Google has introduced an AI-powered virtual 'try it on' tool that allows users to upload their photos, enabling them to visualize how clothing items would look before making a purchase.

In addition to this feature, Google has launched a price tracking system that lets users set alerts for specific sizes and colors, defining price thresholds to receive notifications when items drop in price or are restocked.

Targeted primarily at U.S. shoppers, this initiative aims to streamline the online shopping experience, particularly for students preparing for back-to-school shopping and individuals redecorating their homes.

As economic inflation drives demand for smarter shopping tools, Google seeks to enhance user experience while gathering data on consumer preferences to refine its algorithms.

These innovations are expected to disrupt the e-commerce landscape, similar to the impact of AI on news publications, as Google positions itself to compete more aggressively with platforms like Amazon and Pinterest.

The new tools are designed to increase consumer engagement within Google Search and Shopping, encouraging users to browse longer and move closer to making purchases.

While the virtual try-on technology offers potential benefits, concerns remain about the accuracy of AI-generated images, which may not always match real products.

Data privacy concerns have also emerged, as the AI tools process personal photos and search histories to deliver tailored shopping experiences.

Retailers like Estée Lauder and e.l.f. Cosmetics have reported significant increases in conversion rates after implementing similar virtual try-on tools, highlighting the trend towards personalized shopping experiences.

Despite criticisms regarding AI's influence on consumer choices and its impact on news publishers, Google CEO Sundar Pichai noted that these AI features are positively influencing Google Search usage.

The new features are free to use, aiming to simplify the shopping process by allowing users to find and purchase products based on their queries.

Ultimately, the goal of this tool is to help users visualize complete outfits and find complementary pieces, bridging the gap between individual items and full ensembles.