“Photoshop is an interesting example. If you think about fashion design historically, the process involved people making sketches. From those sketches, samples would be made,” he explains. Designers would produce prototypes, edit them repeatedly, and eventually narrow those iterations down into a final collection. The process was time-intensive and often required multiple physical samples before a final look was approved, he continues.
Digital tools gradually altered that workflow. “Then, we moved into a scenario where people began using Photoshop rather than sketches to create looks. That allowed for a much more accurate representation of what the final sample would look like,” Smith continues. By enabling designers to visualize garments more precisely before producing physical prototypes, the software reduced waste, accelerated development cycles, and allowed creative teams to experiment more freely. From that perspective, AI may simply represent the next stage in a longer evolution of creative technology. “To me, it makes total sense that instead of manually Photoshopping all those different looks you could use AI to generate them based on sketches, prompts, or archival imagery,” he adds.
What distinguishes the most compelling uses, however, is not the algorithm itself but the human direction behind it. “At the moment, the only way to make good AI art is to have a human with really good taste feeding inputs into the model, then providing feedback and iterating on it until it looks right,” Smith says. Rather than replacing creative roles, AI may function primarily as a productivity tool — a way to expand experimentation while leaving aesthetic judgement firmly in human hands. “I don’t think it’s going to replace humans in the creative sphere anytime soon. Instead, it’s going to be about humans harnessing AI to increase their creativity.”
Forecasters believe this dynamic will eventually lead to a phase where the technology becomes culturally unremarkable. “We’re predicting that AI as ordinary will emerge by 2028,” says WGSN’s Napoli. In that scenario, generative tools will neither dominate cultural conversation nor provoke widespread backlash; instead, they will operate quietly behind the scenes, integrated into everyday workflows in much the same way as image-editing software or analytics platforms today. “AI integration is seen neither as a miracle nor a menace. Instead, it will be an ambient, intuitive tool to increase personalization and convenience.”
The normalization of AI will likely coincide with greater scrutiny around transparency and trust. As consumers become more aware of how generative systems shape marketing and media, they may expect brands to communicate their use of the technology more clearly. “Consumers will ultimately expect you to be transparent about how you are using it to make things better, not just faster or cheaper for the business,” Napoli says. She describes the balancing act brands will need to perform as the “harmony of convergence”: a strategy in which AI enhances efficiency while human creativity continues to define brand identity.
For marketers, that balance will be critical. “Brands will need to navigate the hype and the growing skepticism surrounding it by integrating AI marketing strategies with care,” Napoli adds. In practice, this means using generative tools to streamline operational tasks — such as data analysis, personalization, and content production — while freeing creative teams to focus on what algorithms cannot easily replicate: emotional storytelling, cultural insight, and creative risk-taking. “AI will need to be an assistive tool so brands can devote more effort to marketing elements that require creativity, care, critical thinking, and connection.”
