As much as 90 percent of online content may be synthetically generated by 2026, according to a new report from European law enforcement group Europol. This shift is already reshaping industries like fashion and retail, where computer vision and generative AI tools are automating everything from design to fraud detection. While synthetic media offers real benefits, experts warn that the technology also creates new risks for disinformation and deepfakes.

What Does "Synthetic Media" Actually Mean?

Synthetic media refers to any content generated or manipulated using artificial intelligence. According to Europol's report, in most cases synthetic media is created for legitimate purposes, such as gaming, improving services, or enhancing quality of life. However, the rapid advancement of AI technology has also opened the door to misuse, particularly through deepfakes and other forms of disinformation.

The 90 percent figure raises urgent questions about the future of content creation. What will happen to artists, writers, and other human creators as AI systems like DALL-E and GPT-3 become more capable? How will people distinguish real information from AI-generated content? And what does this mean for how we consume news and information online ?

How Are Fashion Brands Using Computer Vision and Generative AI?

While concerns about disinformation dominate headlines, fashion and retail companies are already deploying computer vision and generative AI in practical, beneficial ways. These applications show both the promise and complexity of synthetic media in real-world business.

• Garment Authentication: Platforms like The RealReal use computer vision and image recognition to identify counterfeit items. Their tools, called Shield and Vision, have flagged over 200,000 fake products since 2011 by analyzing uploaded images for signs of wear, material inconsistencies, and other telltale markers of authenticity.
• Automated Quality Assessment: Computer vision systems detect wear patterns such as fading, pilling, stains, and stretched seams in secondhand clothing. This automation reduces manual quality checks and ensures consistency across resale platforms.
• Visual Content Enhancement: AI improves product photography by adjusting lighting, removing backgrounds, and correcting colors, which boosts customer engagement and reduces return rates.
• Diversity and Inclusion Auditing: Computer vision models analyze marketing visuals to quantify demographic representation by examining skin tones, body shapes, ages, and facial features. Natural language processing tools also scan product descriptions for gender-coded language or cultural insensitivity.

McKinsey estimates that generative AI could boost operating profits in the fashion, apparel, and luxury sectors by up to $275 billion by 2028, signaling the scale of this transformation.

Can AI Really Replace Human Designers?

One of the most striking applications is AI-assisted fashion design. Tools like Midjourney, DALL-E, and Adobe Firefly now help designers create mood boards, sketches, and full outfit designs in minutes rather than weeks. However, the most successful implementations use a "human-in-the-loop" approach, where AI serves as a real-time collaborator rather than a replacement.

The s.Oliver Group, a major fashion retailer, partnered with Fermat, an AI platform that generates realistic fabric visualizations. This allows designers to prototype new styles using fabrics not yet available in their catalog, validate whether designs fit into collections, and collaborate more efficiently across departments. The workflow automation extends to generating technical packs, colorways, and 3D prototypes, accelerating the journey from sketch to sample.

This approach preserves creative control while dramatically speeding up production cycles. Designers still make the final decisions; AI simply expands the range of possibilities they can explore.

What About AI Shopping Assistants and Virtual Try-Ons?

Fashion retailers are also deploying AI agents to improve the shopping experience. These systems learn a customer's body shape, preferences, lifestyle, and context to provide tailored styling suggestions and simulate virtual try-ons. DressX, a digital fashion platform, lets users create personalized avatars from a selfie and virtually try on outfits from over 200 luxury brands and more than one million products.

Daydream, another fashion AI startup, takes a different approach with a chat-based shopping interface. Users enter their preferences into a "Style Passport" and interact with AI models specialized in fit, fabric, silhouette, and occasion. The system provides personalized recommendations across 8,000 brands and 200 retail partners, and upcoming social features will let shoppers share and remix collections.

These tools address a real problem: online fashion returns are notoriously high because customers struggle to assess fit and style from photos alone. By enabling instant outfit creation and virtual try-ons, AI agents could significantly reduce return rates and improve customer satisfaction.

What Does This Mean for the Future of Content and Creativity?

The fashion industry's embrace of generative AI and computer vision offers a glimpse into how synthetic media might reshape other creative fields. Rather than replacing human creativity, these tools are augmenting it, allowing designers, retailers, and marketers to work faster and more efficiently.

However, Europol's warning about the 90 percent figure remains relevant. As AI-generated content becomes ubiquitous, the challenge will be ensuring that these tools are used responsibly. In fashion, computer vision helps authenticate products and reduce fraud. In other contexts, the same technology could enable deepfakes and disinformation. The key difference lies not in the technology itself, but in how it is deployed and governed.

For content creators, artists, and writers, the rise of synthetic media presents both opportunity and risk. Those who learn to work alongside AI tools, much like fashion designers are doing, may find new ways to amplify their creativity. Those who resist the shift may find themselves increasingly marginalized. The next few years will determine whether AI becomes a tool for human creativity or a replacement for it.