How AI Is Shaping Creative Advertising

If you're using AI for marketing, this is absolutely worth your time. It turns out that most of us may have been doing it wrong. 🫢 Researchers just published a massive study testing AI-generated ads against those created by humans. What they discovered challenges a lot of this early, conventional wisdom and defined some new best practices. 🤔 Here's what they found... ➡️ Asking AI to edit and polish our existing ads is where it performs worst. When researchers tested AI-modified ads, performance actually dropped compared to the originals. ➡️ But, when they let AI create ads from scratch, it was a different story altogether. A 19% improvement in click-through rates (CTR) versus the human versions. AI redesigns of product packaging had even higher performance boosts. 😮 ➡️ Telling customers it's AI-generated drove CTR to the floor, plummeting by 31.5% Transparency requirements are coming, but this validates the pain in performance. This is probably something that the industry needs to figure out fast. So, why do they think all of this happens? ➡️ When AI modifies existing ads, it loses that authentic feel that makes ads work. But creating from scratch, AI generates more emotionally engaging, visually fluent creatives that connect better with people. How could you put this into practice? ➡️ Use AI as your ideation engine at the beginning of the creative process. Generate 20 concepts in minutes, then let humans select and refine the winners. ➡️ For small teams, this is important. You don't need a massive creative department when one person who understands these principles can generate what used to take an entire team. tl;dr - Stop asking AI to fix your ads. Start asking it to reimagine them completely. 😊 This awesome paper is attached below for your convenience. #ai #technology #innovation #creatives #marketing

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

Everyone says AI is killing creativity. That’s not what’s happening. What it’s killing is waste: the endless cycles of guesswork that passed as creative testing. AI is finally making creative testing work the way it always should have. We’re seeing it firsthand at Adquadrant. And it’s changing the entire feedback loop - from ideation to iteration to insight. Instead of simply spending more on ads, your next big performance gain will come from building AI systems that give your team true leverage. So what's actually changing? Let me walk you through what we're seeing work: 1. You can generate creative at ridiculous speed now. Generative AI spits out hundreds of variations (different copy, visuals, hooks, CTAs) in the time it used to take to brief a designer. Instead of agonizing over 20 ads, you're testing 200. And you know what's working before you've finished your coffee. 2. We're getting predictive. There are models now that look at your past data and basically tell you which creatives will bomb before you waste a dollar on them. Tools like CreativeX and VidMob give you scores pre-launch. So you only run the stuff that has real potential, the top 20%, not the whole mess. 3. We finally understand the "why." Computer vision and language models are breaking down what actually makes something convert. Not just "this one won" but why. Which visual choices moved the needle. Which tone hit different. That's the insight that scales. 4. The systems run themselves. This is the wild part: you've got AI agents now that can design, launch, and iterate tests around the clock. Your team gets to do what they're actually good at, strategy, storytelling, the human stuff, while the machines handle the repetitive grind. 5. Everything talks to everything. AI dashboards pull from Meta, TikTok, Google, all of it, and surface patterns you'd never spot manually. Which themes actually drive intent. When your audience gets tired of seeing the same thing. Cross-channel intelligence that used to take a whole team to piece together. Creative testing is no longer a one-off process. It’s a system, and the teams who build it now will be the ones defining what performance looks like next year. 

AI isn’t replacing creativity. It’s expanding who gets to use it. From luxury cars to telecom to personal assistants, Brands are testing what’s possible when AI becomes a creative tool. Not every output is polished. But the willingness to experiment? That’s the real shift. Here are 8 brand campaigns showing how AI can stretch ideas, formats, and interaction: 👇 🚘 Volvo – First AI-Generated Ad Subtle. Elegant. Conceptual. Volvo used AI to visualize simplicity and safety in a fresh, poetic way. https://lnkd.in/eW9Qbn4D 🌐 BMW × Lil Miquela AI meets virtual influencer. A fictional creator promoting a real car—merging identity and product in a new-age collab. https://lnkd.in/ec3UuP84 📱 Vodafone – Rhythm of Life AI meets human interaction. The campaign used AI-generated avatars and motion to bring connectivity to life—bridging people and networks. https://lnkd.in/eFxeZV_K 🛳️ Virgin Voyages – Jen AI Let customers interact with an AI version of themselves. Voice + face synthesis turned every user into their own vacation concierge. https://lnkd.in/eVwf2jDB 🎾 Nike – Never Done Evolving AI helped Nike visualize how Serena Williams' game changed over time. A layered view of performance, growth, and legacy. https://lnkd.in/eE9pXPFS 🍅Heinz – AI Ketchup Asked AI “What does ketchup look like?” Most outputs looked like Heinz—showing how deeply brand codes are embedded in culture. https://lnkd.in/eb97n9Wy 🎨 Nutella – 7 Million Jar Designs AI-driven packaging design at scale. Each jar unique. Creative access widened like never before. https://lnkd.in/eveXx_Ac 🎄 Coca-Cola – AI Holiday Ad Classic seasonal campaign, reimagined using GenAI tools. Visually rich, a glimpse into what AI-powered storytelling could become. https://lnkd.in/eAUr28tN The real takeaway here: AI is breaking down execution barriers. ✅ You no longer need huge teams to create personalised experiences. ✅ Creative assets can be imagined and iterated in hours, not weeks. ✅ Interaction is moving from one-way to dynamic. You don’t need to be a tech company to act like one. You just need to start. #AI #Creativity #Marketing #Advertising #Brand 

🌟♦️New Research Paper Alert:🌟♦️ Creative is becoming the performance engine in an AI first world. As targeting tightens and attention fragments, brands are turning to visual Gen AI to scale concepts at speed. But a practical question keeps popping up in boardrooms, media agencies and creative ops: Should AI create our ads end-to-end, or merely assist human designs? Our new paper (with Hyesoo Lee , Vilma Georgia Todri and Panagiotis Adamopoulos ) puts that to the test across latent diffusion pipelines + a lab experiment + a field study comparing:(1) expert-crafted ads, (2) genAI-modified ads (AI enhances human designs), and (3) genAI-created ads (fully AI-generated). What we find 1) Creation beats modification. Across diffusion pipelines + lab + field, our working paper shows that GenAI-created ads consistently outperform both human and AI-modified ads, lifting CTR up to 19% in the field. 2) Fewer constraints, bigger gains. We show that performance improves further when genAI also designs product packaging. 3) Why it works. GenAI-created ads elicit stronger emotional engagement and higher visual processing fluency; genAI-modified ads often fail to preserve ecological validity. 4) Policy wrinkle. Disclosing AI involvement reduces effectiveness by up to 31.5%, surfacing real trade-offs for emerging AI disclosure rules. Why this matters now 1) Strategy: Move from “AI as polish” to AI as primary creator where constraints are minimal. 2) Operating model: Reallocate time from micro-tweaks to prompting, evaluation, and experimentation. 3) Governance: Test disclosure language; compliance choices can materially shift outcomes.

Last night’s Super Bowl LX felt like an inflection point: AI stopped being a cameo in ads and became both the product and the production engine. A few moments that made me sit up: 🔷 “Made with AI” went mainstream. Svedka ran what it described as the first primarily AI-generated national Super Bowl spot, and reporting suggests it took months of model training to reconstruct and animate their iconic “Fembot” character. That is a new scale signal, not a gimmick. 🔷 Fast-turnaround, high-stakes creative is now viable. ADWEEK reported Genspark assembled its Super Bowl spot on a compressed timeline after securing inventory late. AI is starting to function as a true “schedule compressor” for premium media moments. The AI companies are now competing in public narrative, not only product. Multiple outlets covered a wave of AI-native advertisers (OpenAI, Anthropic, and others) using the Super Bowl to position values, business models, and trust posture, not features. AI spilled beyond commercials into fan experiences. Adobe highlighted Firefly-powered activations with the National Football League (NFL) that turned generative tools into participatory brand moments, closer to “co-creation” than broadcast. What this represents for Media and Entertainment is bigger than “AI in marketing”: 🔷 AI is becoming a first-class production capability. When brands can credibly ship Super Bowl-grade work with smaller teams and tighter cycles, the competitive advantage shifts from raw spend to pipeline design. 🔷 The aesthetic of advertising is changing. Some spots leaned into synthetic style as a feature. Others tried to hide it. That tension will shape craft norms, union conversations, and audience tolerance. Provenance becomes a brand safety primitive. The OpenAI “leaked ad” hoax is a perfect preview of the next problem: misinformation wrapped in high production value, moving at culture speed. Assumption worth pressure-testing is that “more AI” automatically means “lower cost.” At Super Bowl stakes, the new cost center becomes governance. This mean rights clearance, likeness and training-data risk, creative accountability, and provenance tooling, all before you hit render. Looking at this from a strategic lens, AI is turning the Super Bowl into a live demo of the future media supply chain, and the winners will be the teams that can operationalize trust at scale without slowing creative velocity. Read the TechCrunch reporting here: https://lnkd.in/erkcsMYd

AI-modified ads actually underperform compared to human-created ones. You'd think using AI to enhance expert-designed ads would improve performance. According to a new study, "The Impact of Visual Generative AI on Advertising Effectiveness", they don't. Plot Twist: Gen AI-created ads from scratch perform best (19% increase in click-through rates). When AI also designs the product packaging, effectiveness amplifies even further. But when they modify human-created ads, the outcome is worse. Why This Matters: The research reveals that visual genAI excels at creating holistic, emotionally engaging compositions with higher visual fluency. But it struggles to preserve the "ecological validity" of existing designs when asked to edit within constraints. Here's where it gets tricky: When consumers know AI was involved, CTR drops 31.5%. This highlights a critical tension between regulatory transparency requirements (like the EU AI Act) and advertising performance. What This Means For Marketers: ✓ Use genAI for complete ad creative generation, not refinement ✓ Leverage AI's strength in creating unified visual experiences ✓ Navigate the disclosure dilemma - transparency matters, but so does performance AI in marketing is not about choosing between performance and ethics but understanding how AI creates value differently than human creativity.

Great creative is hard. But when you get it right, it can be a game changer for any campaign. You have the idea. You have the media plan. But production? Usually slow. Expensive. High execution risk. Now AI flips this. You can move from concept to design in hours (sometimes minutes). A re-orchestrated flow, from idea → production → launch, is now the name of the game. And the budget? Lighter than ever. This changes everything, especially for growth teams. Maybe the future of marketing isn’t brand vs. performance. It’s iteration speed. Message velocity. Visual scale. These are 7 AI-generated examples that proved to me AI is going to reshape advertising: 1️⃣ BMW - The Ultimate AI Masterpiece ➝ They trained a neural net on 50,000 pieces of art. Then projected it live onto a car. ➝ No headline. No tagline. Just motion. The Change: What used to take an art director and a VFX team now runs in real-time. 2️⃣ Revolve - Best Trip ➝ A 20-year brand campaign. Built with generative AI. ➝ No models. No photographers. Just prompts. The Change: End-to-end billboard creative — concept to render — in less time than booking a studio. 3️⃣ KitKat – Have a Break (AI Edition) ➝ They didn’t brief a team. They briefed an AI. ➝ Headline, copy, layout: all generated. The Change: The creative team is now a prompt engineer. And the copy still lands. 4️⃣ WWF - #WorldWithoutNature ➝ AI imagined a future without forests, oxygen, birds. ➝ And it looked… normal. Which made it hit harder. The Change: AI didn’t just replace the illustrator. It did the emotional work faster. 5️⃣ Jacquemus – Le Bambino ➝ AI-generated handbag buses in Paris. Unreal, but believable enough to go viral. The Change: Creative that used to cost six figures and weeks of prep? Now it’s 48 hours and a rendering engine. 6️⃣ Nike – Never Done Evolving ➝ AI simulated Serena Williams playing her 1999 self. ➝ Then Nike ran it across outdoor and digital. The Change: No shoot. No CGI. No guesswork. Just training data and execution. 7️⃣ Virgin Voyages – Jen AI ➝ AI-generated J.Lo invites you on a cruise. Personalized. At scale. The Change: Celebrity campaigns used to mean long lead times. Now they scale like email. This isn’t about AI replacing creatives. It’s about giving them leverage. To move faster. Test bigger. Launch bolder. Growth teams that adapt will scale. The rest will be outpaced. * * * ♻️ Share if this made you think differently. Follow me, David Manela, for more 📈