{"id":14338,"date":"2026-06-08T08:39:51","date_gmt":"2026-06-08T06:39:51","guid":{"rendered":"https:\/\/www.optimalways.com\/2026\/06\/commerce-ai-summit-london-what-retailers-need-to-do-now-before-ai-rewrites-the-rules-of-the-game\/"},"modified":"2026-06-08T08:39:51","modified_gmt":"2026-06-08T06:39:51","slug":"commerce-ai-summit-london-what-retailers-need-to-do-now-before-ai-rewrites-the-rules-of-the-game","status":"publish","type":"post","link":"https:\/\/www.optimalways.com\/en\/2026\/06\/commerce-ai-summit-london-what-retailers-need-to-do-now-before-ai-rewrites-the-rules-of-the-game\/","title":{"rendered":"Commerce AI Summit London: What Retailers Need to Do Now, Before AI Rewrites the Rules of the Game"},"content":{"rendered":"

Nicolas Malo, CEOof Optimal Ways<\/strong>, was pleased to participate in the very first Commerce AI Summit<\/strong> in London on June 3, 2026. Here are the key takeaways from this day of lively discussion on the future of AI in retail and commerce. <\/p>\n

This new event is being organized by Ian Jindal<\/strong> and the RetailX<\/strong> team. Ian had come to Lille in January 2026 to participate in a Franco-British debriefing on the NRF alongside Michel Koch<\/strong>. <\/p>\n

The Commerce AI Summit was designed as an open, practical, and collaborative<\/strong> forum for discussion on how artificial intelligence is transforming retail and commerce.<\/p>\n

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The event was organized around four major themes<\/strong> drawn from the Commerce DNA framework: External AI, Experience AI, Capability AI, and Strategic AI<\/strong>. Each theme addressed a different aspect of AI\u2019s impact, ranging from the AI-enhanced consumer to the AI-transformed enterprise. <\/p>\n

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For each topic, the format consisted of<\/strong> a 30-minute panel discussion with experts<\/strong>, followed by a 30-minute Q&A session<\/strong>. This allowed moderators and participants to delve deeper into the ideas discussed, share their experiences, and explore their practical implications for retailers, brands, and technology partners. <\/p>\n

The discussions were held under the Chatham House Rule<\/strong>: participants may use the information shared, but may not reveal the identities of those who provided it. For this reason, this article does not contain any direct quotes attributed to the speakers. <\/p>\n

This approach fostered particularly open discussions about the opportunities, challenges, and uncertainties associated with AI.<\/p>\n

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AI in Retail: From Executive Board Hype to Business Reality<\/h2>\n

At the opening of the RetailX Commerce AI Summit, Ian Jindal, editor-in-chief of RetailX, set the tone with a familiar observation: AI may seem new, but many of the conversations it sparks bear a striking resemblance to those from previous waves of digital transformation.<\/strong><\/p>\n

For many retail executives, the current enthusiasm surrounding AI is indeed reminiscent of other technological revolutions. The terminology may change, but the questions remain the same: Where does the value lie? How do you measure ROI? And how do you turn experimentation into business impact? <\/strong><\/p>\n

AI is no longer just a tool being tested by innovation teams. It is becoming part of the daily lives of executives, employees, customers, and competitors<\/strong>. CEOs are experimenting with tools like Claude, teams are building their own AI workflows, and consumers are arriving better informed, better equipped, and more demanding than ever.<\/strong> <\/p>\n

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AI and Retail: The Next Wave in Commerce<\/h2>\n

One message emerged clearly from the Commerce AI Summit: AI is not just a new technological trend.<\/strong> It is part of a more profound transformation in the way consumers discover, choose, and purchase products.<\/p>\n

The retail industry has already gone through several waves: brick-and-mortar stores, e-commerce, marketplaces, and now agent-based commerce.<\/strong> AI agents, voice assistants, and conversational interfaces could soon influence\u2014or even directly make\u2014purchases on behalf of consumers.<\/strong><\/p>\n

These new models will not replace the existing channels overnight. Stores, websites, apps, and marketplaces will continue to play a major role.<\/strong> But retailers must prepare for a world in which AI is becoming a new gateway to customers.<\/strong><\/p>\n

\ud83d\uded2 The next channel might not look like a channel<\/h3>\n

AI agents could become powerful shopping intermediaries<\/strong>. Consumers may no longer need to visit an e-commerce site directly. They\u2019ll simply be able to ask their assistant to recommend the best product, find a gift, or place a repeat order.<\/strong> <\/p>\n

For retailers, the challenge will be to remain visible, reliable, and accessible<\/strong> within these new AI-driven environments.<\/p>\n

But the experience with marketplaces should serve as a warning: retailers must avoid giving up too much control over their customer data, customer segmentation, and customer retention<\/strong>. AI agents present an opportunity, but they must not weaken the direct relationship with the customer<\/strong>.<\/p>\n

\ud83c\udfaf Start with the problem, not the technology<\/h3>\n

We shouldn’t use AI just because it’s AI.<\/strong><\/p>\n

Retailers should start by asking three simple questions:<\/p>\n

What problem are we trying to solve? What impact do we expect? How will we measure success? <\/strong><\/p>\n

AI delivers the most value when it addresses specific use cases: fraud prevention, customer service, product discovery, or operational efficiency.<\/strong><\/p>\n

Experimentation remains essential, but it must lead to the demonstration of a real business impact<\/strong>.<\/p>\n

\ud83d\udcca Measuring AI is difficult, but essential<\/h3>\n

AI performance must be measured based on the use case.<\/p>\n

For fraud detection, this might involve reducing false positives or losses<\/strong>. For customer service, it might involve reducing resolution time or improving satisfaction<\/strong>. For product discovery, it might involve increasing conversion rates, raising the average cart value, or reducing returns.<\/strong> <\/p>\n

The key is to define the expected outcome before launching the project.<\/strong><\/p>\n

\ud83e\udde0 AI culture is becoming a key skill in retail<\/h3>\n

Transformation through AI is not just about technology. It also requires culture, training, and leadership.<\/strong> <\/p>\n

Employees need to understand what AI can do, what it cannot do, and where human judgment remains essential.<\/strong><\/p>\n

The retail leader of tomorrow will likely need to combine expertise in several areas: data, products, customer experience, operations, governance, and AI workflows.<\/strong><\/p>\n

“Team manager” could soon also mean AI agent manager.<\/strong><\/p>\n

\ud83d\ude80 The Strategic Choice for Retailers<\/h3>\n

AI in retail spans many areas: automation, fraud prevention, customer service, product discovery, voice commands, agent-based commerce, and business transformation.<\/strong><\/p>\n

The challenge is to pinpoint specific opportunities<\/strong>. Retailers must identify where AI can solve concrete problems today, where it could transform consumer behavior tomorrow, and where it could revolutionize retail in the longer term.<\/strong> <\/p>\n

The next wave is already on the horizon, but retailers still have time to prepare for it.<\/strong> The winners will be those who can identify the right use cases, clearly measure their impact, and stay close to their customers<\/strong> \u2014even when the first point of contact is no longer a website, an app, or a store, but an intelligent agent<\/strong>.<\/p>\n

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\ud83e\udd16 External AI: The AI-Enhanced Consumer<\/h2>\n

External AI explores one of the most significant changes retailers must prepare for today: consumers no longer navigate their purchasing journey alone.<\/strong><\/p>\n

They are increasingly using AI-powered search, shopping bots, social discovery tools, and conversational assistants<\/strong> to search for products, compare options, and make decisions more quickly.<\/p>\n

The fundamental question, then, becomes:<\/p>\n

What is my client doing with AI, and how should I adapt to it?<\/strong><\/p>\n

\ud83d\udd04 A New Customer Journey<\/h3>\n

The traditional e-commerce journey:<\/p>\n

search \u2192 click \u2192 buy<\/strong><\/p>\n

is beginning to evolve into:<\/p>\n

ask \u2192 answer \u2192 buy<\/strong><\/p>\n

Instead of scrolling through numerous pages and sifting through extensive catalogs, consumers can ask an AI directly for a recommendation, a comparison, or a selection of products.<\/strong><\/p>\n

But the impact will vary by industry. In the luxury, beauty, and cosmetics sectors<\/strong>, the fastest response isn\u2019t necessarily the best. Emotion, trust, inspiration, and the brand experience<\/strong> remain essential. <\/p>\n

\ud83d\udd0e Visibility Is Becoming a Strategic Factor<\/h3>\n

Traffic from LLMs and AI assistants is growing, even though the revenue generated remains limited.<\/p>\n

Brands must now understand how they are perceived not only by consumers but also by AI agents that read, interpret, and recommend their products.<\/strong><\/p>\n

Structured data, content, customer reviews, availability, promotions, and conversational language are therefore becoming strategic.<\/p>\n

\ud83d\udcca AI Share of Voice<\/h3>\n

A new visibility metric is emerging: AI Share of Voice<\/strong>.<\/p>\n

Retailers will need to assess how often, how accurately, and in what way<\/strong> their brands and products appear in the responses and recommendations generated by AI.<\/p>\n

This is where GEO\u2014Generative Engine Optimization\u2014<\/strong> comes into its own.<\/p>\n

Just as SEO helped optimize visibility on search engines, GEO will help improve visibility in the AI-guided discovery tours.<\/strong><\/p>\n

\ud83d\uded2 Shopping Agents and Trust<\/h3>\n

Shopping assistants could become true confidence-building tools<\/strong>: reading reviews, comparing products, summarizing customer feedback, and helping consumers make decisions.<\/p>\n

This creates new requirements: accurate product data, relevant reviews, up-to-date promotions, and reliable availability.<\/strong><\/p>\n

The trust<\/strong> becomes central.<\/p>\n

\ud83d\ude80 What Retailers Need to Do Now<\/h3>\n

The priorities are clear: improve content quality, structure product data, measure visibility in AI systems, test user experiences for agents, verify how promotions are interpreted by AI systems, and build consumer trust.<\/strong><\/p>\n

The AI-enhanced consumer is already emerging.<\/p>\n

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\ud83d\udecd\ufe0f Experience AI: Retail Enhanced by AI<\/h2>\n

Experience AI focuses on how retailers use artificial intelligence to improve the customer experience, increase conversion rates, and strengthen their competitive advantage.<\/strong><\/p>\n

This includes AI features on websites and apps, chatbots, personalization engines, and product experiences that remain under the retailer’s control.<\/p>\n

The central question is:<\/p>\n

How can AI make the customer experience more relevant, useful, and value-driven?<\/strong><\/p>\n

\ud83e\udde0 Personalization Gets a Second Chance<\/h3>\n

Personalization isn’t new. What’s changing with AI is the ability to understand intent, use new formats such as images or multimedia, and reduce friction all the way to conversion.<\/strong> <\/p>\n

But personalization only works if the customer perceives real value in return.<\/p>\n

\ud83d\udcca Data remains the foundation<\/h3>\n

AI does not replace the fundamentals.<\/strong><\/p>\n

Retailers always need data that is properly collected, organized, reliable, and used in accordance with consent.<\/strong><\/p>\n

Without solid data, AI-powered experiences risk becoming inconsistent, irrelevant, or impossible to scale up for industrial production.<\/strong><\/p>\n

\ud83e\udd1d Humans need authenticity; bots need efficiency<\/h3>\n

Retailers must now design their experiences for two audiences:<\/p>\n

People need emotion, trust, and authenticity.<\/strong><\/p>\n

Bots need clarity, structure, and efficiency.<\/strong><\/p>\n

\ud83d\udd0e From Keywords to Conversation<\/h3>\n

E-commerce has long been built around keywords. AI is now pushing retailers toward a more conversational and intent-based<\/strong> approach .<\/strong> <\/p>\n

Product descriptions, customer reviews, and the language actually used by consumers will become increasingly important.<\/p>\n

\u2699\ufe0f Build, Buy & Test<\/h3>\n

The question of ” build versus buy<\/strong> ” remains central.<\/p>\n

Purchasing a solution allows retailers to quickly test a proof of concept, but they must plan ahead for scaling, costs, and dependence on suppliers.<\/strong><\/p>\n

The message is simple: Test before moving to mass production.<\/strong><\/p>\n

\ud83e\udde9 Flexible architecture is becoming essential<\/h3>\n

A composable architecture makes it easier<\/strong> for retailers to test, combine, and replace AI solutions.<\/strong><\/p>\n

This flexibility will be essential in an environment that will likely combine internal capabilities, external solutions, and human expertise.<\/strong><\/p>\n

\ud83d\ude80 AI-Enhanced Retail<\/h3>\n

Experience AI isn’t about using AI just for the sake of using AI. It’s about creating experiences that attract, convert, and retain customers.<\/strong> <\/p>\n

The retailers that will succeed are those that can combine reliable data, a rigorous testing process, effective cost control, a flexible architecture, and the right balance between human creativity and AI-driven automation.<\/strong><\/p>\n

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