Circular Fashion Talks: The Role of Artificial Intelligence in Fashion’s Circular Transformation
Monitor for Circular Fashion SDA Bocconi
Circularity in fashion is today one of the most complex and strategic challenges for the entire industry. Best practices, constantly evolving regulations, and new business models are reshaping value chains, pushing companies toward a structural transformation that requires collaboration, vision, and the right tools.
It is within this context that the Monitor for Circular Fashion SDA Bocconi operates, where a group of companies from different sectors has chosen to face the path toward more sustainable and circular models together.
A new episode of Circular Fashion Talks, the podcast curated by Francesca Romana Rinaldi, Director of the Monitor for Circular Fashion SDA Bocconi, and Silvia Gambi, journalist and founder of Solo Moda Sostenibile, focuses on a key theme for the future of the fashion system: Artificial Intelligence.
The conversation aims to understand how innovative technologies can concretely support companies in implementing their sustainability and circularity strategies. What is the approach of the companies participating in the Monitor? How is AI already contributing to increasing sustainability along the value chain? And are there potential applications that have yet to be fully leveraged?
Artificial intelligence in the fashion industry
Among the podcast guests is Mattia Ettore Negro, R&I at Deda Ai, who speaks on behalf of Deda Stealth, partner of the Monitor for Circular Fashion SDA Bocconi. His contribution offers a practical and applied perspective on the role of AI in fashion.
Mattia explains how Deda is integrating Artificial Intelligence into the fashion industry with a highly pragmatic approach, keeping a clear objective in mind: supporting companies in critical decision-making moments across the entire value chain, from planning to sales, enabling them to simulate multiple scenarios that may arise along the value chain, while preserving the decision-maker’s full control to confirm, adjust, or reject the proposed solutions.
This approach is implemented through three major decision-support modules: Plan, Execute, and Sell. The Plan module leverages AI to support demand forecasting through machine learning models that take into account numerous variables, such as seasonality, product lifecycle, sizes, and colors, as well as external data, including long-term weather forecasts and events that may impact sales. This also includes Assortment Management and Merchandise Financial Planning. In a sector characterized by short-lived products, high uncertainty, and many external variables, these models provide a more solid view of the future, reducing the risk of over- or under-production.
The Execute module represents the next step, focusing on the operational and industrial phase. Here, AI is used to optimize and schedule production, starting from defining the raw materials needed. Artificial Intelligence allows companies to coordinate decisions that are traditionally fragmented, what to produce, when, and under which constraints, while maintaining a balance between costs, timing, and production capacity.
Finally, the Sell module focuses on omnichannel distribution and product allocation. The goal is to ensure that each product is in the right place at the right time, avoiding both overstock and lost sales. AI supports decision-making regarding when and where to ship products, coordinating channels that often influence one another, both in wholesale order management and retail allocation.
All of this is based on proprietary models developed through over thirty years of optimization experience. These are not generic solutions but algorithms specifically designed for the dynamics of the fashion world, a sector with its own rules, complexity, and specificities; aimed at demonstrating how the integration of AI into supply chains not only enhances business competitiveness but also helps create a more sustainable and responsive ecosystem.
Regarding accessibility, AI is certainly more accessible today than in the past, but some barriers remain. According to Mattia, these are not primarily technological but organizational, procedural, and related to trust in the models. For this reason, Deda’s three modules are modular and scalable, allowing companies to start with a limited scope and expand over time. Great attention is also given to UX and UI, with the aim of making AI a tool that simplifies and supports people’s work rather than complicating it.
Artificial Intelligence, when introduced with domain expertise, gradual implementation, and careful adoption, can become a true value enabler along the entire value chain, supporting the fashion industry in its journey toward increasingly sustainable, efficient, and circular models.