Senior Editor
Sarah Chen is a technology journalist specialising in artificial intelligence applications in commerce and retail. Originally from the San Francisco Bay Area, she studied computer science before pivoting into tech journalism and has been covering e-commerce and retail technology since 2014.
After several years reporting from the US and Europe, she relocated to Bangkok — a city whose street-level commerce, live-selling culture, and rapid adoption of mobile payments she finds a far more interesting vantage point for watching where consumer behaviour is heading than any conference room in California. She has been saying this at the start of every conversation for about four years now and shows no signs of stopping.
Her particular focus is AI personalisation, consumer trust, and the gap between what retail technology promises and what shoppers actually experience. She has a talent for talking to the people who use the products, not just the people who built them, and her reporting tends to be considerably more sceptical than the press releases it follows. When not writing, she advises early-stage startups on go-to-market strategy — which mostly means telling founders their homepage needs a complete rewrite and watching them agree warmly before doing nothing about it.
She speaks at industry events across Southeast Asia and Europe, and has strong opinions about checkout UX that she will share whether you ask or not.
LLMs are genuinely changing how recommendation engines work. UK shoppers are using AI tools in growing numbers. Most of them can't name a single experience that impressed them. That gap is the story.
This week's biggest stories in AI and commerce: Amazon's checkout-free expansion gathers pace, Shopify Magic reaches all merchants, and the EU's algorithmic pricing net draws tighter.
As fraudsters adopt AI tools, payment providers and retailers are deploying increasingly sophisticated machine learning to protect transactions. Neither side is winning decisively, but the data advantage currently sits with the defenders.
After years of underwhelming chatbot experiences, AI-powered conversational commerce is finally delivering on its promise. Here's what's changed, and what the numbers actually say.
Tilt launched Snap in April 2026, an AI feature that creates product listings from live video in under a second. Early testing shows a 47% uplift in sell-through rate. The mechanism is less glamorous than it sounds, and more interesting than the headline suggests.
AI-powered loyalty programmes in 2026 can predict churn 60 days out, personalise incentives at the individual level, and adjust offers in real-time based on behavioural signals. Marks & Spencer, Tesco and Boots are already doing versions of this. The results are meaningful. The questions about data and consent are overdue.
Adobe's March 2026 data shows AI-referred traffic converting 42% better than non-AI channels. That's a record, and a number that needs careful interpretation: selection effects, early adopter behaviour, and the specific nature of AI-mediated discovery all shape what it means for your planning.
TikTok Shop's 2025 full-year US GMV came in at $15.82 billion — up 108% year-on-year. The global figure was $64.3 billion. The AI recommendation engine driving that growth isn't a feature; it's the entire product. Brands that still haven't engaged with social commerce are running out of comfortable reasons not to.
Smart carts, autonomous checkout, computer vision for shelf intelligence, inventory robots. All have had conference moments. In early 2026, some are scaling. Some are quietly struggling to find their use case outside the pilot environment. The UK high street has a specific lens on this.
True one-to-one personalisation (not segments, not 'customers like you') is in production at scale in early 2026. The infrastructure is real. The results are real. So are the questions about data, consent, and where helpful ends and uncomfortable begins.
Jeremy Howard proposed LLMs.txt in September 2024 as a way for websites to communicate with AI crawlers. By October 2025, 844,000 sites had implemented it. The major AI crawlers are still largely ignoring it. So where does that leave us?
Google AI Overviews now appear on 48% of searches, with an average zero-click rate of 83% when they do. Between 58% and 68% of all Google searches now end without a click. The organic traffic model that UK retailers have relied on for fifteen years is structurally broken. Here's how to think about that.
Only 39% of Americans trust AI agents to make everyday purchases on their behalf. That sounds like a problem for agentic commerce. Look more closely and it's more interesting than that: trust is real, category-dependent, and building along a predictable path.
AI-generated product content is now standard for large catalogues. The tooling works. The quality variance is the problem nobody planned for, and on a 50,000-SKU catalogue, even a 1% error rate is 500 wrong product descriptions.
Adobe's Q1 2026 data shows AI-referred traffic to US retail sites grew 393% year-on-year. A separate Adobe finding: product pages across the retail sector score an average 66% on machine readability. The traffic is arriving. The infrastructure to capture it is not.
Adobe Analytics recorded $257.8 billion in US online spending across the full 2025 holiday season. UK shoppers spent a record £26.9 billion. AI-referred traffic converted 54% better on Thanksgiving. Those are the headline numbers. The less-headline numbers are, as usual, the more interesting ones.
The infrastructure for agentic commerce arrived in 2025. Payment rails, checkout integrations, holiday-season data — all of it landed at once. The harder question is why consumer behaviour hasn't caught up yet.
Salesforce says AI influenced $67 billion in Cyber Week sales. Adobe tracked a 693% surge in AI traffic to retail sites. The numbers are real. What they mean takes a little more work.
The Leaders Connected relaunch brought together Anna Barsby from Tessiant and Kevin Evans from Rosslyn for an evening of candid fireside conversation about data, AI, and organisational reality in the North of England. Organised by Jody Marks and Grant Spencer, it was the kind of event the Northern tech community does quietly well.
On 29 September 2025, OpenAI launched Instant Checkout, the ability to buy products directly through ChatGPT, powered by Stripe and starting with Etsy and Shopify merchants. Etsy's stock jumped 16%. The interesting questions start after the headlines.
TikTok Shop now accounts for nearly 20% of US social commerce. Among under-35s in the UK, 89% say they'd consider buying through it. The algorithm is doing most of the selling work. That's worth understanding.
The gap between virtual try-on demos and virtual try-on that consumers actually use has been wide for a long time. In 2025, it narrowed meaningfully. The question now is whether it closes all the way — and what retailers should be doing about it.
In May 2025, Klarna's CEO admitted they'd pushed AI-driven job cuts too far and began rehiring human agents. The story got covered as a cautionary tale. It's more useful than that — and more instructive about what actually went wrong.
Between AI Mode, agentic checkout, virtual try-on expansion, and Project Mariner, Google confirmed more commerce-relevant technology at I/O 2025 than at any developer conference in recent memory. Most coverage led with the chatbot.
Easter 2025 was the first major UK retail season where AI-powered demand forecasting, personalised promotional timing, and AI-assisted customer service all operated at meaningful scale simultaneously. The results weren't transformative — but they were instructive.
The word 'agentic' is now applied to almost everything with a language model in it. Here's a working definition based on how the technology actually functions, and a clearer view of what's in production versus what's still mostly demos.
Schema.org Product markup and JSON-LD have been around for over a decade. In 2025, they became the infrastructure that determines whether AI systems can accurately understand and recommend your products. The SEO conversation became a GEO conversation. The stakes got real.
A year ago the question was whether to run pilots. Now it's what to put into production. That shift sounds small. It isn't.
UK online spend on Black Friday 2024 hit £1.12 billion — a 7.2% year-on-year increase and the strongest Black Friday since 2021. The AI traffic story was early but present. The mobile payment story was significant. And BNPL hit £117 million in a single day.
In September 2024, Answer.AI's Jeremy Howard proposed llms.txt — a standard for structuring web content so AI systems can read it more effectively. The technical case is interesting. Whether it matters for ecommerce is a more honest question.
Retail media networks have quietly become one of the fastest-growing advertising markets in the world. Now AI is changing how campaigns get built, targeted, and measured — and not always in ways advertisers should be comfortable with.
The term GEO (Generative Engine Optimisation) is starting to circulate. Ignore the jargon, but pay attention to the underlying shift: AI-powered search is changing what good product content looks like.
Shopify's AI assistant is in gradual rollout to thousands of stores. The democratisation story is real. But what does it actually mean in practice for a small UK retailer, and where does it stop?
OpenAI's new model processes text, audio, and images natively in a single pass. The voice demos got all the coverage. The more interesting story for retail is narrower and more actionable.
Amazon's new AI shopping assistant is imperfect and occasionally baffling. It's also probably the most commercially significant thing to happen to product discovery in years. Not because of what it does now, but because of what it implies about product content strategy.
Easter is one of the bigger seasonal retail events in the UK calendar, and one of the most technically demanding for ecommerce teams — compressed timeframes, perishable stock, and demand patterns that are both predictable and notoriously hard to get exactly right. It's a good stress test for AI planning tools.
When Klarna revealed its AI assistant had handled 2.3 million customer conversations in a single month, the industry took notice. The story behind the numbers is worth examining carefully.