IBM, Tommy Hilfiger and FIT Reimagine Fashion Retail with AI

The fashion industry is undergoing a major upheaval driven by the rise of artificial intelligence (AI) and machine learning (ML). As consumer expectations for novelty and speed reach fever pitch, iconic brands like Tommy Hilfiger are teaming up with tech powerhouses like IBM to reimagine every facet of the fashion value chain.

Launched in 2018, the pioneering "Reimagine Retail" project brings together Tommy Hilfiger, IBM, and the Fashion Institute of Technology (FIT) to explore how AI can revolutionize design, manufacturing, and merchandising. By tapping into the power of computer vision, natural language processing, and deep learning, the collaboration aims to spark creativity, increase speed to market, and prepare the next generation of fashion leaders for an AI-powered future.

The Need for Speed in Fashion

The fashion calendar is undergoing a seismic shift. According to a 2020 report by McKinsey & Company, traditional designer collections that deliver new products on a seasonal basis are giving way to a "see now, buy now" model fueled by Instagram trends and influencer culture. Consumer demand for fresh looks is accelerating, putting immense pressure on retailers to shrink turnaround times.

Source: McKinsey & Company, The State of Fashion 2021

For most apparel brands, long lead times and a reliance on trend forecasts made 12-18 months in advance result in overproduction, markdowns, and waste. The rise of fast fashion challengers has further exposed the limitations of the traditional design and merchandising model. AI offers a path forward by enabling brands to spot micro-trends in real-time, optimize inventory, and get new products to market faster.

Under the Hood of the Reimagine Retail Project

At the heart of the Tommy Hilfiger x IBM collaboration is a suite of ML models trained on a vast trove of fashion data. To equip FIT students with cutting-edge skills, IBM provided access to tools like Watson Visual Recognition for analyzing product images and identifying themes, and Watson Natural Language Understanding for mining customer reviews and social media chatter.

The students harnessed these tools to dissect Tommy Hilfiger‘s entire product catalog, along with over 600,000 publicly available runway images and 100,000 fabric patterns. By training convolutional neural networks (CNNs) on this dataset, the system learned to identify common attributes like colors, textures, silhouettes, motifs, and styles.

Generative adversarial networks (GANs) then used these features to spit out entirely new designs incorporating up-to-the-moment trends. For instance, if neon was picking up steam on Instagram, the GAN could propose ways to infuse highlighter hues into Tommy Hilfiger‘s classic preppy aesthetic. This algorithmic remix of familiar and emerging style elements yielded designs that were both fresh and brand-appropriate.

Turning Real-Time Data into Actionable Insights

To take its pulse on shifting consumer sentiments, the Reimagine Retail project also leveraged AI to listen in on social media buzz. IBM‘s Watson Discovery can ingest and analyze millions of online images, product reviews, and comments to surface trending topics, customer pain points, and user-generated content.

Armed with these real-time insights, Tommy Hilfiger can make lightning-fast pivots rather than being locked into a seasonal cadence. If a particular color or print is taking off on TikTok, the brand can rapidly respond by pushing out a capsule collection or influencer activation. Social listening also enables smarter demand forecasting to reduce overstock and unsold inventory.

A Human-AI Creative Collab

While some designers fear being replaced by algorithms, Tommy Hilfiger views AI as a collaborative tool to augment rather than automate human creativity. ML models can parse petabytes of data to surface patterns and predict trends faster than any individual could. But ultimately, it‘s up to human designers to interpret and act on these insights in unique ways.

The Reimagine Retail project demonstrates how AI can break designers out of their comfort zones, expose them to fresh stimuli, and suggest unexpected juxtapositions. By taking on the time-consuming tasks of trendspotting and cataloging, AI frees up human creatives to focus on higher-level ideation and strategy. The result is a powerful human-machine symbiosis that plays to the strengths of both.

As Avery Baker, Chief Brand Officer at Tommy Hilfiger, told Vogue Business:

"We‘re not looking to AI to replace the creative process, but to enhance it. It‘s about taking the data and transforming that into meaningful insights and creative solutions. That‘s still very much a human process, but can be enriched through the power of AI."

The Bottom-Line Impact

Beyond serving as a wellspring of design inspiration, AI can drive measurable improvements in operational efficiency and the bottom line. By leveraging ML to optimize everything from product development and assortment planning to dynamic pricing and personalized marketing, fashion brands can unlock significant cost savings and sales uplifts.

A 2021 report from the Capgemini Research Institute surveyed 500 fashion executives from large retail organizations across the globe to quantify the impact of AI:

• 43% of respondents reported a reduction in design and development costs
• 31% saw a decrease in inventory holding costs
• 95% said AI helps them make faster and more data-driven decisions
• 80% credited AI with boosting sales and improving customer satisfaction

Source: Capgemini Research Institute, State of AI in Retail

As these metrics illustrate, AI is not just a nice-to-have capability but a must-have for fashion brands looking to stay agile and competitive. Companies that harness the power of analytics and algorithmic decision-making will be best equipped to navigate the turbulence ahead.

Towards an AI-Powered Fashion Future

If the past year has taught us anything, it‘s that the only constant in fashion is change. Amidst a global pandemic that upended consumer behavior and rattled supply chains, AI proved an invaluable asset for predicting demand, enabling touchless retail, and connecting with shoppers stuck at home.

But the disruptive potential of AI extends far beyond times of crisis. As the Tommy Hilfiger x IBM collaboration demonstrates, we are on the cusp of an era in which data science and human ingenuity will work hand in hand to push the boundaries of what‘s possible in fashion.

Looking ahead, other AI-powered innovations on the horizon include:

• Virtual showrooms and digital catwalks that allow brands to showcase collections without producing physical samples
• 3D design tools that enable real-time garment simulation, pattern making, and customization
• Smart factories with sewbots and autonomous systems to enable faster, more agile manufacturing
• AI stylists and virtual try-on tech to replicate the in-store experience online
• Blockchain and computer vision to power end-to-end traceability and authentication

As fashion and technology become inextricably intertwined, brands will need to cultivate a new breed of talent that can toggle between the creative and analytical. To stay ahead of the curve, companies should invest in upskilling their workforces with data literacy, algorithmic thinking, and human-centered design.

Initiatives like the Reimagine Retail project offer a sneak peek into this hybrid future of humans and machines working in lockstep. By combining Tommy Hilfiger‘s signature twist on prep, IBM‘s deep tech chops, and the ingenuity of FIT students, the collaboration provides a blueprint other fashion players can follow.

In the coming years, look for AI to become an even more integral part of the fashion tech stack. While robots won‘t be replacing designers, merchandisers, and buyers wholesale, they will become indispensable co-pilots for navigating the complexity ahead. Brands that view AI as an engine for amplifying rather than diminishing human creativity will be the ones that thrive.