stack in writing. As of mid-Feb 2025, here are 10 common use cases and the tools I use to accomplish them: 🔍 RESEARCH: 1. Quick answers: Perplexity Pro (my Google replacement 95% of the time) 2. Going deep: Google's Gemini 1.5 with Deep Research (for consulting-grade analysis) 🎯 SYNTHESIZE: 3. Newsletter insights: Relay.app + OpenAI's GPT-4 Mini (the So Whats) 4. Email prioritization: Relay.app and Meta's Llama 3.1 Sonar (must-replies) 🧩 SHAPE: 5. Brainstorming: Anthropic's Claude 3.5 Sonnet (developing ideas) 6. Structuring: also Claude 3.5 Sonnet (organizing ideas) ✍️ CREATE: 7. Image creation: OpenAI's ChatGPT 4o (visualizing ideas) 8. Long-form writing: Anthropic's Claude 3.5 Sonnet (posts and essays) 🎤 TALK (the layer that enhances everything above): 9. Constant banter: OpenAI's ChatGPT 4o Advanced Voice Mode (thinking partner) 10. Voice capture: Wispr Flow (we talk faster than we type) In ten upcoming posts, I'll break down each of these use cases and tools, sharing specific workflows, examples, and lessons learned. Consider this first post as the table of contents for an ongoing series on my AI-Forward playbook. Disclaimer: In 2025 AI-land fashion, I'll likely replace some of these tools with even better options by the time I write about them. That's the pace of advancements these days, which is 80% exhilarating and 20% exhausting - exhilarausting? - to keep up with. #AIThatWorksWithMe #AIForward

If you're still using AI to "write content", you're already behind. The real players aren't prompting. They're building ecosystems. Let me show you the difference (and how to actually win with AI)👇 Most people think AI = better content 💀Wrong AI = better strategy If you know how to use it. If you're using AI just to write blogs, you're in a race to the bottom. If you're using AI to research, position, and execute? You’re in a league of your own. Most AI content fails because it’s: ❌ Generic ❌ Data-starved ❌ Easily copied Everyone's writing “Top 10 Tools” posts. No one's doing deep research into what those tools are missing. That’s where the opportunity lives. Here's how to use AI like a strategist: ✅ Do competitive analysis ✅ Extract pain points from Reddit, YouTube, and reviews ✅ Build out buyer journeys ✅ Turn one insight into 10 pieces of content ✅ Own a positioning no one else is touching Example: Instead of prompting ChatGPT to “write a LinkedIn post…” → Ask it to summarize common frustrations from real users in your industry You’ll get content that speaks to pain, not filler. Use AI to find gaps. Scrape top-ranking blog posts. Ask AI: “What are these articles missing?” Find the blind spots. Then own them. That’s your content moat. That's what separates you from your competitors. Use AI to map content to your funnel: Top of funnel (ToFu): → Scan social for trending problems Middle (MoFu): → Analyze customer reviews for objections Bottom (BoFu): → Generate custom nurture sequences based on behavior Want to build a real AI-powered content engine? Try this: 🧠 A tool that tracks competitor SEO shifts 🎯 A script that repurposes blogs into high-performing LinkedIn carousels 📊 A dashboard that monitors what’s trending before it hits your feed That’s not content. That’s infrastructure. What I'm saying is that AI isn't here to replace you. It's here to multiply you. The winners won't just use AI to just write faster. They'll use it to think deeper. Move quicker. And execute harder. If this hit, follow for more breakdowns on branding, tech, and unorthodox growth moves for first-gen founders.

Using AI to generate content is like taking your Rolls Royce or your Bugatti to the grocery store. Yes, it can do that. It will get the job done, and done in style. But that's not even remotely close to what it's capable of. At this year's MarketingProfs B2B Forum (#mpb2b), I suggested a few other use cases that B2B marketers should think about using generative AI for. 1. Take the last 30 days of sales calls from your call management system, have AI transcribe them, and then have generative AI tools like ChatGPT generate an analysis of what objections are being raised on sales calls and how successfully your team is addressing them. If the calls aren't going well, use generative AI to then help build better call scripts for your team. 2. Take screenshots of the 60,451 MarTech tools you're using in your organization and their dashboards, toss all the screenshots into a generative AI tool with vision capabilities (ChatGPT, Gemini, Claude) and ask it to organize all your data into a coherent story, a buyer's journey. Then have it suggest where your buyer's journey is falling down, and come up with ideas for fixing it. 3. Take documentation for any channel you're marketing on, from Google's Search Quality Rater Guidelines to Meta's System Cards, and build an AI app that evaluates your content and campaigns against the way the systems are built. You'll get far better results than prompting it with generic terms like "Write SEO-optimized copy". Take AI out of first gear and off the green circle trails. It's far more capable than you're using it for. #AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

A fascinating HBR article that provides concrete data on how people are actually using generative AI tools in 2025, and I wanted to share some key insights. What struck me most was the primary use cases that have emerged: 📝 Content creation and refinement remains the dominant application, with professionals across industries using AI to draft, edit, and polish everything from emails to presentations. 🧠 Ideation and brainstorming has become a critical workflow enhancement, with teams using AI as a thought partner to generate novel approaches and overcome creative blocks. 🔍 Information synthesis is transforming how we handle the information overload, with AI helping to summarize research, extract insights from complex data, and connect dots across disparate sources. 👨💻 Coding assistance has matured beyond simple autocompletion to helping developers architect solutions, debug complex issues, and even handle full feature implementations. What I found particularly interesting was the shift from novelty use cases toward integration into core workflows. The tools that are winning aren’t standalone “AI solutions” but rather intelligent capabilities embedded directly into the software we already use daily. What’s your experience? Are you using generative AI in ways that align with these findings, or have you discovered unique applications in your field? https://lnkd.in/eHC75ikZ #GenerativeAI #Productivity #FutureOfWork #AITrends2025

5 AI prompts every marketer should use in 2025: 92% of marketers say AI has already impacted their roles, but fewer than half feel clear on how to use AI. (HubSpot's 2025 State of Marketing Report) 5 AI prompts you can use today: 1️⃣ Blog posts: "Generate 25 interesting headline ideas for an article about [topic] for [audience]. Explain why each option might perform well." Pro move: Once you find the perfect headline: "Write a first draft of the article with [these talking points]." Why it works: Content creation is one of the top AI use cases for marketing. It’s far easier to make progress when you have a draft to respond to (rather than staring at a blank page). —— 2️⃣ Market research: "You're about to launch [new product]. Identify 5 distinct customer personas, including their demographics, pain points, objections, daily challenges, and the exact language they use when describing problems this product solves." Pro move: “For each persona, suggest 3 campaign ideas that would resonate deeply with them." Why it works: Detailed personas help you reach key demographics effectively. For example, ~74% of marketers are targeting Millennials, with growing focus on Gen Z (33% B2B, 39% B2C). AI can give you market research on that exact persona. —— 3️⃣ Customer feedback: "Analyze these customer reviews to identify: 1) recurring themes, 2) pain points, 3) competitive advantages, and 4) unexpected use cases. Format as a brief report with actionable insights.” Pro move: “Come up with 5 ways to engage our top customers in Q2." Why it works: 96% of marketers reported that personalized experiences increased sales. Understanding customer feedback is essential for personalization. —— 4️⃣ Ad creation: "Develop 4 unique concepts for an ad campaign [on Google, LinkedIn, etc.] that will target customers in the following [locations] and [firmographics] who are trying to solve [these pain points]." Why it works: Paid social media content is the 2nd highest ROI marketing channel in 2024 (for B2B and B2C brands). It’s critical to come up with fresh content often. 5️⃣ Competitor analysis: "Analyze the last 10 campaigns from each of these competitors: [list 3-5 competitors]. Identify their messaging themes, content types, engagement patterns, and apparent strategy.” Pro move: “Then suggest 5 unique angles we could take to differentiate ourselves while addressing similar audience needs." Why it works: 92% of marketers plan to maintain or increase investments in brand awareness in 2025. That means competition is getting steeper. Use AI to gain a creative edge. ——— These are just a few ways that AI can be used in marketing. As AI continues to evolve, it will become an even more powerful tool. But it's critical to remember that AI is just that— a tool. It's up to us marketers to use AI effectively and ethically. Read HubSpot’s full 2025 State of Marketing Report here: https://lnkd.in/etQY-vHB #AIMarketing #HubSpotPartner #MarketingPrompts

It all begins with a question. I asked our Google Cloud Consulting team... 1.) How are they using AI to amplify their unique strengths and passions in their daily work, and 2.) ideas on what we could develop using AI to free them up to focus on the aspects of their jobs they are best equipped for—and truly enjoy doing. 🌟 The response has blown me away! 🤯 In just a few weeks, the team has shared over 100 ways they are already using Google AI to enhance their unique contributions, and close to 100 ideas on how we can develop AI solutions to remove repetitive or less fulfilling tasks, enabling them to double down on the work that excites them and delivers the most value to our customers. 🚀 Here are the top 10 use cases—curated with insights from Gemini, of course—that highlight how AI can help our team do more of what they love and excel at. Click the … in the upper right hand corner to save this post for your own teams AI journey. 1. Document Analysis and Generation: AI is heavily used for analyzing and generating various documents, including Statements of Work (SOWs), Product Requirements Documents (PRDs), contracts, proposals, and reports. 2. Meeting Enhancement and Summarization: Gemini is utilized to transcribe meetings, summarize discussions, extract action items, and generate structured reports from meeting content. 3. Code Generation and Review: AI assists in generating code snippets, skeleton scripts, and even complete applications based on provided requirements. 4. Customer Insights and Analysis: NotebookLM and other AI tools are used to analyze data, including earnings reports, public information, and meeting notes, to identify growth opportunities and assess customer health. 5. Knowledge Management and Retrieval: AI facilitates the organization and retrieval of information from various sources, such as internal documentation, playbooks, and research claims. 6. Proposal and RFP Response Automation: AI streamlines the process of responding to RFPs by generating proposals, scoping questions, and highlighting risks from provided inputs. 7. Content Creation and Communication: AI is used to generate various types of content, including blog posts, newsletters, learning materials, and presentations. 8. Learning and Development: AI supports learning and development by creating study guides, generating personalized learning paths, and providing answers to curriculum questions. 9. Automation of Repetitive Tasks: Tools like Botz are used to automate repetitive tasks, such as email drafting, report creation, and data analysis, improving overall efficiency. 10. Enhanced Data Analysis and Visualization: AI tools are used to generate custom dashboards, perform large-scale data analysis, and translate spreadsheet data into presentations. 📸 A glimpse into our North America Summit with our customer success team talking about AI4Us