Artificial intelligence (AI) is not just transforming industries—it’s redefining them forever. Fashion, a $3 trillion global market plagued by inefficiencies, is ripe for disruption. For investors, the key isn’t just recognizing AI’s potential but identifying where it can deliver tangible returns.
The New Frontier: Practical AI Applications
Consider Raspberry AI, a New York Fashion Tech Lab graduate and the first fashion tech firm backed by Andreessen Horowitz. Its platform revolutionizes design workflows, slashing tasks tremendously. CEO Cheryl Liu notes, “Something that would take you eight hours to render in 3D you could render in 15 seconds in Raspberry.” This leap in efficiency has made Raspberry AI an attractive investment, not because it’s flashy but because it works—streamlining processes without the need for extensive upskilling and empowering fashion designers at the same time.
Similarly, Diffusely ,founded by CEO Gaétan Rougevin-Baville , reduces production costs by up to 50% for mid-size brands through AI-driven model imagery. By eliminating the need for traditional photoshoots, Diffusely helps brands showcase diversity in models effortlessly, driving higher conversion rates and reducing operational expenses. As Rougevin-Baville explains, “Getting closer to the user is part of the customer experience, but we do it in a more concrete way than virtual avatars—through real visuals that resonate with diverse audiences.”
From Hesitation to Opportunity: Learning from the Past
Fashion tech’s rocky history with overpromised solutions has made investors cautious. As Bryan Kim, Partner at Andreessen Horowitz, emphasizes a strategy for investment, “It has to be something that’s easy to pick up, solves an immediate problem, and doesn’t require 14 weeks of training.” His investment in Raspberry AI was driven by factors that should guide any investor:
Market Potential: Quantity of users for the solution have to be significant, in this case the number of fashion designers was larger than the number of UX designers using Figma (a tool we all love).
Real-World Utility: Seamless integration into existing workflows boosting productivity while assisting the stakeholders ( designers).
Cross-Departmental Adoption: In this case, the tool was usable across design, marketing, and merchandising teams, increasing organizational buy-in.
Strategic Fit: Tackles systemic issues like inefficient workflows and siloed data.
Key Areas for AI Investment in Fashion
Investors should target sectors where AI’s impact can be both immediate and measurable:
Associate Support & In-Store Experiences: Post-COVID, in-store shopping feels cumbersome. James Butler , CEO of Miirage, proposes using 3D holographic AI avatars as sales assistants: “An AI avatar could work alongside associates, offering product information and personalized customer interactions.” This enhances service without replacing human staff, collecting data to improve both retail and supply chain functions.
Supply Chain Optimization: AI excels at real-time data processing, essential for dynamic inventory management. Devon Person , VP of Supply Chain at Foot Locker, highlights, “With over 3,000 stores, knowing the right amount of SKUs to send is tough. AI helps us adjust inventory in real-time, reducing backroom clutter and out-of-stock issues.” Tools that help with demand planning , massive data sets and event predictive analysis can make a huge difference in the supply chain.
Discovery Platforms & Personalization: AI-driven personalization transforms product discovery. Neha Singh , CIO (Chief Innovation Officer) of Infinite Reality, notes, "Customers want independent discovery in-store and online. AI enables a seamless experience—whether through virtual try-ons, peer recommendations, or digital spaces that mimic physical stores." The enhancement of both virtual and physical shopping is a space where Ai is needed the most.
Size and Fit Technology: Returns, often due to poor fit, cost the industry billions. John Bruce Terry , President and Co-Founder of Bodidata, asserts, “Retailers can improve net margins by 50 to 90% using accurate size and fit technology powered by Ai.” Bodidata’s AI tool, Kora, scans bodies (even with clothes on) to recommend the best-fitting items, reducing returns and dead stock—a $70 billion issue tied to customer hesitation.
Sustainability and Waste Reduction: I often say there is only one way to be truly sustainable, by matching people to product on a 1:1. Making this a goal can help to establish sustainable practices beyond greenwashing. AI can drive real sustainability by optimizing production, minimizing waste and being preventative to avoid reactionary methods that are not effective. Predictive algorithms help align supply with demand, reducing overproduction and identifying innovative recycling opportunities, making fashion both profitable and environmentally responsible.
Conclusion: The Future is Now
AI isn’t a trend; it’s the future of fashion. As a 10 year veteran in the fashion technology space, I have never been more excited to see the development and adoption of tools that previously would not be available without the advancement of Ai. For investors, success lies in backing technologies that address real problems—whether in design efficiency, supply chain resilience, or personalized customer experiences. The industry is on the brink of transformation. The question isn’t whether AI will revolutionize fashion; it’s whether you’re ready to invest in that revolution. The future is now!