While the concept seems simple, the underlying AI technology is advanced. In a live demonstration, the tool appeared to function seamlessly. The feature is now available in the United States and is part of Google’s broader efforts to enhance the online shopping experience through AI integration. It’s particularly useful for people who often struggle to visualize how clothing will look on their body compared to how it appears on models.
However, the rollout of this tool raised valid questions about user privacy. AI systems that involve personal images often come with concerns over data usage. Addressing these worries, a Google representative clarified that uploaded photos are used exclusively for the try-on experience. The images are not stored for AI training, are not shared with other services or third parties, and users can delete or update their photos at any time.
This level of privacy protection is notable in an industry where user data is typically leveraged to improve algorithms.
Given Google’s ongoing development of AI-driven tools, some expected the company to utilize this photo data for model training. Instead, the commitment to user privacy in this case suggests a more responsible approach.
Virtual fitting technology isn’t entirely new. Retail and tech companies have been exploring similar ideas for years. Amazon, for instance, has experimented with AI tools in its fashion division. Google, however, claims its new tool offers a more in-depth understanding of diverse body types.
During the presentation, Vidhya Srinivasan, Google’s VP of ads and commerce, emphasized the system’s goal of accommodating different shapes and sizes more effectively.
Past AI image tools have faced criticism for lacking diversity and realism. It’s unclear whether Google’s new tool will be more reliable across the board. Nevertheless, their assurance that user images won’t be used to train models helps build trust.
Although the virtual preview may not always perfectly reflect real-life appearances, this development points to a promising direction for AI in retail. If successful, it could improve customer satisfaction, reduce returns, and make online shopping a more personalized experience.
