Generative AI In Creative Jobs

If your AI brainstorming starts with an AI prompt  such as “give me ideas about for X,” you’re limiting your imagination.  I learned this while working through IDEO U’s Human-Centered Design and AI certificate program, which keeps reminding me that AI only supports creativity when humans stay actively involved. To test this, I ran a small experiment tied to my design challenge: how can nonprofit professionals use AI to augment their thinking so their work becomes more strategic, creative, and human-centered? Here’s what happened. When I began with human-only ideation (my own brain or a brainstorming session with other humans), the ideas were grounded in mission, constraints, and real community needs. When I switched to AI with a clear creative direction to generate ideas, I asked for absurdity.  AI delivered: costume-based learning scenes, dramatic falling sequences, Play-Doh brains, even a human–AI tango. These weren’t solutions or a waste of time. They were creative provocations that loosened up the tight mental space we often operate within. The best ideas emerged only after I cycled through several layers of human grounding, AI variation, and human synthesis. It felt like a club sandwich of thinking modes. Humans brought mission and ethics. AI widened the possibility space. Humans shaped meaning. The infographic (created in Nano Banana) shows the practices that made this work: 💡Begin with human insight. 💡Give AI a clear creative direction. 💡Separate idea expansion from idea selection. 💡Use reflective checkpoints. 💡Treat AI as a partner, not a replacement. This experiment makes me think that the real value of AI in nonprofit brainstorming is less about efficiency and more about expanding imagination. When humans guide the process, AI becomes a thought-partner for more human-centered creativity. What would open up in your work if your organization treated AI as a creative partner instead of a shortcut?

I meet with hundreds of creators around the world every year, from independent designers to global creative directors. In conversation after conversation, one thing is clear: creators aren’t just experimenting with AI – they’re embedding it into their workflows to expand their range, accelerate production and unlock capacity for more ambitious work.    A few consistent priorities stand out: ✅ Creators want a one-stop shop for AI models. Keeping up with all the new models – and juggling apps and accounts – slows them down. That’s why we built Adobe Firefly as an all-in-one creative AI studio, bringing leading models from Adobe, Google, OpenAI and others together in one place, at one price. ✅ Models are powerful, but in the right tools they're transformative. Using Google’s #NanoBanana directly inside Photoshop lets creators reshape a pose or reimagine a background by pairing breakthrough AI with the world's best imaging tools. ✅ Ideation with AI is liberating. Designers tell me Firefly Boards helps them take an initial sketch in hundreds of directions in minutes. Creative directors say it’s reshaping how their teams explore concepts at the earliest stages. ✅ Modular, composable workflows are the future. Project Graph, the creative system we previewed at #AdobeMAX, lets creators mix and match creative tools to move beyond prompts into visual workflows they can build, customize and reuse across Adobe's ecosystem.    I’m continually inspired by how intentionally creators adopt new technology to elevate their craft. It motivates us at Adobe to build tools that remove friction, expand possibility and help creators move from idea to impact even faster.    Learn more about why creators are excited about Project Graph ➡️ https://lnkd.in/gmMhvnbn

A very useful in-depth study out this week on how humans work with AI agents. The research analyzed 2,200 participants in the process of creating 11,000 advertisements, analyzing speed, quality, and creative variety. The findings: 🚀 AI agents supercharge individual output. Collaborating with AI agents increases individual productivity by 50% per worker compared to human-only teams. These teams also maintain higher completion rates for specific tasks like headlines and primary text. AI appears to effectively substitute for a second human collaborator. 🏔️ Skills follow a jagged frontier of capability. Collaborating with AI improves the quality of ad text but results in lower image quality compared to human-human teams. This uneven capability means that AI-assisted ads perform better on click-through rates and view duration, while human-designed ads are more effective at lowering cost-per-click. 🤖 Social maintenance disappears in AI collaboration. Humans + AI teams send 25% more task-oriented messages but 18% fewer interpersonal messages than human-only teams. Because AI requires no rapport-building, encouragement, or conflict resolution, communication becomes more instrumental and directive. ✍️ Work shifts from doing to directing. Humans make 62% fewer direct text edits when working with AI, choosing instead to delegate 17% more of the workload to their digital partners. This creates a "delegation workflow" where the human moves into a supervisory role, spending less time on manual production and more time providing instructions and feedback. 📉 Automation leads to a collapse in creative diversity. Humans + AI teams produce outputs that are more self-similar and less unique than those produced by human pairs. While delegating to AI can improve the average quality of text, it consistently reduces the variety and atypicality of the final content, leading to a homogenization of creative output. 🧐 Knowing your partner is AI changes how you work. Recognition of a partner's identity acts as a key behavioral moderator; participants who correctly identify their partner as AI are significantly more task-oriented and more likely to delegate work. Awareness of AI’s capabilities allows humans to override social defaults like politeness or turn-taking, and adopt more efficient, calibrated collaboration strategies. A really solid study, but there is a lot more to uncover in the realities of human-AI agent work and complementarity.

The Future of Teamwork is Human + AI, I just reviewed fascinating new Massachusetts Institute of Technology research by Prof Sinan Aral and Harang Ju on AI-human collaboration that has significant implications for innovation teams. Key findings from the study:- • Human-AI teams communicated 137% more than human-human teams. • Workers with AI partners focused 23% more on content generation. • Human-AI teams achieved 60% greater productivity per worker. • AI teams produced higher-quality text, while human teams created better images. • AI personality traits can be matched to complement human personalities for optimal results. Most remarkably, ads created by human-AI teams performed comparably to human-human teams in real-world tests with ~5M impressions! The researchers developed “MindMeld” - a collaboration platform enabling humans and AI agents to work together in real-time. Their field experiments revealed that AI agents reduce social coordination costs, letting humans focus more on creative output. As a builder and innovator working with agentic AI solutions, I find this research validates what I’ve experienced: the future isn’t about AI replacing humans, but about thoughtfully designing AI systems that complement human strengths. What’s your experience working with AI collaborators? Have you noticed changes in your productivity or communication patterns? #AICollaboration #FutureOfWork #AgenticAI #Innovation

🚀 Excited to share my latest Fortune column on truly groundbreaking academic work from my co-authors Professor Karim Lakhani and Fabrizio Dell'Acqua at Digital Data Design Institute at Harvard (D^3), where I serve as an executive fellow. This remarkable field experiment with 776 Procter & Gamble professionals fundamentally challenges what we thought we knew about teamwork. The research reveals the emergence of the "cybernetic teammate"—AI that doesn't just assist but actively participates in collaboration. Three breakthrough findings: 1. AI Can Replicate Team Benefits Individuals working with AI achieved nearly 40% performance gains—matching traditional two-person teams. AI is providing the same collaborative benefits we've long attributed to human teamwork. 2. Cross-Functional AI Teams Generate Breakthrough Innovation AI-augmented cross-functional teams were 3x more likely to produce top 10% solutions. This isn't marginal improvement—it's a multiplicative effect that neither human-only teams nor AI-enabled individuals could achieve alone. 3. AI Breaks Down Silos (For Real This Time) R&D specialists with AI proposed commercially viable solutions. Commercial professionals developed technically sound approaches. AI acted as a bridge, enabling each team member to think holistically across functions—achieving the "silo breaking" that leaders have struggled to accomplish through org chart reshuffles. Bonus finding: AI collaboration increased positive emotions by 64% in teams. This isn't cold, mechanical work—it's energizing and engaging. At Seven2, we're translating this research into practice with our portfolio companies, building these AI-augmented cross-functional teams to drive innovation and competitive advantage. This is the future of collaborative work—not AI replacing humans, but human-AI ensembles that combine the best of both worlds. Read the full analysis: https://lnkd.in/ef3f3pED #AI #Innovation #HBS #D3Institute #FutureOfWork #PrivateEquity #TeamDynamics

AI agents aren’t just changing the game—they’re rewriting the rulebook for publishers. With OpenAI's launch of the "Operator" AI agent, the publishing world is buzzing with questions: Will this technology create a traffic vacuum as users bypass traditional search engines? Or will it push publishers to prioritise hyper-personalisation, delivering richer, more customised audience experiences? As The Drum highlights, OpenAI CEO Sam Altman describes Operator as a “paradigm shift” in how people interact with information. By offering direct, conversational answers, AI agents could significantly reduce reliance on traditional search platforms, posing a challenge for publishers still heavily dependent on organic traffic. Here's another crucial insight: Google is also introducing AI agents through Project Mariner, which takes personalisation a step further by allowing AI to browse the web on your behalf to provide custom, contextually relevant answers (NewsBytes). This means that AI agents aren’t just presenting static, pre-selected information—they’re actively browsing and curating answers based on real-time user interactions. Publishers must evolve their strategies to keep pace with this kind of dynamic content delivery. But here’s the thing—this doesn’t mark the end for publishers. It’s a pivotal moment to recalibrate, innovate, and build stronger, more direct relationships with audiences. Instead of seeing AI as a threat, why not view it as an opportunity to rethink how we engage with readers? Here’s what publishers need to focus on: - Reinvent audience development strategies: Relying on a single channel is no longer sustainable. Instead, build direct connections with your audience through owned platforms like newsletters, apps, and exclusive memberships. These aren’t just optional—they’re critical. Also, understand at what stage of the reader funnel the platform/channel is most valuable to you and your audiences. - Embrace personalisation: AI tools can work for you, not against you. Leverage them to create tailored content, gain real-time audience insights, and deliver adaptive user experiences that keep readers engaged. - Leverage partnerships and innovation: Collaborating with pubtech and providers and investing in emerging tools will help you confidently navigate this shifting paradigm. What’s your strategy to thrive in the next stage of AI agents? Share your thoughts in the comments—I’d love to hear from you. #DigitalPublishing #AIForPublishing #AudienceEngagement

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.

AI isn't just a tool; it's becoming a teammate. A major field experiment with 776 professionals at Procter & Gamble, led by researchers from Harvard, Wharton, and Warwick, revealed something remarkable: Generative AI can replicate and even outperform human teamwork. Read the recently published paper here: In a real-world new product development challenge, professionals were assigned to one of four conditions: 1. Control Individuals without AI 2. Human Team R&D + Commercial without AI (+0.24 SD) 3. Individual + AI Working alone with GPT-4 (+0.37 SD) 4. AI-Augmented Team Human team + GPT-4 (+0.39 SD) Key findings: ⭐ Individuals with AI matched the output quality of traditional teams, with 16% less time spent. ⭐ AI helped non-experts perform like seasoned product developers. ⭐ It flattened functional silos: R&D and Commercial employees produced more balanced, cross-functional solutions. ⭐ It made work feel better: AI users reported higher excitement and energy and lower anxiety, even more so than many working in human-only teams. What does this mean for organizations? 💡 Rethink team structures. One AI-empowered individual can do the work of two and do it faster. 💡 Democratize expertise. AI is a boundary-spanning engine that reduces reliance on deep specialization. 💡 Invest in AI fluency. Prompting and AI collaboration skills are the new competitive edge. 💡 Double down on innovation. AI + team = highest chance of top-tier breakthrough ideas. This is not just productivity software. This is a redefinition of how work happens. AI is no longer the intern or the assistant. It’s showing up as a cybernetic teammate, enhancing performance, dissolving silos, and lifting morale. The future of work isn’t human vs. AI. The next step is human + AI + new ways of collaborating. Are you ready?

The AI art debate is missing the real story. Everyone focuses on the technology. Few talk about the humans behind it. Here are 5 uncomfortable truths: 1) AI doesn't create → it recombines Just like the marionette that traces over a photo reference, AI models remix existing works. The creativity lies in human direction and curation. 2) Attribution is broken When Gemini 2.5 Flash generates art from millions of training images, whose style is it really? The original artists deserve recognition and compensation. 3) Human skill still matters Getting quality output from AI requires expertise. Prompt engineering, style direction, and post-processing all need human intelligence. 4) The plagiarism line is blurry Traditional artists have always drawn inspiration from others. But AI operates at unprecedented scale and speed. We need new frameworks for what's acceptable. 5) The technology is democratizing creativity Love it or hate it, tools like Gemini 2.5 Flash are putting advanced creative capabilities in everyone's hands. Over one million users joined overnight. The real question isn't whether AI will replace human creativity. It's how we ensure human creativity remains valued and protected as these tools evolve. We need industry standards. Legal frameworks. Ethical guidelines. And we need them now, before the genie gets too far out of the bottle. How should we balance innovation with protecting creators' rights? ♻️ Share this to spark important conversations 💚 Follow me if you care about the future of creativity VC: @galeria_marionet IG / TT #techforgood #ai #gai #provenance #proofofhumanhood