AI in Creative Industries

In a MAJOR ruling for European copyright law, the Munich Regional Court has sided with Germany’s music rights society GEMA against OpenAI, finding that the company’s ChatGPT model unlawfully used copyrighted song lyrics in its training and responses. The decision, issued this morning, marks the first major European court judgment holding an AI company liable for using protected works without a licence. I got into AI through being Director of Legal Affairs and Regulatory Compliance in IMRO, the Irish counterpart of GEMA - and I know the people in GEMA - so this is very interesting to me. The case centred on GEMA’s allegation that OpenAI trained ChatGPT on its repertoire of German song lyrics, allowing the chatbot to reproduce works by artists such as Helene Fischer and Herbert Grönemeyer. The court agreed, concluding that the model’s ability to reproduce lyrics word for word demonstrated that the works had been used in training. It ruled that OpenAI is liable for copyright infringement and prohibited ChatGPT from reproducing lyrics from GEMA-represented artists unless a licence is obtained. The court also held that the European Union’s Text and Data Mining exceptions cannot shield generative AI systems that “memorise” and reproduce copyrighted material. This reasoning undermines one of the primary legal defences AI developers have relied upon in Europe. While damages will be determined in a separate proceeding, the court’s finding of liability alone sets a powerful precedent. OpenAI has announced plans to appeal. The 42nd Civil Chamber of the Munich Regional Court had indicated its position in September, when it observed that the model’s outputs could not be explained without training on copyrighted material. The final judgment confirmed that assessment. For the wider AI sector, the ruling suggests that AI companies operating in the European Union may need explicit licences for any copyrighted content used in model training or risk litigation. The decision also has regulatory implications. It aligns with growing momentum within the EU to enforce transparency and rights-holder protections under the AI Act and the Copyright in the Digital Single Market Directive. The GEMA v OpenAI ruling diverges sharply from Bartz v Anthropic in the United States. In Bartz, Judge Alsup found that AI training on copyrighted material could qualify as fair use, meaning no licence is required when the use is deemed transformative and non-substitutive. He viewed training as an analytical process that teaches the model general patterns rather than reproducing expression. The Munich court took the opposite view, holding that using protected works in AI training without permission constitutes reproduction requiring a licence. This illustrates the growing divide between the U.S. model, where fair use can exempt AI developers from licensing duties, and the European approach, which treats copyright as an enforceable economic right demanding prior authorisation.

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

Google just dropped a new AI shopping experience that's going to bypass social. Here's what you need to know: At Google I/O 2025, the company just announced its virtual try-on technology that could change how people shop for clothes online. By uploading a photo of yourself, you can now see how different outfits look on your own body. The “try-on” tool is rolling out today in the US via Search Labs, allowing you to access 50 billion apparel listings. When you search for clothing on Google, look for the “Try it on” icon next to supported products. My first thought? This is like Cher's closet in Clueless! My second thought? If people can see how clothes look on them just by uploading a photo to Google, why would they need to scroll through brand socials or UGC? We all keep citing that stat: 45% of Gen Z prefers social search over Google. And that’s still true. Social plays a huge role in discovery. The customer journey has changed. And yet... a lot of people still use search engines. And if Google starts to personalize the experience — pulling directly from retailers — that could essentially sideline the role of social. ** It's important to note ** There is no social integration at this time. If someone wants to try on the latest Gap x DÔEN Collection, it's not pulling from Instagram or TikTok. It's pulling directly from retailer websites. My POV: This is a shopper-first feature and, if done right, could be a great experience. But brands need to pay attention. If this takes off, it prioritizes keeping Google Merchant Center up to date with new products, accurate prices and high fidelity images. And it could reduce the need for UGC. If shoppers can see how clothes look on them, they may not care how they look on random people. Would this change your shopping habits? Would you skip TikTok reviews and go straight to search? #Google #GoogleIO #AI

We’ve just stepped into a new era of creativity. The Mokobara ad film you see here wasn’t shot in a studio. No cameras, no actors, no locations. Every single frame — the characters, the settings, the visuals — was generated through prompts using generative AI. Think about that for a moment. What once required casting calls, production crews, weeks of planning, and expensive shoots… can now be done in hours with a keyboard. This isn’t the future. This is happening now. So what does this mean for us as creators, brands, and storytellers? It means the playing field is changing. The technical barriers are falling away. What used to take deep pockets and big teams is being democratized by AI. But here’s the key: tools may change, but the power of storytelling won’t. In a world where anyone can generate visuals, the real differentiator will be the story you tell. The ability to connect with an audience, move them, and inspire action will matter more than ever. Generative AI will keep getting better, faster, and more accessible. But it will never replace the uniquely human spark that gives stories meaning. The future belongs to those who can combine imagination with storytelling — and let technology do the rest. 👉 What do you think — will storytelling become even more valuable in the age of AI? Mokobara Ad created by Aaron & Pranay Maurya | | Somya Parikh | Raghav Shrivastava | Aaron Gabriel C. | #Mokobara #GenAI #AIAds #AIFilmMaking #Marketing #Storytelling

The conversation around AI in Hollywood is shifting fast – and how it gets built matters more than ever. I work closely with leaders across studios, streaming platforms and global franchises. Media and entertainment companies need to create more content, faster, while staying true to their brand and IP. And they need partners who honor the craft, nuance and authenticity that define great creative work. The stakes are high. Demand for content is rising while timelines are shrinking. And no studio, streamer or franchise can afford to sacrifice the originality that sets their work apart, whether they’re expanding beloved characters and franchises or creating stories that are entirely new. Studios want to partner with companies that share their commitment to the integrity of their IP – companies that truly understand creativity, how it scales and what it takes to protect it. For decades, Adobe technology has been at the center of how films get made. Our tools have earned multiple Academy Awards for scientific and technical achievement, and filmmakers have relied on them to cut, shape and finish their own award-winning films. We understand firsthand what’s at stake in the day-to-day realities of production. The director who needs a reshoot while lead actors are halfway around the world. The animator who must maintain character consistency across hundreds of shots in a single series. The studio launching a franchise film across dozens of markets and languages, with every asset needing to stay true to their brand. That's exactly why we built Adobe Firefly Foundry. Foundry enables media and entertainment companies to build and train custom AI models on their own IP. Their characters. Their worlds. Their visual language. Teams can maintain character consistency in pre-visualization, generate hundreds of thousands of on-brand assets quickly and compress the timeline from concepting through post-production. Every output across image, video and audio stays aligned to their story's creative identity. It also gives studios something just as important: the ability to collaborate with creators thoughtfully while expanding access to their IP. This means that as they scale, studios still protect their actors, their characters and the integrity of their work. Creativity is too important to be a side bet. At Adobe, we're deepening four decades of partnership with the creative industry and working hand-in-hand with creators, studios and media organizations to shape what comes next. Really excited about what the next forty years of storytelling will bring. https://lnkd.in/gy6cr942

Chanel can't use AI the way Mango does. Obviously. But here's what luxury must do about AI now: Fast fashion uses AI for efficiency: more products, faster cycles, cheaper production. Luxury can use AI differently: Not to replace the artisan, but to reveal their mastery. Not to speed up production, but to make precision scalable. Not to homogenize, but to personalize at the level only a private client team could before. Imagine: - Hermès using AI to optimize leather cutting = more bags from the same hide, less waste, same craft - Cartier deploying machine learning for counterfeit detection = protecting the value of human artisanship - A beauty house using AI to analyze skin at the molecular level = bespoke formulation that used to require a lab visit This wouldn't be AI instead of craft. It would be AI in service of craft. Where I think luxury should use AI aggressively: → Ecommerce intelligence: Personalization engines that understand style evolution. Virtual try-on that actually works. Spatial commerce that makes digital feel more intimate than in-store. Customer service AI trained on decades of brand codes and heritage. → Operational excellence: Supply chain transparency. Materials sourcing. Inventory intelligence that prevents overproduction. Predictive analytics that help artisans plan, not replace them. → Creative augmentation: AI as design research tool. As pattern exploration. As the apprentice to the master craftsperson, generating options that human taste then curates. Where luxury should stay away: → Emotional storytelling. Don't let AI write your brand narrative. Don't generate your campaigns. Don't algorithmically create the imagery that's supposed to make someone feel something about your house. The luxury brands doing it right are the ones where taste is the product, not just the outcome. Where you can feel human intention in every decision. AI can inform. It can optimize. It can enable. But it can't replace the creative director's eye. The artisan's hand. The archivist's knowledge. The risk isn't moving too fast with AI. It's moving too slow. Because while luxury hesitates, a generation of consumers is forming relationships with brands that do understand AI. Brands that use it to get closer, more personal, more responsive. In five years, when Gen Alpha (the most digitally fluent, AI-native generation) enters their luxury spending years, they won't forgive brands that feel outdated in a spatial computing world. What's your take? Where should luxury draw the line with AI? Image: Chanel via Matthieu Blazy Socials #LuxuryStrategy #AI #FutureOfLuxury #DigitalTransformation #CraftAndTechnology

For the first time, Nano Banana’s AI agent can design across all mediums: images, video, 3D, music, even voiceovers. Honestly, this makes me rethink my entire view of creativity. I used to believe design was defined by tools—the brush, the camera, the editing suite. But if one agent erases those boundaries, then what even is a “designer” anymore? I catch myself wondering: will future creatives introduce themselves not by their craft, but by their perspective? In my opinion, this isn’t just another creative tool—it feels like the beginning of a new design era. I’ve spent years switching between Photoshop, Premiere, Blender, and Ableton. Suddenly, all of that fits into a single agent. It’s thrilling… and unsettling. Here’s what it means: → Creative disciplines are converging. → The barrier to professional-level work is collapsing. → The role of “designer” itself may be redefined. Here’s how I think we can stay ahead in this new landscape: ✅ Focus on taste and judgment—the one thing AI can’t replicate. ✅ Build multi-modal fluency: don’t just know visuals, learn sound and interaction. ✅ Treat AI as an amplifier, not a replacement—bring in your unique point of view. The real shift is this: creativity is moving from production to direction. From “how do I make this?” to “why should this exist?” And that, to me, is both exciting and terrifying—because it means the creative field is no longer about tools. It’s about judgment. 👉 So here’s the debate: will this new wave of AI usher in a golden age of creative abundance—or a race to creative sameness? #AI #Creativity #FutureOfWork #Design #Innovation Video credits: x.com

Quick commerce might create new rails for fashion in India. But AI is about to rewrite the stack. It won’t just improve margins or automate workflows. It will reshape how demand is created, what gets made, and how we buy. Here’s my prediction: 1. Search becomes intent-led Nobody wants to scroll through 400 SKUs. AI will learn your taste, body, budget, event, and mood, and surface five things that just work. Think: Spotify-style discovery, but for clothes. Discovery becomes contextual, not chaotic. We’re already seeing this in early interfaces like Perplexity’s shopping copilots. 2. Assortments get micro-targeted Massive catalogs are a liability. AI lets brands adapt SKUs dynamically, by user, region, season, even returns history. Shein scaled fast fashion through supply speed, but never cracked fit. Newme is flipping the model by doing weekly drops of 10–15 SKUs based on real-time feedback As merchandising behaves like content, inventory becomes a live system. 3. Returns are engineered out Returns were the biggest margin killer. Now they’re a solvable product problem through predictive sizing + fit-tech + try-at-home delivery. Zalando and H&M are already running fit-tech integrations + virtual try-ons at scale. Fit-tech will become table stakes. 4. Supply chains go real-time From design to drop to replenish to clear. AI enables live demand forecasting, smarter markdowns and faster reaction cycles. Urbanic, Zara, and Myntra are tightening feedback loops using browsing + returns + trend signals Fashion will respond to signals, not seasons and less dead stock will lead to better margins. 5. Shopping shifts from search to recommendation Shopping will shift from browsing to context-driven nudges. AI copilots will shop with you, not for you. Voice-first agents are already live. AI doesn’t just improve conversion: it changes the loop. The next generation of fashion brands will scale through personalization, fit precision, intelligent curation, and habit-forming UX Fashion will live at the intersection of fast-moving infrastructure and intelligent systems. This wont change how we buy. It will change what gets made.

🚨 Fascinating AI paper alert: "Consent and Compensation: Resolving Generative AI’s Copyright Crisis" by Frank Pasquale & Haochen Sun is a must-read for everyone interested in AI, copyright, and artists' rights. Quotes: "The opacity and scale of AI systems is disrupting the knowledge ecosystem by significantly eroding authors’ proprietary control of their works, well beyond extant digital practices that have already undermined many authors’ well-being. Whereas prior scraping at scale tended to be focused on the non-expressive aspects of works (such as facts), AI is focused by many prompts on their expressive dimensions. Search engines have historically provided links which lead users to works themselves. In contrast, AI tends to provide substitutes for such works, while failing to provide citations to the works in the dataset most similar to the texts, images, and videos it presents as a computed synthesis." (pages 8-9) - "Under the proposed mechanism, copyright owners can first request AI providers to take actions to effectively prevent their systems from generating outputs that appear identical or substantially similar to relevant copyrighted works. A copyright owner would be entitled to send a notice to an AI provider when he or she identifies that an output generated by the provider’s AI system contains either a verbatim or substantially similar copy of his or her work, or a derivative work. In the notice, the copyright owner would be obliged to document the unauthorized reproduction of the work and his or her copyright ownership, along with a digital copy or an online link to the work." (page 21) - "Given the complexity of the AI supply chain, particularly with respect to generative AI, it is not feasible to impose a per-device cost on AI providers. However, other triggers for payment are possible. Levies on the use of particular datasets may be imposed, or on model training, or on some aggregate number of responses provided to users, or on paid subscriptions. Alternatively, the level of the levy could be benchmarked with respect to some percentage of AI providers’ expenditures or revenues" (page 39) ➡ Link to the paper below. #AI #copyright #consent #AIregulation #AIpolicy #AItraining

🧨 AI in luxury fashion & beauty (retail) seem to go hand in hand, but where are we today and where are we heading? 👇 Remzi Ural came up with an interesting framework for how AI will transform retail in 3 waves. While some companies are still preparing for Wave 1, the consumer's expectation is already halfway Wave 2... ⚙️ WAVE 1 - The Engine Layer The first wave happens where customers don't come: in the machine room of ops, supply chains, content creation, ... → AI making existing processes faster & cheaper. • American Eagle uses AI for predictive restocking. Data shows that a shelf is about to be empty in 1 hour, AI predicts sales loss & sends an alert: 'Restock shelf X.' • Stella McCartney uses AI to select eco-friendly materials & optimize cutting patterns = reducing fabric waste by 30%. • Burberry analyzes historical patterns + real-time social sentiment to forecast trends. • Mango uses AI for content creation. From turning studio pics into videos, to virtual influencers.. making production of content cheaper & faster. ❤️ WAVE 2 - The Experience Layer The second wave is a shift in interaction with customers. AI moves to the front, creating experiences that feel less like shopping and more like having an assistant. • Cucinelli launched a full AI-website, centred around conversational AI first. No pages, no menus. Worth a visit 😉 • Faces launched Layla AI, a Gen AI-powered beauty assistant. Almost 10% of their customers use it on a daily basis! L'Oréal has something similar, confirming the trend. • LV introduced an in-store Extraordinaires AI-Configurator. Using a photo of the customer or prompts, this VA suggests products that are matched to the customer’s style & needs. • Google VTO lets users try on thousands of clothing items by simply uploading a picture of themself. → Wave 2 is not about cheaper or faster, but better ... and requires rethinking processes. The question isn't whether to invest in Wave 2, but if you can move fast enough, before the competitive advantage's gone. 🤖 WAVE 3 - The Agentic Layer The last wave represents the most profound shift. "Agentic" will COMPLETELY change how commerce occurs. AI agents don't just assist, they execute autonomously on behalf of customers. We're still in the early days of this wave, with only few examples: • Perplexity launched "Buy with Pro" • ChatGPT has "Operator" • OpenAI, Shopify & Stripe are partnering up The user sets preferences & budgets and the agent handles discovery, comparison, negotiation and purchase. No browsing. No abandonment. No checkout (friction). Knowing that 51% percent of Gen Z consumers already starts product research in LLM platforms like ChatGPT or Gemini, this will be the future! ➡️ The brands that will thrive aren't necessarily the ones with the biggest tech budget or the best engineers. The winners will be those that understand what problem they're solving and have the courage to act, even when the path isn't perfectly clear. ⏳