By Sam in AI & E-commerce — 30 Jan 2026

Man vs Machine: Luxury brands bet on the human touch

As AI capabilities become embedded within all operations, from marketing to inventory management and customer experience, brands are increasingly doubling down on what technology cannot replicate: emotional connection.

Photo by Laura Chouette / Unsplash

PLUS: 47 billion reasons why Amazon hates agentic commerce

“At the very top end of luxury, you’re not selling a product, you’re selling a feeling. That emotional connection is what brings them [customers] back" - Michael Ward, Managing Director at Harrods

Afternoon All,

What emotion drives someone to pay £7000 for a Tom Ford trench coat? When they could pay £2000 for a Burberry one, or less than £200 for one from Nobody's Child?

That emotional driver is something AI cannot understand or replicate yet (if ever), and could be the key to our survival in this new economy.

We explore that and more today...

Today's dots:

Luxury brands get personal in the age of AI
The key traits of retailers getting AI right
Why every business needs to be in the hospitality business
47 billion reasons why Amazon hates agentic commerce

Emotional growth. Luxury brands get personal in the age of AI.

Here's the thing: Over the past decade, the luxury category has relentlessly optimised for ROI, investing heavily in data, CRM systems and performance marketing. Now, as AI capabilities become embedded within all operations, from marketing to inventory management and customer experience, brands are increasingly doubling down on what technology cannot replicate: emotional connection.

Let's unpack that:

At the recent Shoptalk Luxe conference Michael Ward said data and specifically AI is critical in understanding customer behaviour. However it cannot replace human intangibles “AI helps us see patterns at scale,” he said. “But if you reduce luxury to efficiency, you lose what makes it special.”
In the near future, AI will be core infrastructure. Shopping via AI agents will be as common place as online shopping is today. According to luxury leaders this makes inimitable human skillsets more important, not less.
Anne Azais de Vergeron, CEO of Repossi, says “Emotion doesn’t replace data, it gives data a purpose.” At Loro Piana, store advisors don’t get raw data, but instead grouped insights into a customer’s preferences based on their search behavior, so they can deliver more informed, high-touch service in-store.
With this combination of digital and physical touchpoints, and fragmented consumer journeys, traditional metrics to measure business success may not tell the full story of what is really driving sales demand.

If you remember nothing else: As technology automates more operational tasks, the role of people becomes more visible and more valuable as they become the stewards of the human connection with customers. Brands, especially luxury names, have to rethink what success looks like. Some traditional ecommerce metrics no longer tell the full story.

The difference between retailers getting AI right vs wrong

Here's the thing: Margins are thin, customer expectations keep rising, and the pressure to automate, cut costs and grow sales without losing service quality keeps getting bigger. Plus if you're not "doing AI" then you're falling behind right? PwC reports 88% of executives plan to increase AI investment this year. According to Anthropic, there is a clear 3 step framework to successfully implementing AI in retail.

Let's unpack that:

PwC reports 88% of executives plan to increase AI investment this year. According to Anthropic, there is a clear 3 step framework to making AI transformation in retail a productive process.
Step 1: Lay the foundation. AI offers enormous opportunity to improve
inventory and operational efficiency that reduce markdowns, aswell as personalised customer experiences that increase lifetime value. Aligining on "one source of truth" across fragmented systems, and different stakeholders is the first hurdle.
Step 2: Launch a pilot "Successful pilots in retail deliver quick wins while building organizational capability and demonstrating clear ROI" e.g using AI/ML time-series algorithms to improve sales and inventory forecasting. Keeping a human in the loop means existing institutional knowledge can be used to validate any recommendations
Step 3: Scale impact Scaling any successful pilot requires developing deep AI capability across every role in your retail organisation. Education in every role requires a different focus because their interaction with the new system will be different. This alignment should be clear if step 1 was done properly...

If you remember nothing else: Retail organisations who achieve tangible gains from AI implementation, do so when they reimagine core workflows
around new AI capabilities. Focused and strategic planning, strong data foundations, and clear success metrics are vital in making this non-negotiable transformation work.

Why every business needs to be in the hospitality business

Here's the thing: While AI has massive potential to improve efficiency, accuracy and productivity in the workplace, it’s less clear how it will evolve to replicate the human touch that all businesses face.

Let's unpack that:

The human-centred skills found in the hospitality sector (empathy, creativity, adaptability, kindness, resilience and cultural intelligence) are still the hardest skills to replicate in and by AI. They may also be the most valuable.
By 2030, industries such as banking, healthcare and retail are expected to rely heavily on agentic AI products (i.e systems that can solve complex problems in real time) to interact with customers.
While AI can process data and do transactions, it cannot truly care, comfort or create trust. These are crucial measures in ensuring that the human element does not fade into the background.

If you remember nothing else: In a world where purchases become transactional and commoditised by AI agents, hospitality skills can deliver the “why” – the meaning behind the interaction. That deeper understanding of a customer can be the differentiation brands need to thrive in the new economy.

47 billion reasons why Amazon hates agentic commerce

Here's the thing: AI-first browsers such as Perplexity’s Comet and OpenAI’s Atlas can now search, compare, and initiate purchases with minimal human involvement. It also challenges many ecommerce conventions, including the role marketplaces play in product discovery, transactions, and advertising.

Let's unpack that:

In November 2025, Amazon sued Perplexity, alleging that the Comet web browser masquerades as a human, accesses Amazon accounts, and places orders in violation of Amazon’s terms of service and computer fraud laws. Just this month, eBay updated its user agreement to outlaw end-to-end LLM-driven checkouts. In reality, these moves are almost certainly about control.
It makes sense. Marketplaces exist to aggregate and centralise shopping. It is their USP. Hence agentic commerce is a threat. According to its 2025 Q3 filing Amazon generated $47 billion in “advertising services” revenue - sponsored listings, recommendation units, and paid placements. All deeply embedded in search results and category pages which are completely bypassed by shopping agents.
Ecommerce marketplaces also observe, track, and record onsite behavioural information. These signals feed ranking algorithms, recommendation systems, and personalisation models. That data disappears when an external AI agent performs comparisons and decision-making offsite. The marketplace only sees the final purchase.

If you remember nothing else: After the lawyers get rich AI agents will eventually access marketplaces via official APIs, subject to rate limits, identity verification, and possibly commercial arrangements. For SME ecommerce businesses, the agent-marketplace relationship will likely be a key revenue channel and primary route for getting products into Perplexity, ChatGPT, and similar platforms.