E-commerce Solutions Using AI

Agentic AI: The Next Major Disruption in Retail and E-Commerce Beyond Chatbots—A New Era of AI Autonomy While ChatGPT and generative AI have dominated discussions on AI-driven automation, the real game-changer for industries like retail and e-commerce is Agentic AI. Unlike traditional AI assistants, Agentic AI operates autonomously, making decisions, handling complex tasks without human intervention, and streamlining business processes in real-time. This shift could redefine customer experiences, supply chain management, and online shopping efficiency. How Agentic AI is Reshaping E-Commerce Retail, especially e-commerce, is a prime sector for Agentic AI adoption because it is built on digital interactions and data-driven decision-making. Key applications include: • AI Shopping Assistants – Fully autonomous AI agents can browse, recommend, and purchase products tailored to individual customer preferences. • Automated Supply Chain Optimization – AI can predict demand fluctuations, adjust inventory levels, and optimize logistics in real time, reducing costs. • Personalized Marketing & Customer Engagement – Agentic AI can analyze customer behavior and autonomously launch targeted promotions and product suggestions, enhancing conversion rates. • Fraud Detection & AI-Driven Cybersecurity – Autonomous AI systems monitor transactions, identify fraud risks, and secure digital transactions in real time. Why Small Businesses Can Compete Previously, large enterprises had the resources to deploy AI-driven automation, but cloud-based agentic AI services now offer scalable, cost-effective solutions that even small businesses can integrate. As AI evolves from a supportive tool to an autonomous operator, businesses of all sizes can enhance efficiency, reduce manual effort, and drive profitability. What’s Next for Retail and Agentic AI? The future of e-commerce and retail will likely see entirely AI-driven online stores, automated warehouses, and real-time AI customer service representatives that seamlessly handle end-to-end shopping experiences. As agentic AI continues advancing, businesses that embrace it early will have a competitive edge, while those that hesitate risk falling behind.

𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐣𝐮𝐬𝐭 𝐫𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐢𝐧𝐠 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬. 𝐍𝐨𝐰, 𝐭𝐡𝐞𝐲’𝐫𝐞 𝐛𝐮𝐲𝐢𝐧𝐠 𝐭𝐡𝐞𝐦 𝐟𝐨𝐫 𝐮𝐬. In recent weeks, Visa, Mastercard, and PayPal each unveiled major initiatives that move us closer to agentic commerce - a future where AI agents search, decide, and purchase on our behalf. 𝐇𝐞𝐫𝐞’𝐬 𝐰𝐡𝐚𝐭’𝐬 𝐡𝐚𝐩𝐩𝐞𝐧𝐢𝐧𝐠: • Visa launched Intelligent Commerce • Mastercard introduced Agent Pay • PayPal rolled out its Agent Toolkit 𝐖𝐡𝐢𝐥𝐞 𝐛𝐫𝐚𝐧𝐝𝐞𝐝 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐥𝐲, 𝐭𝐡𝐞𝐲 𝐚𝐥𝐥 𝐝𝐨 𝐭𝐡𝐞 𝐬𝐚𝐦𝐞 𝐭𝐡𝐢𝐧𝐠: Empower AI agents to act as autonomous shoppers - securely, reliably, and under user control. 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐞𝐚𝐧 𝐟𝐨𝐫 𝐞-𝐜𝐨𝐦𝐦𝐞𝐫𝐜𝐞? ➡️ Frictionless buying: No more checkout pages or logins. Agents will handle the full funnel - from discovery to delivery. ➡️ Hyper-personalization: Agents know preferences, price thresholds, even timing - optimizing not just what is bought, but how and when. ➡️ New interfaces: Shopping may move from screens to voice, messaging, or even background automation. We’re witnessing the start of a new paradigm. E-commerce is becoming AI-native. Curious to hear your thoughts: Would you let an AI agent handle your next purchase? Or your next 100?

AI is about to steal traffic from your ecommerce site. And you should let it. For years, ecommerce was simple: 1️⃣ People googled. 2️⃣ Clicked your ad or SEO result. 3️⃣ Landed on your site. 4️⃣ You prayed they didn’t bounce. That funnel is being rewritten in real time: OpenAI just turned ChatGPT into a shopping interface where people can buy from Etsy — and soon from hundreds of thousands of Shopify stores — without ever visiting a website, using instant checkout and Stripe under the hood. Shopify launched an AI Store Builder that spins up full stores (layouts, images, copy) from a few keywords, so more merchants will be AI-ready by default. Amazon is rolling out Lens Live and “Help Me Decide”: camera-based and conversational AI that recommends what to buy and explains why, directly inside the app. The pattern is clear: Traffic is moving from websites to agents. In 24 months, your real “homepage” won’t be your hero banner. It will be how an AI agent describes you to a customer. So what should serious ecommerce teams do? 1️⃣ Design for agents, not just humans. Structure your catalog, metadata, reviews, and margins so AI can instantly understand: What you sell Who it’s for When you beat alternatives 2️⃣ Expose clean APIs and offers. Agents don’t browse, they call APIs. Make it trivial to: Fetch products, prices, availability Understand shipping, returns, guarantees Execute a low-friction checkout 3️⃣ Treat AI agents as a new acquisition channel. Like SEO or paid social, you’ll need: “Agentic commerce” playbooks (how you appear in ChatGPT, Rufus, etc.) Attribution for AI-driven sales Partnerships with apps and networks in the post-purchase and cross-store layer (this is exactly the space I’m building in with Adalore). 4️⃣ Protect your brand while you scale. Klarna showed both sides: huge cost savings from AI, then a partial step back after CX issues. The winning pattern isn’t “AI instead of humans” — it’s AI on the front line, humans as the safety net. The opportunity is massive: Agents handle discovery and comparison. Your job is to become the obvious answer those agents return. The brands that understand this first won’t just optimize conversion rates. They’ll own the interface between AI and demand. What’s your take? Are you already designing your ecommerce stack for AI agents, or still only for human browsers?

𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗖𝗼𝗺𝗺𝗲𝗿𝗰𝗲: 𝗛𝗼𝘄 𝘁𝗵𝗲 OpenAI & Stripe 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗶𝘀 𝗿𝗲𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝘂𝗹𝗲𝘀 𝗳𝗼𝗿 𝗲-𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲. The recent announcement from OpenAI and Stripe deepening their partnership on "Agentic Commerce" marks a turning point for the B2C e-commerce landscape. With "Instant Checkout" in ChatGPT and the underlying Agentic Commerce Protocol (ACP), the vision of AI agents shopping autonomously on our behalf is becoming a reality. But what does this mean for software vendors, especially in the small and medium-sized business (SMB) segment? 1. 𝗧𝗵𝗲 𝗗𝗲𝗰𝗼𝘂𝗽𝗹𝗶𝗻𝗴 𝗼𝗳 𝗨𝘀𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲 𝗮𝗻𝗱 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻 The ACP creates a standardized interface between AI agents, merchants, and payment providers. Stripe's brilliant introduction of Shared Payment Tokens (SPTs) allows an agent to securely initiate a payment without ever handling sensitive credit card data. It's essentially OAuth for payments—a milestone for security. 2. 𝗧𝗵𝗲 𝗦𝗵𝗶𝗳𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗩𝗮𝗹𝘂𝗲 𝗣𝗿𝗼𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝗼𝗳 𝗘-𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 Traditional e-commerce platforms bundle the frontend (storefront), backend (data management), and checkout. This bundle is now being unraveled: The frontend is increasingly the AI agent (e.g., ChatGPT). The checkout is handled by standardized protocols like ACP and providers like Stripe. The consequence: The value of an e-commerce platform no longer lies in a beautiful storefront or an optimized checkout funnel. 3. 𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗶𝘀 𝗗𝗮𝘁𝗮 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 For merchants, this means a strategic realignment. The key question is no longer "What does my shop look like?" but "How well do AI agents understand my products?". The answer lies in perfectly structured, machine-readable product data. ➡️ PIM systems are evolving from a "nice-to-have" to an essential core component of any e-commerce architecture. ➡️ Real-time APIs for inventory, pricing, and fulfillment status are no longer optional. 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 𝗳𝗼𝗿 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗩𝗲𝗻𝗱𝗼𝗿𝘀:  The future isn't in building more "all-in-one" shops. The opportunity for vendors in the SMB segment is to position themselves as the best "headless" backend for the age of Agentic Commerce. They must provide merchants with the tools to seamlessly and compliantly (via ACP) integrate their product data and processes into the ecosystems of AI agents. The e-commerce platform becomes the central data hub and process orchestrator in the background. The question, therefore, is not if, but how quickly software vendors will adapt to this new, API-driven reality. Or am I missing something? What role is left for the classic all-in-one e-commerce suite in a world where AI agents do the shopping? I look forward to hearing your perspectives. Whats your take on that Daniel Hinderink Shaun McCran Dr. Roman Zenner Michael Türk Christian Münch

Now that we're halfway through 2025, where do we stand with AI for Retail? AI = New Competitive Moat for Retailers - Incumbents like Amazon and Walmart are using AI to reinvent customer experience, logistics, pricing, and personalization. - Open-source models and global competition (notably from China) lower the barrier for smaller players to adopt cutting-edge tech. AI-Powered Consumer Discovery is Mainstream - ChatGPT’s growth and capabilities are disrupting how customers discover products—search behavior is changing fast. - Generative AI is being integrated into search (Google), recommendation engines, and digital shopping assistants. Personalization at Scale Is Now Table Stakes - AI enables ultra-personalized messaging, product curation, and promotions—critical in email, SMS, and ecommerce experiences. - Segment-of-one marketing is becoming real-time and predictive, not reactive. AI Reshaping Ops & Labor - Brands like Yum! (Byte by Yum!) are using AI to optimize inventory, kitchen ops, scheduling, and staffing decisions. - Retailers can now reduce SG&A and improve store-level profitability by automating repeatable decisions. AI Voice & Translation → Global Expansion Leverage - ElevenLabs and Spotify show that real-time AI voice translation is viable—enabling retailers to localize at scale without human translators. - Big unlock for global DTC growth with minimal operational overhead. AI Infrastructure Is the New Storefront - Companies are rethinking their digital stack: AI copilots, LLMs, and autonomous workflows are becoming embedded in ecommerce platforms. - NVIDIA and others frame AI infrastructure as the next era of retail IT—akin to cloud adoption in the 2010s. CMO + CTO Alignment More Critical Than Ever - 75% of global CMOs are already using or testing generative AI tools. - Success requires alignment across data, content, and experience design to fully activate these capabilities. (Source: BOND)

A shopper just asked ChatGPT for a ceramic dinnerware set under $100. Your product exists. Your store is live. ChatGPT recommended someone else. This is happening to ecom founders every day in 2026 - and most have no idea. The game has changed: → Customers aren't just Googling anymore → They're asking AI to shop for them → And AI only recommends what it can read, trust, and verify Here are the 10 things every ecom founder needs to fix today 👇 1). Product-First Data ↳ Fill every field: size, material, use case, price ↳ If AI can't understand your product, it won't recommend it 2). CITE Framework ↳ Complete. Identifiable. Trusted. Extractable. ↳ Use structured data AI can actually read 3). PDP Optimization ↳ Your product page is your AI storefront ↳ Write descriptions AI can extract and reference by name 4). Author Authority ↳ Link your brand to a real founder ↳ AI trusts people signals over faceless pages 5). Fresh Catalog Data ↳ Keep prices, specs, and stock current ↳ AI systems favour fresh, complete information 6). Multi-Format Content ↳ FAQ blocks. Comparison tables. Ingredient pages. ↳ Structured content is easier for AI to interpret 7). Off-Site Trust ↳ Build consistent brand signals across the web ↳ Clear references help AI verify your brand exists 8). Original Research ↳ Publish category data no one else has ↳ Authority and usefulness - AI rewards both 9). GEO Audit ↳ Test ChatGPT, Perplexity, and Gemini weekly ↳ See exactly how your product appears in real buyer prompts 10). AI-SOV Tracking ↳ Monitor your share of voice vs competitors ↳ Small improvements = AI mentions your brand more often Google rankings rewarded patience. AI rankings reward preparation. Save this checklist and start with #1. P.S. Which of these 10 is your biggest gap right now? ♻️ Repost to help every ecom founder in your network prepare for this shift. 🔔 Follow Francesco Gatti for more on AI-Powered Commerce.

🚀 Big move in commerce: OpenAI just rolled out a Shopping Research tool inside ChatGPT — here’s what that means for brands, retailers and shoppers. 🔍 What the tool offers: • Lets users ask ChatGPT to describe what kind of product they want and get a personalized buyer’s guide in minutes. • Compares across products, features, trade-offs and delivers deep research rather than a quick answer. • Initially rolling out to Free, Plus, Pro and logged-in users — broad access. 💡 Why it matters for e-commerce and retail tech: • Brands and retailers gain a new channel of discovery — AI becomes a first interface, not a just a tool for search. • With generative AI, the discovery→purchase path gets shorter and more conversational, raising stakes for merchandising, personalization and visual tech. • For you working in fashion, luxury & multi-brand retail tech: this underscores the need to own the “AI-first” workflow (visuals, metadata, cross-channel signals) — the tools around you will be consumed through GPT-style experiences. • Even mid-market & enterprise stacks (think your GTM for orchestration layers) need to factor in how brands will integrate with AI-driven shopping agents — not just web search and ads. 🧭 Actionable next steps: • Audit your product metadata, visual assets and brand/style narrative — does it hold up when summarized by an agent versus traditional search? • For your GTM with orchestration layer clients: highlight how orchestration + visual/AI tech can plug into this agent-ecosystem (not just Google/Meta). • For retail brands: begin experimenting with conversational shopping flows (via ChatGPT-like agents), making sure you’re “found” when the AI asks for options. • For your generative AI consulting work: position this as a shift in “discoverability” (to borrow your framing around AEO/GEO) — agents will now ask products about your brand; make sure the brand answers.

In a world of instant gratification, your customer support builds loyalty faster than your products ever will. 𝐄𝐯𝐞𝐫𝐲 𝐝𝐞𝐥𝐚𝐲𝐞𝐝 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐚𝐠𝐞𝐧𝐭 𝐫𝐞𝐩𝐥𝐲 𝐨𝐫 𝐜𝐚𝐧𝐧𝐞𝐝 𝐜𝐡𝐚𝐭𝐛𝐨𝐭 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐞 𝐩𝐮𝐬𝐡𝐞𝐬 𝐲𝐨𝐮𝐫 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬 𝐭𝐨𝐰𝐚𝐫𝐝𝐬 𝐬𝐰𝐢𝐭𝐜𝐡𝐢𝐧𝐠 𝐭𝐚𝐛𝐬, 𝐟𝐢𝐧𝐝𝐢𝐧𝐠 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐬𝐭𝐨𝐫𝐞, 𝐚𝐧𝐝 𝐧𝐞𝐯𝐞𝐫 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐛𝐚𝐜𝐤. Let’s be real, no small/mid-sized business or e-com startup can afford an army of support reps sitting on standby for every customer ping. And those out-of-touch chatbots that struggle to understand specific situational context or make decisions using customer's historical data? ? They don’t cut it anymore either. 𝐓𝐡𝐚𝐭’𝐬 𝐰𝐡𝐲 𝐰𝐞 𝐛𝐮𝐢𝐥𝐭 𝐚𝐧 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐦𝐮𝐥𝐭𝐢-𝐚𝐠𝐞𝐧𝐭 𝐚𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭 𝐭𝐡𝐚𝐭 𝐟𝐢𝐥𝐥𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐠𝐚𝐩 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐬𝐥𝐨𝐰 𝐡𝐮𝐦𝐚𝐧 𝐫𝐞𝐩𝐥𝐢𝐞𝐬 𝐚𝐧𝐝 𝐦𝐞𝐜𝐡𝐚𝐧𝐢𝐜𝐚𝐥 𝐛𝐨𝐭𝐬. It responds instantly, 𝐠𝐞𝐭𝐬 𝐰𝐡𝐚𝐭 𝐲𝐨𝐮𝐫 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬 𝐫𝐞𝐚𝐥𝐥𝐲 𝐦𝐞𝐚𝐧, answers based on the customer’s specific problem rather than a preset rulebook, applies your business rules on the fly while generating responses, detects emotions and knows exactly when to loop in a human. Behind the scenes, multiple specialized agents work together, like the 𝐎𝐫𝐝𝐞𝐫 𝐋𝐨𝐨𝐤𝐮𝐩 𝐀𝐠𝐞𝐧𝐭, 𝐑𝐞𝐭𝐮𝐫𝐧 & 𝐏𝐨𝐥𝐢𝐜𝐲 𝐀𝐠𝐞𝐧𝐭, 𝐅𝐫𝐚𝐮𝐝 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐀𝐠𝐞𝐧𝐭, 𝐒𝐞𝐧𝐭𝐢𝐦𝐞𝐧𝐭 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐀𝐠𝐞𝐧𝐭, etc. each handling its domain to deliver precise, contextual support in seconds. The result? Less chaos for your team, lower costs for your business, and customers who actually get answers when they need them. 🎥 𝐖𝐚𝐭𝐜𝐡 𝐭𝐡𝐞 𝐝𝐞𝐦𝐨 𝐭𝐨 𝐬𝐞𝐞 𝐭𝐡𝐞𝐬𝐞 𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐚𝐠𝐞𝐧𝐭𝐬 𝐢𝐧 𝐚𝐜𝐭𝐢𝐨𝐧, 𝐬𝐨𝐥𝐯𝐢𝐧𝐠 𝐫𝐞𝐚𝐥 𝐞-𝐜𝐨𝐦𝐦𝐞𝐫𝐜𝐞 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐢𝐧 𝐫𝐞𝐚𝐥 𝐭𝐢𝐦𝐞.

The End of the E-Commerce Funnel: Welcome to the Age of Agentic Shopping 25 years of e-commerce have trained us to: Search. Click. Filter. Scroll. Compare. Add to cart. Abandon. Repeat. That entire flow? Rapidly becoming obsolete. For decades, discovery and decision were separate steps. Now, they’re collapsing into one. We’re entering a new era—where AI agents, not websites, drive the journey from intent to purchase. In just the past few weeks, the signals have been everywhere: 🛒 Retail • Walmart × OpenAI — Walmart became the Dow’s top gainer after announcing shopping via ChatGPT—customers can now search, discover, and buy through an AI agent. (MarketWatch, Oct 29) • Amazon Help Me Decide — Amazon launched an AI decision tool that recommends the “right” product based on behavior, preferences, and context—replacing filters with conversation. (About Amazon, Oct 23) 💳 Payments • PayPal × ChatGPT — PayPal integrated its wallet directly into ChatGPT, allowing purchases to happen inside the conversation itself. (Reuters, Oct 28) • Visa Intelligent Commerce — Visa introduced AI-powered checkout flows that let agents apply loyalty, promotions, and payment routing automatically. (Visa Corporate, Oct 2025) ⚙️ Infrastructure & Enablement • Stripe + PwC — Announced infrastructure for “agentic commerce,” where AI agents can discover, decide, and transact on behalf of consumers. (PwC Newsroom, Oct 2025) • Worldpay Open Agentic Protocol — Worldpay launched tools for merchants to plug into agent-driven checkout flows. (Worldpay Press Release, Oct 2025) • Adobe Agent Composer — Adobe expanded its AI-agent platform so brands can deploy autonomous shopping and service agents. (Digital Commerce 360, Oct 9) Across every layer of the stack—shopping, payments, infrastructure, and marketing—the same pattern is emerging: → Intent becomes transaction. → Discovery collapses into decision. → Commerce becomes conversational. The next interface for shopping won’t be a website. It’ll be an agent that knows you, speaks your language, and completes the task. Which raises a harder question: When discovery and checkout collapse into one interaction, what happens to brand, storytelling, and differentiation? Because in an agent-driven world, you won’t win by shouting louder— You’ll win by being understood. #ecommerce #retail #AI #GenAI #retailmedia #advertising #agenticAI #marketinginnovation #OpenAI #Walmart #Amazon #PayPal #Stripe #Adobe

Amazon just announced an AI agent that can shop third-party websites (called "Buy with Me"), not just Amazon. This follows up on the Buy with Prime program which exposed many more stores to Amazon's sizable audience. That’s a pretty clear signal: the #ecommerce world is shifting to an era where human shoppers become more and more rare. E-commerce stores need to think beyond just human visitors. AI agents will rely heavily on structured data, consistent pricing, and clear product info to make decisions. If your product pages are missing schema markup, have inaccurate pricing, unclear reviews, or murky shipping details, you might see your return rates climb, and AI cart abandonment become a real concern. Things to focus on: - Structured data (like schema.org for product info) - Real-time pricing and inventory - Transparent shipping, return, and variant details - Accurate, complete product descriptions - Clear, consistent reviews. This is less about chasing a trend and more about keeping your store accessible to all types of shoppers—human or not. At Coalition Technologies, we’ve seen the benefits of getting ahead of changes like this. Structured data improvements alone can help with visibility across search engines, marketplaces, and now AI tools. Has anyone here started adjusting for this? What areas are you focused on first? https://lnkd.in/gA-D-u6y