Executive Master in AI for Fashion

Day 1 — AI, Fashion and the New Business Context

02 Oct 2026

• Overview of the fashion and luxury industry: business models, value chain, channels and digital transformation
• Why AI matters now: megatrends, competitive pressure, efficiency, personalisation, speed and creativity
• What AI is: history, definitions, myths and real-world examples
• AI vs Machine Learning vs Deep Learning vs Generative AI vs Automation vs Agentic AI: simplified frameworks for non-technical users
• Agentic AI applied to fashion: what agents can actually do today and what remains unrealistic
• The unified fashion AI value chain: products, images, customers, transactions, stores, suppliers and social trends
• Case discussion: how luxury, fast fashion, sportswear and digital-first brands are experimenting with AI
• Output: AI literacy map, what every fashion executive needs to understand before making decisions

Day 2 — Prompting, Governance and Responsible AI

09 Oct 2026

• Governance, legal and ethical frameworks shaping AI in fashion
• EU AI Act, privacy, IP, copyright, brand protection and data security
• Talking to AI: prompts, NLP, memory, guardrails and enterprise assistants
• The role of data quality, ownership and access
• Bias, reputational risk and sustainability implications
• Human control, validation and escalation rules
• How to define acceptable and unacceptable AI use inside a fashion company, Designing an internal AI policy for fashion companies
• Enterprise AI Assistants Lab: Microsoft Copilot, Claude and AI workflows for fashion businesses
• Output: AI governance checklist for fashion companies

Day 1 — Trend Forecasting and Creative Intelligence

16 Oct 2026

• AI for trend forecasting: data sources, signals and limits
• Social listening, search trends, cultural data, sales data and market signals
• From trend detection to creative interpretation
• Generative AI for moodboards, creative territories, materials, colour palettes and collection narratives
• The role of AI in creative direction: support, not substitution
• Risks: aesthetic flattening, brand dilution, plagiarism and over-standardisation
• Tools / demo: Midjourney, Stable Diffusion, Adobe Firefly or equivalent tools for moodboards and visual exploration
• Practice lab: build an AI-assisted moodboard for a seasonal concept

Day 2 — Product Development, Digital Twins and Virtual Prototyping

23 Oct 2026

• AI-assisted product design: silhouettes, details, variants and product storytelling
• From sketch to prototype: generative tools, 3D, virtual sampling and digital twins
• Product data foundations: PLM, PIM, DAM, taxonomy, attributes and Digital Product Passport
• AI for fit, sizing, material simulation and product iteration
• Connecting design, merchandising and supply chain earlier in the process
• Human creative control: where AI helps and where it should not decide
• Practice lab: create an AI-assisted product concept with description, visual direction and product attributes
• Output: product concept sheet generated with AI support

Day 1 — Sourcing, Production and Supply Chain Intelligence

30 Oct 2026

• AI for demand forecasting and production planning
• Supplier selection, sourcing intelligence and risk monitoring – Digital Product Passport, traceability and compliance
• Quality control, defect detection and computer vision in production
• Inventory optimisation and stock allocation
• RFID, IoT and real-time supply chain visibility

Case Studies & Labs

• Case study: improving availability and reducing overstock through predictive planning
• Practice lab: map a sourcing or production process and identify where AI can reduce cost, delay or risk

Day 2 — Logistics, Returns, Circularity and Sustainability

06 Nov 2026

• AI for logistics, distribution and warehouse optimisation
• Automated warehouses, packing systems, shipping and delivery predictions
• Returns prediction and reverse logistics
• AI for sustainability: waste reduction, material innovation, recycling and circular business models
• Textile recycling, resale, repair and recommerce enabled by data and AI
• Sustainability claims and reputational risk
• Case study: predictive logistics and improved delivery timeframes in ecommerce warehouses
• Practice lab: optimise a logistics or return flow using automation and AI
• Output: AI opportunity map for supply chain and operations
• Module 3 — AI for Sourcing, Production, Supply Chain & Sustainability — subtotal

Day 1 — Merchandising, Buying and Commercial Planning

13 Nov 2026

• AI for assortment planning and buying decisions
• Open-to-Buy (OTB): AI-assisted range planning, seasonal budget and in-season rebalancing
• Demand prediction by market, store, channel and customer segment
• Smart pricing, markdown optimisation, promotional planning and competitive intelligence and price monitoring
• Allocation, replenishment and stock balancing
• Fashion KPIs: sell-through, margin, full-price sell-out, stock turn and markdown rate
• Wholesale sell-in: AI for B2B order management, buyer portals, showroom analytics and trade show intelligence

Case Studies & Labs

• Case discussion: luxury vs fast fashion vs sportswear — different AI priorities in merchandising
• Practice lab: create a merchandising plan using AI support

Day 2 — Retail, Ecommerce and Omnichannel Performance

20 Nov 2026

• AI for physical store operations: visual merchandising, traffic analysis, layout optimisation and in-store shopper behaviour
• AI for Store Intelligence, Clienteling & Luxury Omnichannel Experience
• AI for ecommerce personalisation and product recommendations
• Visual search, virtual try-on and assisted product discovery
• Conversational commerce and AI shopping assistants
• Under-the-radar AI: payments, fraud detection, security and transaction processing
• Marketplaces, DTC and wholesale distribution: different AI use cases

Case Studies & Labs

• Practice lab: design an AI activation for in-store experience or ecommerce — participant’s choice
• Output: commercial AI use case canvas

Day 1 — Data Strategy, BI and Predictive Intelligence

27 Nov 2026

• The data lifecycle: collection, cleaning, integration, analysis and decision-making
• Structured vs unstructured data in fashion
• Data models for product, customer, sales, inventory and marketing
• Analytics and Business Intelligence: dashboards, metrics and predictive intelligence
• From descriptive reporting to predictive and prescriptive decision-making
• Data governance: ownership, quality, accessibility and accountability

Practice Lab:

• Practice lab: design the data flow for one key fashion business process

Day 2 — AI for Finance, Planning and People Performance

04 Dec 2026

• AI for budgeting, forecasting and financial analysis
• Fashion P&L structure: wholesale vs retail vs ecommerce margins, COGS and markdown budget management
• Scenario planning and margin simulation
• AI for P&L control, cash flow, inventory valuation and profitability analysis
• AI in HR: recruiting, skills mapping, performance support and training
• People analytics, organisational risk and AI impact on fashion job roles
• Limits, privacy and bias in HR and finance AI applications

Practice Lab:

• Case discussion: AI for management control in a multi-channel fashion business
• Output: AI dashboard brief for finance, BI or management control

Day 1 — Brand, Content and Communication in the Age of AI

11 Dec 2026

• AI for brand strategy, communication planning and content operations
• Fashion shows, events, PR and influencer relations: AI for planning, press coverage analysis and amplification
• Producing and optimising campaigns for algorithms and social platforms
• AI-generated copy, product descriptions, editorial content and storytelling
• Brand voice, tone of voice and prompt libraries
• Digital content factory: photography, video, images and localisation at scale
• Virtual influencers and synthetic content: opportunity or risk?
• GEO for AI, LLM optimisation and discoverability in conversational search
• AI content governance: approval flows, brand consistency, legal review and localisation control

Workshops & Labs

• Workshop: optimise website content for LLMs and chatbots — product pages, collections and landing pages

Day 2 — CRM, Loyalty, Performance and Personalisation

18 Dec 2026

• AI in customer experience: loyalty, clienteling and predictive CRM
• Luxury-specific risks: exclusivity, human touch, brand control and client data sensitivity
• Segmentation, next best action and personalised campaigns
• AI for customer service: chatbots, virtual assistants and after-sales automation in fashion
• Marketing analytics, attribution, marketing mix modelling and AI
• Paid media optimisation and campaign automation, Google Ads, Meta Ads and AI-powered campaign workflows
• Balancing automation, creativity and brand protection

Workshops & Labs

• Case study: AI-generated digital advertising campaigns and personalised customer journeys
• Practice lab: build an AI-assisted campaign concept from moodboard to channel activation
• Output: AI campaign and CRM activation brief

Day 1 — AI Systems, Platforms, Vendors and Integration

08 Jan 2027

• Essential notions of AI systems: platforms, cloud, APIs and integrations
• Build vs buy vs partner
• How to select AI vendors and evaluate solutions. AI procurement and vendor due diligence
• Integration with ERP, PIM, DAM, CRM, CDP, ecommerce platforms and BI tools
• Data readiness and system architecture
• Cybersecurity, shadow AI, access control and company policies
• Vendor management: contracts, SLAs, ownership and scalability

Workshops & Labs

• Practice lab: evaluate an AI vendor using a structured checklist

Day 2 — AI Project Management, Business Case and Prototyping

15 Jan 2027

• AI project management: agile, prototyping, MVPs and pilots
• How to build an AI business case
• ROI, KPIs, success metrics and adoption metrics
• From pilot to scale: when to stop, iterate or roll out
• Change management and internal adoption
• Bias, governance and validation in implementation
• Vibe coding and no-code / low-code AI prototyping: opportunities and risks

Workshops & Labs

• Workshop: build an AI opportunity map for a fashion business
• Learning activity: prototype an AI use case or define the pilot specification
• Output: AI pilot project brief

Day 1 — AI Strategy, Organisation and Future Capabilities

22 Jan 2027

• Human + AI collaboration: future skills for managers and creatives
• How organisations change with AI: roles, responsibilities and capabilities in agentic enterprise
• AI governance model: who owns what
• New organisational structures: AI committee, business owners, data owners, legal, IT and brand guardians
• AI literacy and upskilling roadmap
• The future of AI in fashion and luxury: agents, automation, personalisation, product intelligence and new business models
• Workshop: design the AI operating model for a fashion company

Workshops & Labs

• Workshop: design the AI operating model for a fashion company

Day 2 — Final Project, Presentations and Certification

29 Jan 2027

• Final project workshop: AI Adoption Roadmap
• Review of AI adoption roadmaps
• From Copilot licences to real adoption: enterprise AI assistants in the AI roadmap
• Feedback from instructors and peers
• Common errors in AI roadmaps
• Prioritisation: quick wins, strategic bets and long-term capabilities
• Final assignment requirements and scoring criteria
• Presentations: selected group presentations + instructor synthesis, wrap-up and certification
• Output: final AI Adoption Roadmap