Retail, Luxury & Consumer Brands
Redesign how brands understand demand, create products, serve customers and operate — for an AI-native world.
Artificial intelligence is changing more than internal productivity. It is reshaping how products are discovered, interpreted, selected, purchased and experienced — across stores, e-commerce, social platforms and AI assistants.
The challenge is not to add AI to every activity. It is to decide where AI creates measurable value, how workflows should be redesigned, and what must remain human-led: creativity, judgment and human connection.
I help retailers, luxury houses and consumer brands identify high-value AI opportunities, redesign workflows around AI and automation, and turn isolated experiments into scalable operating capabilities.
Business outcomes
AI can change how brands understand their markets, develop products, engage customers and manage operations.
Turn consumer and market signals into better products and on-brand content.
Improve discovery, client relationships, conversion and loyalty.
Increase precision across merchandising, stores, inventory and supply chains.
Preserve brand integrity, margins, trust and control.
Agentic commerce
As product discovery expands into AI interfaces, brands must be ready to serve both people and the agents acting on their behalf.
This changes the requirements of digital commerce.
The customer remains human, but part of discovery, comparison and evaluation may increasingly be delegated to AI agents acting on their behalf.
Brands will still need to inspire people, create desire and build emotional connection. But they will also need to become legible, credible and relevant to the systems helping customers make decisions.
In this environment, marketing is no longer only about visibility. Brands must become admissible in the customer's decision system.
Product attributes, benefits, stories, policies and brand knowledge need to be complete, structured and accessible.
AI systems cannot accurately represent a product they cannot properly interpret.
Being visible is not enough.
Brands need distinctive positioning, trusted information and evidence that help both people and AI systems understand:
Product discovery must connect to live availability, pricing, fulfilment, service and return policies.
The journey should continue from recommendation to action without losing accuracy or brand control.
For luxury brands, the challenge is even more specific. The brand must be interpreted with the right context, codes and level of service — not reduced to a comparison of price, popularity and product attributes.
Perspective
When customers use their own AI agents to filter, compare and challenge offers, brands no longer compete only for attention.
They must become admissible in the customer's decision system.
From B2C to B2A · From personalisation to trajectory · From persuasion to proof
Read the perspectiveBy segment
Retailers, luxury houses and consumer brands share many AI opportunities, but their customers, economics and operating models are different.
AI transformation should start with the workflows that matter to each business.
Retailers operate across stores, websites, marketplaces, customer service channels and an emerging generation of AI interfaces.
The opportunity is not simply to optimise each channel independently. It is to connect customer intent, product data, inventory and operations across the entire journey.
Luxury depends on meaning, emotion, curation, scarcity and human relationships.
AI should make service more informed and operations more precise without making the experience generic or transactional.
AI expands context. The advisor preserves the relationship.
Specialised industry focus
Watchmaking combines heritage, craftsmanship, controlled rarity, confidential relationships and long-term responsibility for each timepiece. Explore how AI can strengthen the Maison without compromising what gives it value.
Explore WatchmakingConsumer brands need to understand rapidly changing demand while coordinating innovation, marketing, distribution, production and supply.
AI can help connect consumer insight to execution across the product lifecycle.
AI-native workflows
The real value is not adding AI to individual tasks.
It is redesigning how people, AI and software work together — from the original signal to the final business outcome.
AI expands the context. The advisor owns the relationship.
AI recommends. Merchandising decides.
One trusted product source, adapted for every human and AI channel.
Operating model
Many organisations begin by asking: “Where can we use AI?”
A more valuable question is: “If we designed this workflow today, how should people, AI and software work together?”
An AI-native workflow defines three roles clearly.
Scale intelligence. Preserve creativity, judgment and human connection.
Methodology
Successful AI transformation requires more than selecting tools.
It requires redesigning how work gets done — from strategy through implementation.
Map current processes, systems, information flows and decision points.
Identify where teams spend time searching, copying, coordinating, reconciling, producing repetitive content and responding to predictable exceptions.
Evaluate where AI, agents and automation can create value across:
Not every possible use case deserves to be built.
Create a prioritised portfolio focused on the strongest combination of value, feasibility, strategic relevance and organisational readiness.
Define:
I design how AI connects to the existing environment — commerce platforms, CRM, PIM, DAM, ERP, POS, OMS, data and APIs — and orchestrate the right specialists.
Delivery happens with internal teams and technology partners. My role is operating-model design, workflow architecture and transformation leadership.
Measure operational, commercial and customer impact.
Then determine what should be improved, expanded, integrated or industrialised across markets, brands and functions.
Governance
Different workflows require different levels of autonomy.
The appropriate level depends on customer exposure, reversibility, financial impact, data sensitivity and the extent to which the moment defines the brand.
AI researches, extracts, drafts and prepares.
Nothing customer-facing or business-critical is used without human review.
AI proposes an action together with the data and evidence supporting it.
A person accepts, adjusts or rejects the recommendation.
AI and automation execute low-risk, reversible and standardised actions inside defined thresholds.
Exceptions and low-confidence cases escalate to a person.
The more brand-defining, emotionally significant or financially consequential the moment, the less autonomy the system should have.
Customer-facing AI must be grounded in approved product and brand information. It should not invent product facts, prices, availability, claims or brand history.
Governance by design means protecting:
AI Opportunity Assessment
You do not need an enterprise-wide AI programme to begin. Start by identifying where AI can create the greatest measurable value without compromising the customer experience or the brand.
Critical customer, product and operational workflows
AI, agent and automation opportunities
By value, complexity, data readiness, customer exposure and risk
Initial AI-native workflows
An actionable AI Transformation Roadmap
The result is not a list of tools. It is a clear view of where AI should change how the organisation operates, what must remain human, and what to do first.
Discuss an AI Opportunity AssessmentAI transformation in Switzerland
I work at the intersection of executive leadership, finance, retail operations, digital commerce, business transformation and artificial intelligence.
I combine strategic and financial discipline shaped by executive leadership experience with hands-on understanding of brand building, retail and e-commerce.
My approach starts with the operating model and the business outcome — not with a specific AI vendor.
I start with how the organisation should operate, not with the tool it should buy.
The objective is to determine how AI, agents, automation and human expertise can work together to create stronger brands and more effective organisations.
Retail & e-commerce · Luxury, fashion, watches & beauty · Consumer brands & CPG
Sergio Castagna