AI in Creative Industries

There’s a secret trap MANY people fall into when using AI to create their presentations. After years of studying what makes presentations succeed or fail, I'm noticing a concerning pattern as leaders rush to adopt AI for their high-stakes communications. In 1964, media theorist Marshall McLuhan said, "The medium is the message." His framework helps us understand what happens when a new technology enters our lives. When I applied his Tetrad of Media Effects to AI in presentations, the pattern became clear . Here's what AI is doing to your presentation process: AI gives you a 24/7 thinking partner. Need headline variations for your product launch? Want to test different story angles for your board presentation? AI accelerates all of that exploration. You're no longer building in isolation. Like the ancient oral traditions, you can shape ideas through dialogue before they're polished. It's collaborative, iterative, and fast. This transforms your role from slide creator to story architect. Your job isn't to fill slides, but to shape the logical and emotional journey your audience experiences. But there's a dangerous trade-off emerging. I've watched brilliant leaders deliver AI-generated presentations that looked perfect on paper, yet completely failed to move their audiences to action. Their messages were efficient... but empty. Here's the trap: When your presentation arrives instantly through AI, you skip the mental friction that creates genuine breakthrough thinking. The quiet walk. The reflective pause. The deep consideration of your audience's specific needs. Without realizing it, you become reactive rather than purposeful. Your thinking is outsourced rather than enhanced. The most devastating consequence? Your audience feels it immediately. They detect the generic thinking. They sense the lack of true empathy for their situation. And they don't take action. The very tool that makes you faster can undermine what makes you persuasive. The solution isn't avoiding AI. It's using it while preserving four essential human capabilities: 1. Empathy: Deeply understanding your audience's context 2. Message: Testing for clarity and resonance 3. Visuals: Creating memorable images that guide understanding 4. Delivery: Bringing it to life through authentic presence Because every presentation that moves people to action still starts with human empathy, not algorithmic efficiency.

The music AI landscape is too complex for a single map — so instead, I made three. 🤓 As part of my presentation at last week's Boston Music AI Meetup, I developed a brand-new set of market map visualizations, capturing the rapidly evolving state of music AI from multiple angles. If you've been following Water & Music for a while, you may remember our first music AI market map from November 2022, focused on how AI slots into the creative process. Since then, the landscape has expanded dramatically, with dozens of new tools, industry partnerships, and legal challenges emerging. I've realized that one single map is simply insufficient to capture what's happening. So, I opted for three new ones, each showcasing a different part on the market: 🎯 Map 1: The Use Case Lens breaks down who's using what tools and why. The market has naturally organized into distinct segments serving specific needs — from consumer-facing, full-stack generation platforms like Suno and Udio, to specialized professional tools for audio processing and vocal editing. The "Rights & Protection" category in particular did not exist in our 2022 map, reflecting the music industry's growing focus on copyright and attribution for AI. 💰 Map 2: The VC Rollercoaster lens traces how the money trail of VC funding in music AI startups has shifted over the past few years. Ever since Suno's massive $125M raise, the investment focus has actually shifted away from full-stack consumer moonshots toward B2B solutions with clearer revenue paths, particularly those addressing rights management and professional workflows. 🔄 Map 3: The Industry Incumbent lens reveals how established players are responding, leveraging existing user bases and distribution channels to maintain relevance without starting from scratch. While some companies like Splice, Output, and YouTube are building their own capabilities in-house, we're also seeing strategic partnerships and integrations becoming the norm, led by SoundCloud's integrations with nearly 10 different AI tools. I'll be publishing a comprehensive analysis for Water & Music members next week that explores these patterns and their implications for creators, rights holders, and tech companies. Not a member yet? Sign up for our free newsletter to be notified when this analysis drops. Link in comments 👇 #MusicAI #MusicTech #AIStrategy #MusicIndustry #MusicBusiness

If broadly true, this is massive. "Our findings reveal that AI enhances general human capital (cognitive abilities and education) by facilitating adaptability and idea integration but diminishes the value of domain-specific expertise." A fascinating study, "Augmenting Minds or Automating Skills: The Differential Role of Human Capital in Generative AI's Impact on Creative Tasks" (link in comments) researches humans + AI work dynamics in highly creative domains. The results align with what I have been thinking: because we can readily access and learn domain expertise, generalist skills are rising in relative value. This leads to many more questions, such as how we develop generalist skills, when this can only be built from sets of domain expertise. I will be sharing more on this in later posts. Some specific insights from the paper: 📊 Generative AI Enhances Creativity but Favors General Human Capital: Across two experiments—flash fiction writing and songwriting—AI improved creativity, particularly in novelty and overall impression. However, this effect was significantly stronger for individuals with high general human capital (education and IQ). Specific human capital, like domain-specific expertise, negatively moderated the AI-creativity relationship, as experts benefited less. In songwriting, AI use did not consistently improve creativity, suggesting task-specific limits of AI's impact. 💡 AI’s Role in Breaking Knowledge Barriers: The experiments highlight how generative AI transforms the value of expertise by reducing reliance on domain-specific knowledge. In songwriting, for instance, AI’s ability to synthesize diverse information outperformed the narrower focus of experts, allowing novices to achieve comparable results. 🎯 Implications for Task Design and Skill Development: The findings reveal that AI excels in tasks involving broad exploration and integration of ideas, while its impact diminishes in emotionally nuanced or deeply specialized contexts, such as songwriting. Organizations can leverage AI most effectively by redesigning roles to emphasize strategic oversight and integration rather than routine expertise. 🔄 Cognitive Ownership and Engagement Dynamics: AI use decreased participants’ psychological ownership of their creative work, potentially undermining intrinsic motivation. However, it boosted creative self-efficacy, particularly for novices, empowering them to engage in tasks they might have avoided due to perceived skill gaps.

This year I’ve been on 100+ podcasts which account for more than 50% of all of our inbound. For every podcast, it’s important for me to get the most scale out of every asset that I can pull. For most people, that’s where the leverage stops. Episode drops → one or two promo assets → onto the next one. But if you’re doing that, you’re leaving a ton of scale on the table. Because every episode actually contains: -Multiple sharp, 30–60 second takes -Reusable stories and frameworks -Hooks that could live on LinkedIn, YouTube Shorts, your site, email… The real game isn’t “be on more podcasts.” It’s: get the right clips out of every appearance and put them back to work everywhere. That’s what I started doing with Goldcast's new Agentic Video Editor. I take all of my appearances and drop them straight into Goldcast. The Agentic Video Editor analyzed everything and surfaced the exact moments where I was really on a roll: -Clean, self-contained clips -Strong hooks and one-liners -Segments where I’m explaining a framework or telling a story Instead of me hunting through 60-minute recordings, it did the first draft of “here are the clips worth scaling.” From there, I turned those moments into a whole library of ready-to-publish clips in a fraction of the time it would normally take. The AI handled the grunt work: -Auto captions I could quickly tweak -Smart scene changes so clips feel dynamic, not like a Zoom rip -On-screen callouts for the big ideas or quotable lines -Suggested b-roll and background music to keep people watching The result? Every podcast appearance now turns into: 1️⃣ A set of short clips for social 2️⃣ Mid-length cuts for landing pages, nurture, or sales enablement 3️⃣ A searchable library of “my best answers” on core topics Same recordings. Way more surface area. Way longer shelf life. If you’ve spent the year doing podcasts and panels, Goldcast’s Agentic Video Editor is the fastest way I’ve found to: Turn scattered interviews into a clip library And turn that clip library into real distribution—across every channel your buyers actually hang out on. #GoldcastPartner

'Transform', shape changing furniture by MIT media lab. Quite a depiction also of where our social feeds and digital content are heading:   AI is quickly becoming the main tool for the creation of texts, images and designs. In which users tell the systems what to create. But that's an intermediary phase. The more fundamental shift is one in which AIs will create without our detailed instructions. And change content on the spot.   That future is here. Last week Meta introduced their 'Imagined for you' project at the Meta Connect Event. Idea is that images on your Facebook or Instagram feed are generated by AI instantly. For you, based on your data. This is a shift that will occur in all sort fields where content creation and design come into play.   It's not necessarily a bad thing. Creation will change, away from craftmanship to working more on a conceptual level, setting the boundaries for the systems. As long as the creating systems connect to deep human stories, concepts, or emotions, they can lead to interesting output. Maybe even art.   Where it becomes problematic, is when the systems do their thing based on the statistics that drive our social media. Being triggered by flat impulses, click bait and polarization. Leading to content increasingly finetuned to get you in matching states a mind. A development therefore to be critical about and push back against.   The shape changing table 'Transform' was created in 2014. More prophetic about an upcoming future than its makers probably ever imagined (for you).

UK House of Lords: AI, copyright and the creative industries The UK faces a choice between two futures. In the first, the UK becomes a world-leading home for responsible, licensing-based artificial intelligence (AI) development, where commercial model developers using UK content obtain permission, pay fair remuneration to rightsholders and can deploy their models without questions of legal liability. In this scenario, both the UK’s creative industries and AI sector could thrive. In the second scenario, the UK continues to drift towards tacit acceptance of large-scale, unlicensed use of creative content and long-term dependence on opaque models trained overseas, with most benefits accruing to a small number of US-based firms while harms to UK creators grow. Only the first path is compatible with the UK’s long-term interests. In the age of AI, the protections for creators afforded by copyright are under threat. This is not because the copyright framework is outdated or in need of reform. Rather, widespread unlicensed use of protected works, coupled with limited transparency from AI developers about how their models have been trained, leaves rightsholders unsure about whether their content has been used, and unable to enforce their rights when it has. In addition, the absence of a robust ‘personality right’ or specific protection for digital likeness in the UK means creators and performers are unable to challenge harmful outputs that imitate their distinctive style, voice or persona. Meanwhile, technology sector stakeholders are pressing for the introduction in the UK of a broad new exception for commercial text and data mining (TDM) that would legitimise large-scale AI training on copyright-protected works. Without this, they argue, the growth of the UK’s AI sector will be stunted. There is, however, only limited evidence to show that weakening UK copyright law would significantly expand our AI sector. In contrast, a broad commercial TDM exception presents predictable harms to rightsholders by removing incentives to license protected works for AI training. A new regime must now be created to safeguard creators’ livelihoods, while harnessing the potential of AI for creativity and economic growth. To deliver this, we recommend the following actions: 📍Rule out a new commercial text and data mining exception with an opt-out model 📍Close gaps in protection for identity, style and digital replicas 📍Make transparency about AI training data a statutory obligation 📍Create the conditions for a fair and inclusive UK licensing market 📍Champion the development of technical standards for control, provenance and labelling 📍Prioritise the development and adoption of sovereign AI models

If I were starting as a designer in 2026, here's what I'd do: Most designers are optimizing for the wrong things. Being good at Figma is no longer how you stand out. AI will become better at polishing UI than most designers anyway. What matters now is knowing what to build, recognizing product quality, and articulating intent clearly enough that AI becomes your best sparring partner. That's the new designer skill set worth betting on in 2026. If you have clear thinking, good visual taste, and judgment about what to build, you'll win. When anyone can execute at a baseline level, your product mindset becomes your only differentiator. So here's the thing: developing that mindset is way harder than developing technical skills. But no one is born with it, it all comes through practice. You need to ship and ship and ship until you get really good at it. So if I were starting today, here's what I'd focus on: 1/ Develop your product mindset before pro tool skills Study great products obsessively. Ask why things work. Build your internal quality bar for what good looks like. 2/ Learn to articulate your intent clearly AI execution is only as good as your clarity of thought. Practice describing what you want in specific, unambiguous language. Prompting is the new wireframing. 3/ Ship constantly, not perfectly Excellence comes through repetition. Build 10+ versions of something rather than perfecting one in isolation. 4/ Understand the full stack enough to be effective You don't need to code, but understand how AI systems connect. Take advantage of MCPs, agents, and automations to build end-to-end experiences. 5/ Develop strong opinions Your value isn't speed. It's knowing what's worth building and recognizing quality when you see it. You'll win as a designer by developing clear vision and sharp taste, then using AI to execute at impossible speed. The golden age of the design founder is here. But only if you're developing the right muscles.

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

🌟 When #AI meets #Ghibli: Whimsy or Warning Sign? 🎨 #OpenAI’s new Studio Ghibli-style image generator is going viral—and it’s easy to see why. The nostalgic dreamscapes, hand-drawn warmth, and childlike wonder of Miyazaki’s world now rendered in seconds by machine. I could not resist to try 👇🏽 Stunning? Yes. But also… unsettling. This is more than aesthetic novelty. It’s another sharp pivot in the #creativeeconomy. AI isn't just replicating art—it’s repackaging cultural legacy into synthetic outputs. The questions I’m asking: 📍 Whose style is it to mimic? Ghibli’s magic was built over decades. Do artists get credit—or compensation—when models are trained on their work? 📍 What happens to imagination? Will Gen Z creators rely on prompts, not pencils? 📍 And what of ethics in automation? We’re glamorizing a tool that blurs inspiration and imitation without rules of engagement. ➕ There’s potential here—yes—for storytelling, education, even mental health. ➖ But there’s also risk. Risk of dilution, of theft masked as innovation, of sidelining the very humans whose ideas trained the machines. I am absolutely fascinated by AI's potential. I build with it. I commercialize it. As I was talking with friends last night and this morning, I also had to interrogate it. Because if we don’t ask hard questions now, we’ll be answering to consequences later. 👀 Have you tried the new Ghibli-style generator? 💭 Impressed? Concerned? Both? 👇 Drop your thoughts. cc: Sebastien Gaudin Alan Martin Insurtech Insights

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