Should fashion brands drop 3D for AI? Ex-Mango 3D lead answers

In Episode 3 of Fashion Decoded, Jess and Ermina Avdisha get into why the answer depends on the use case, where AI already beats 3D for imagery and where 3D still wins, and why clean data and trained teams matter more than the next tool. Ermina has seen this question from both sides: she led 3D at Mango, and today she helps fashion brands decide where 3D and AI belong in their workflows. Episode page and key takeaways: https://botika.com/podcasts/ermina-avdisha-ex-mango WHAT YOU'LL LEARN → How Mango scaled 3D across its teams, and why it was never about the 3D tool itself → Where AI beats 3D for imagery, and where 3D still wins: new garments and fit → Why better images alone won't fix returns or shopper trust → Why AI tools don't stick inside brands, from departing ambassadors to messy data → What AI agents need before they can help creative teams → How brands keep their identity when consumer data drives creative decisions CHAPTERS 00:19 Welcome + who is Ermina Avdisha 01:19 From fashion design to 3D at Mango 05:45 Mango and AI: did they drop 3D? 07:56 3D or AI: which works better for imagery? 10:05 AI imagery, returns and trust 13:14 How AI changed her workday 14:54 Clean data first: why AI tools don't stick 17:45 What brands ask her for in 2026 22:18 AI agents, data and creative taste 25:06 Brand identity and the future of fashion jobs 28:02 Rapid-fire and wrap ABOUT ERMINA AVDISHA Ermina is an independent consultant in digital product creation and AI. She started as a 3D researcher and first used 3D in production at Colmar, then worked on 3D and process at Napapijri before becoming 3D Platform Owner at Mango. She went independent in 2026 and now helps brands decide where 3D and AI belong in their workflows. ABOUT BOTIKA Botika is the AI operating system for fashion content. Fashion brands plan, produce, launch, and optimize every visual they publish, from product pages to campaigns, across every market and channel. Brands on Botika cut production costs by