AI in Creative Industries

Mark Zuckerberg just outlined Meta’s bold vision for the future of advertising in a new Stratechery interview—and it’s unlike anything we’ve seen before. Here’s the punchline for marketers: 1. The “Ultimate Business Agent” “Here’s my goal. Here’s my budget. Go get it.” That’s where Meta is heading. No creative. No targeting. No measurement. AI handles the entire funnel—automated, optimized, and outcome-based. 2. Creative Built by AI Meta is approaching the ability to auto-generate ad creatives at scale. Want more control? Upload your own. But increasingly, you won’t have to. 3. Targeting Is Basically Solved Zuckerberg: Meta’s system finds high-intent audiences better than humans. Manual targeting is increasingly discouraged. 4. Results-Based Billing From impressions → outcomes. Measurement is now embedded, not bolted on. But Here’s the Caveat: AI Without Strategy Is Just Noise at Scale AI makes decisions based on patterns—not business context, brand nuance, or customer empathy. Let it run unsupervised, and you risk: - Wasted spend on false positives - Brand-damaging creative hallucinations - Short-term optimization that kills long-term equity The real winners? Not just businesses who use Meta’s tools—but those who understand how to guide them. Because even the smartest AI still needs strategic guardrails. Otherwise, you’re automating mediocrity. If you’re a performance marketer, your job isn’t going away—it’s evolving. You won’t be setting bids or building audiences. You’ll be crafting positioning, auditing outputs, and fine-tuning the machine. The future of ads is AI-assisted. The future of great ads? Still very human.

I watched the State of the Union, but found the State of the Bots more engaging. The State of the Bots is a report published by TollBit CEO Toshit Panigrahi that assesses the volume and impact of web scraping and generative AI on publishers. It illustrates the potentially devastating impact of the combination of extracting information from web sites and reformulating it into easy-to-digest answers for ChatGPT. According to the report: –The volume of web scraping doubled between the third quarter and fourth quarter of 2024. –During that same time, the amount of unauthorized web scraping increased by more than 40%. –Even when blocked, apps like Perplexity used unidentified agents to scrape sites. All that adds up to one devastating conclusion: “AI chat bots on average drive referral traffic at a rate that is 96% lower than traditional Google search.” In plain English that means online publishers can expect to receive 96% fewer clicks on their web sites in a new world where most internet queries are answered using ChatGPT. A friend of mine compared this to the impact of Uber on taxis in New York. Before Uber, taxis were plentiful and cheap. Afterwards they largely disappeared. Uber may be convenient, but its more expensive and it wiped out the value of owning a taxi license. In the case of publishers, it’s not clear how the new system would let them generate revenue to pay writers since the current ecosystem for advertising-supported content depends on traffic and that comes from Google. The alternative is to go behind a paywall. Either way, the result is less, reliable and high-quality information available to the public. Tech companies have generally balked at compensating publishers for content – either to be used in training models or to be accessed as a reference to answer questions. Analyst Matthew Scott Goldstein (msg) calls it “The Greatest Heist on Earth.”  He wrote: “Powerful tech companies, from social media giants to artificial intelligence startups, are quietly siphoning off the value from content creators across all industries.” Goldstein says safeguarding copyright is essential and steps need to be taken now. “Once AI models are trained on stolen content, the damage is irreversible. The longer this goes unchecked, the harder it will be to claw back rights.” It’s possible some of the damage will be mitigated by new search designs Google is unveiling which it says will make it more attractive for people to click through to web sites. What the State of the Bot report makes clear is that that future is coming fast.

An Oxford study just confirmed what most of us have been saying all along: AI-generated ads can outperform human-made ones, but only when they don't obviously look AI-generated. The secret? Human refinement. The best marketing campaigns aren't purely AI-driven or entirely human-made. They're like pizza. Dough alone is just bread, toppings alone is chaos. The magic happens when everything works together. Want to collaborate with AI effectively? 1) Use AI for rapid ideation, humans for emotional depth Take your worst-performing ad copy and feed it into ChatGPT or Claude with this prompt: "Rewrite this to evoke [specific emotion: frustration, curiosity, nostalgia]. Use conversational language. Surprise me." It'll give you variations you'd never think of. Then your human brain picks the best concept and refines it until you think: "We'd never have written this ourselves." 2) Let AI spot patterns, humans craft the story AI's really good at combing through customer feedback, support tickets, and social mentions for trends. But humans make those insights into stories that actually matter. Say AI finds that most support tickets mention setup frustration. Humans craft that into: "Setup shouldn't feel like assembling IKEA furniture blindfolded." 3) AI scales the testing, you choose the winners Generate multiple variations with AI, but you decide which ones are worth spending money on. AI can create 50 headlines in minutes, your judgment tells you which 3 are worth testing. 4) You set the rules, AI fills the gaps Define your brand voice, values, and no-go zones. Then let AI work within those boundaries to fill content calendars, generate product descriptions, or create email variations. Platforms are making this easier: - Microsoft’s Ads Studio has AI-powered creative tools built into campaign workflows - Google Cloud rolled out AI marketing tools for personalized experiences - Or start simple with ChatGPT/Claude and the prompt above Stop thinking AI vs. humans. Start thinking AI + humans. Your move: This week, pick your worst-performing content. Run it through AI with a specific emotional prompt. Refine the best result with your gut instinct. That's how you make sure your marketing isn't just dough or just toppings, but complete, irresistible pizza. P.S. I'm team pineapple on pizza 🍕 + 🍍 = 🤤 (Sorry to my Italian friends! At least there's no ketchup involved... 😂) #hicm #AI #AIinAdvertising

I keep a simple rule for tools. Match the job, not the hype. Over the past months I tested dozens of AI products across my daily workflow on The Ravit Show. Research. Writing. Slides. Data analysis. Coding. Voice. Design. Video. Hiring. Dev tooling. I pulled the keepers into a one-page guide so my team can grab the right tool fast and move on with the work. How to use this carousel 1. Start from the job you need this week. 2. Pick one tool. Give it a 30 minute test with your real task. 3. Write down what worked and what did not. 4. If it saves time, keep it. If it adds friction, drop it. A few stacks I reach for • Agents and workflows: LangGraph or CrewAI when I need orchestration without heavy setup • Docs and slides: Tome or Gamma to go from notes to a deck quickly • Data insights: Akkio or DataSquirrel to turn CSVs into answers • Code help: Codeium or Tabnine for quick refactors and tests • Voice and video: ElevenLabs for voice, Runway or Pika for fast visuals • LLM app plumbing: Langfuse to trace, PromptLayer to manage prompts The full list with categories is in the carousel. Save it for your team and update it as your needs change. ---- ✅ I post real stories and lessons from data and AI. Follow me and join the newsletter at www.theravitshow.com

3 AM Burps & AI Surprises: My New Creative Process? It's 3 am. The rhythmic patting on the back, the softest of burps, and finally, that moment of stillness before gently placing our little one back in the crib. In the quiet darkness, a thought sparked: let's see what AI can do. So, fueled by lukewarm tea and sleep deprivation, I asked Gemini to create some campaign visuals for a luxury hand cream brand I just conjured up - "divyam" (clearly, 3 am isn't my creative peak!). Honestly? What came back blew my mind. (See the images below!) The sheer speed and visual quality are astonishing. Implications for the Ad Industry: Rapid Prototyping & Concept Exploration: Imagine the possibilities for brainstorming and quickly visualizing campaign ideas. Forget lengthy photoshoots for initial concepts – AI can generate a multitude of options in minutes, allowing for faster iteration and client feedback. Democratization of Visual Content: While the human creative eye and strategic thinking remain crucial, AI tools can empower smaller businesses and individuals to create compelling visuals without the immediate need for extensive resources. Focus on Strategy & Brand Narrative: As AI handles some of the heavy lifting in visual creation, creative professionals can focus more on the core strategy, brand storytelling, and the emotional connection with the target audience. Personalized & Dynamic Advertising: The potential for generating highly personalized ad creatives based on user data could become even more powerful and efficient. The Evolving Role of the Creative Team: The skills required in the ad industry will continue to evolve. Understanding and leveraging AI tools will become increasingly essential, shifting the focus towards curation, strategic direction, and ensuring brand consistency. This little 3 am experiment has certainly given me food for thought. The creative landscape is shifting, and the tools at our disposal are becoming incredibly powerful. It's not about replacing human creativity, but augmenting it in ways we're only beginning to understand.

Mark Zuckerberg just outlined a future where Meta's AI handles everything from creative generation to campaign optimization to purchase decisions. His vision: businesses connect their bank accounts, state their objectives, and "read the results we spit out." The technical architecture he's describing would fundamentally reshape how advertising technology works. But there's a critical flaw in this approach that creates an opportunity for the next generation of advertising infrastructure. The trust problem isn't just about measurement transparency—though agency executives are rightfully skeptical of platforms "checking their own homework." The deeper issue is institutional knowledge transfer and real-time brand governance. Enterprise brands have decades of learned context about what works, what doesn't, and what could damage their reputation. This isn't just about brand safety filters. It's about nuanced understanding of seasonal messaging, competitive positioning, cultural sensitivities, and customer journey orchestration that can't be reverse-engineered from campaign performance data alone. If AI truly automates the entire advertising stack, brands will need their own AI agents—not just dashboards or approval workflows, but intelligent systems that can negotiate with vendor AI in real-time. Think of it as API-level conversation between two AI systems where the brand's AI has veto power over creative decisions, placement choices, and budget allocation. This creates fascinating technical challenges: How do you architect AI-to-AI communication protocols that maintain brand governance while enabling real-time optimization? How do you build systems that can incorporate institutional knowledge without exposing competitive advantages to vendor platforms? We're talking about building advertising technology that functions more like autonomous diplomatic negotiation than traditional campaign management. For platform companies pushing toward full automation, the question becomes whether they're building systems that enterprise clients can actually trust with their brands and budgets. For independent technology builders, there's an opportunity to create the middleware that makes AI-powered advertising actually viable for sophisticated marketers. The future of advertising isn't just about better algorithms—it's about building trust architectures that let those algorithms work together.

Customized Production Planning Develop Generative AI models for customized production planning, considering demand fluctuations, resource availability, and market trends, leading to agile and adaptive manufacturing processes. Conquer Demand Fluctuations with Generative AI Planning! The manufacturing landscape is ever-changing. Generative AI offers a powerful tool to adapt your production plans in real-time, ensuring you meet fluctuating demands and stay ahead of the curve. Imagine: AI systems that analyze market trends, resource availability, and customer demands to generate dynamic and optimized production plans. > Stay Agile in a Shifting Market: Generative AI can quickly adjust production plans based on sudden changes in demand, allowing you to capitalize on new opportunities and minimize the impact of market fluctuations. > Optimize Resource Allocation: AI considers your available materials, equipment, and workforce capacity when generating production plans, ensuring efficient resource utilization. > Reduce Inventory Waste: By accurately predicting demand, you can minimize overproduction and avoid costly inventory holding costs. The benefits of Generative AI for customized production planning are clear: * Enhanced Agility & Responsiveness: Adapt your production quickly to changing market conditions. * Improved Resource Efficiency: Optimize resource allocation and minimize waste. * Reduced Inventory Costs: Produce only what you need, when you need it. Generative AI empowers agile and adaptive manufacturing processes. Ready to transform how you plan your production? #manufacturing #generativeAI #productionplanning

AI is one of the most discussed topics in my artist management and music entrepreneurship courses at Long Island University’s Roc Nation School of Music Sports & Entertainment—and for good reason. Across the creative and corporate landscapes, AI is transforming how music professionals operate and how creators bring their art to life. The numbers tell a compelling story. A recent Ditto Music study revealed that 60% of independent musicians in 2023 are already integrating AI into their music projects: 🎵 77% use it for album artwork. 🎵 66% for mixing and mastering. 🎵 62% for music production. 🎵 47% for songwriting On the corporate side, the adoption is just as significant. According to Gallup, 93% of Fortune 500 organizations have incorporated AI to enhance business practices. However, the rise of AI comes with its own set of challenges for the music industry. For example, AI startups Suno and Udio recently admitted to using copyrighted recordings from major labels without permission, defending their practices under the "fair use" doctrine for training AI models. This debate underscores the legal and ethical complexities AI brings to the table, especially in industries like music that deeply value creativity and ownership. These very issues were highlighted in my recent fireside chat with EMPIRE President Tina Davis as part of the Roc Nation Speaker Series. We explored two critical questions shaping the future of AI in music: 1️⃣ Will AI serve as a catalyst for artists to expand creative boundaries, or might it contribute to a decline in artistic innovation? 2️⃣ How can AI systems establish equitable compensation frameworks to ensure creators are fairly remunerated for their contributions, particularly when their work is utilized in training these technologies? As I prepare to join my former professor NYU Steinhardt School of Culture, Education, and Human Development Howie Singer's Music Data and Analytics class today to discuss the latest developments in AI and music, I’d love to hear your perspective. How do you think AI will reshape the music industry in the years ahead? Any predictions for 2025 that I can share with students? Drop your thoughts below ⤵️

Call me the fun police or whatever, but Hayao Miyazaki didn’t spend his entire life cultivating a distinct artistic identity so that OpenAI could reduce decades of his discipline and integrity to meme fodder. It’s a shame how easily people abandon principle just to feel included. I really don’t understand this vitriol against artists (and believe me, I’ve been facing it all day). Is it a lack of art education in school? Jealousy? Did one artsy kid bully you in grade school? And no, nobody is gatekeeping creativity. A box of pencils and paper is like 6 bucks and you can learn for free from so many places. Stop being lazy. But here’s the thing: the music industry is also playing along with its mixed messaging. The big talk about how “AI is good, creativity is democratized” is just noise when the real problem is ignored. What’s happening to Miyazaki right now is also happening to the music industry. The AI tipping point is here, and the music industry isn’t ready. (my new article for Music Ally: https://lnkd.in/gq9BVvDT) We’ve gone from years of progress to weeks of radical change. Just last week: - Google's Gemini API and Studio – Giving content thieves the perfect toolkit to rip off creators. - Gemini 2.0 – A piracy engine disguised as a multimodal AI beast generating audio, images, videos, and more, all from a single model. Watermark removal, voice cloning, deepfake tracks, done with terrifying ease. - Cartesia Sonic-2 – Cloning any voice with just three seconds of audio, faster and more accurately than anything before. - China’s Zuchongzhi-3 Quantum Computer – A 105-qubit monster making Google's best supercomputer look like a toy. - Agentic AI – Systems like Manus AI that don’t just follow instructions but make decisions, create music, run marketing campaigns, and interact with fans, entirely on their own. AI models are only getting smaller, cheaper, and ridiculously powerful. Instead of asking if AI will change the industry, we should be asking: What will be left of the industry when AI finishes its transformation? My new article for Music Ally digs deep into how AI and quantum computing are smashing through our current systems of distribution, monetization, copyright protection, and artistic creation. And here’s the truth: The real danger isn’t AI itself, but how unprepared the industry is to adapt. Read the article to find out: https://lnkd.in/gq9BVvDT And thank you to Music Ally for giving me the space to talk about this, and to Joe Sparrow for his precious editing. #AI #GenerativeAI #MusicIndustry #CopyrightInfringement #CreatorsRights #InnovationVsExploitation #MusicBusiness #AIRegulation #MusicCreators

I built an EV brand using only AI. Here's how I did it. Meet AR4™ — a speculative AI-enabled EV brand entirely designed using AI. From the name to the identity system, vehicle form language, proprietary materials and the visual world—it was all built through a creative partnership between human vision and machine intelligence. This wasn’t a branding exercise. It was an R&D experiment—a self-initiated project to push my skills in the emerging field of AI design and explore what happens when intuition meets automation. 🧠 How I Built AR4™ Using AI: 01 → Naming + Brand Concept Used AI to explore hundreds of naming conventions grounded in performance, geometry, and material innovation. Landed on AR4™—short, mechanical, elemental. 02 → Design Ethos + Form Language Built a design system rooted in “Forged Geometry,” using AI to iterate vehicle silhouettes, spatial relationships, and material responses. Prioritized form over style—every surface had to earn its place. 03 → Material Innovation Imagined Aero-Titanium™ and Electrive™ battery systems—fusing AI-generated material science insights with conceptual design fiction. Designed with a raw, unpainted metallic aesthetic to reinforce the idea of strength through process. 04 → Brand Worldbuilding Developed Fieldspace™, a nature-reactive workspace, and AeroCarbon™, a carbon-capturing air-filtration system. Crafted environments and landscapes using Midjourney to visualize a fully immersive, elemental brand world. Why? Because I believe the next era of creative work will be shaped by those who learn to collaborate with intelligence—not just command it. AR4™ doesn’t aim to feel nostalgic or futuristic. It feels inevitable — a designation from a future that already exists, forged in material, not marketing. → Built from zero using AI. → Rooted in material intelligence, geometry, and restraint. → Forged, not styled. 👉 Case Study https://lnkd.in/gbmdjXVN #AI #CreativeDirection #SpeculativeDesign #BrandIdentity #AR4 #ElectricVehicles #FutureOfDesign #CreativeTechnology #AIDesign #GenerativeDesign #DesignSystems