We approach it with fresh eyes, searching for the moments that hold the most truth. The best shots are not always the obvious ones; sometimes they’re hidden in the subtle gestures, the fleeting looks, the in-between frames that carry emotion.
Once we’ve found them, the real work begins. We connect fragments, reframe meaning, and give shape to something new. The story evolved, becoming sharper, and more intentional.
Then we took those screenshots and brought them to life with AI. Each frame was carefully described through prompts, the lighting, the atmosphere, and the texture of the scene.
We refined, adjusted, and re-ran until the results matched the story we had in mind. It wasn’t about pressing a button, it was about guiding the AI with detail and intention, shaping movement out of stillness.
A big part of the transformation was adding 3D renders of the products. By integrating them into the scenes, we gave each frame depth and polish, creating visuals that felt high-end and cinematic. The realistic textures, lighting, and movement elevated the material, turning simple screenshots into content with a luxury feel.
We achieved in less than a week what would normally take days of planning, a full production crew, and weeks of post work.
Instead of scouting locations, scheduling shoots, and building sets, we worked directly with the material we had, enhancing it with AI and 3D renders. The process cut away layers of logistics.
What used to be a long, resource-heavy pipeline became a focused creative sprint. In under seven days, we shaped visuals that looked like they came from a full-scale production, but with a fraction of the time and cost.
.jpg)
When people hear “generative AI,” the mind jumps to images and text. In practice, the larger shift is in how work gets done. Adoption is now mainstream. McKinsey reports that 71 percent of organizations regularly use generative AI in at least one function, with marketing and sales among the top users.
AI has compressed large parts of the video pipeline. Advertisers can generate scenes, animate stills, and blend AI environments with photorealistic 3D product renders, which reduces location, set, and reshoot costs while allowing rapid creative exploration. Platforms are baking this in. Google integrated Gemini into Performance Max to generate stronger copy and richer images for placements across Search, YouTube, and more. Amazon rolled out free AI video generation for sellers that creates short product videos in minutes, and continues to expand its image and video toolset for advertisers. Meta reports millions of advertisers using its generative tools and credits AI innovations with stronger ad pricing and performance.
Real results are showing up case by case. Headway, an edtech startup, reported a 40 percent ROI lift for video ads after shifting to AI-driven creative tools like Midjourney and HeyGen, while also cutting production effort.
As routine asset creation and formatting are automated, teams spend more time on strategy, testing, and interpretation. WARC notes that AI’s spread into day-to-day marketing is reshaping how planners and creatives work, even as media quality concerns rise alongside rapid spend growth. IAB’s latest use-case map shows how AI now spans the full value chain, from asset generation to bidding and optimization.
AI helps produce many creative variations that respond to audience signals in near real time. Meta’s ads ranking and recommendation models, along with automatic creative tools, are designed to tailor assets and improve outcomes at scale. Google’s Performance Max and newer AI features do similar work across placements. Retail platforms are following suit, with Amazon’s creative studio and video generator broadening access to performance-ready assets for merchants.
Effectiveness measurement is catching up. Nielsen expanded its suite to include AI-based creative and attention diagnostics, while the IAB has issued attention-measurement guidance that blends multiple signals to predict outcomes. These frameworks help teams compare AI-assisted creatives against benchmarks and make faster, evidence-based optimizations.
On the business side, AI-influenced shopping already moves revenue. During the 2024 holiday season, Salesforce data showed AI-assisted experiences helped lift U.S. online sales, with global AI-influenced sales estimated at 229 billion dollars and chatbot use up 42 percent year over year.
There are limits and risks to manage. Quality concerns, synthetic bias, disclosure, and brand safety are top of mind. Google watermarks AI images in ads. Industry bodies are publishing standards for measurement and responsible use. Marketers should adopt clear review processes, governance for training data, and brand guidelines for synthetic content.