Student designers used insights gained from the IBM/Watson project to infuse their designs with innovative tech capabilities. “The machine-learning analysis gave us insights about the Tommy Hilfiger DNA that we couldn’t begin to consume or understand with the human mind,” says Michael Ferraro, executive director of the FIT/Infor Design and Tech Lab. “In addition to exploring how AI might impact decision-making in fashion design, we explored how tools such as social media listening and voice recognition can create a more personalized shopping experience built around an interactive ‘smart’ supply chain strategy that minimizes waste and environmental impact.” These are examples of the various designs created by the FIT students:

• • A plaid tech jacket was made with advanced color-changing fibers that respond to AI analysis of voice and social media feeds.

• • A SolarActive™ sundress, inspired by Hilfiger silhouettes and color palettes, was created with advanced solar-reactive fabric and customer personalization. One strap of the dress has the initials TH for Tommy Hilfiger; the other strap is customized with the purchaser’s initials.

• • Designs were created based on an individual’s social personality, such as an avatar made to be used as a design element; a bomber jacket that uses Watson Personality Insights from the customer’s Twitter account to determine individualized striping and color; and a white “smart” parka that can display current events, temperature, train updates, music, and social media on a removable OLED screen, using voice control and conductive fibers.

These designs respond to the younger customer’s desire for a personalized shopping experience. According to an IBM study, 52 percent of women in Generation Z would like to see tools that allow them to customize products, increasing delivery speed. With garments made on demand, overstock is also greatly reduced.