Question 1

How are users and brands responding differently to AI agents in e-commerce?

Accepted Answer

_Users bypass homepages while brands invest in generative engine optimization._

It's not yet clear how AI agents will win in e-commerce. Users prefer answer-first experiences powered by ChatGPT, Gemini, and Perplexity. They now bypass the homepage entirely, leading to a decline of the website. Brands, on the other hand, are pushing GEO, which is Generative Engine Optimization. They're also creating ChatGPT-like experiences on their site search. Meanwhile, LLMs like OpenAI and Perplexity want to integrate agent capabilities and the ability to place ads.

— [AI Agents - The Internet Is Being Rewritten - Survey Users Vs Brands?](https://www.forbes.com/sites/lutzfinger/2025/07/24/ai-agentsthe-internet-is-being-rewrittensurvey-users-vs-brands/) · _Forbes_

Question 2

How do you categorize shoppers and how do LLMs serve all three types?

Accepted Answer

_LLMs now serve inspirational, research, and high-intent shoppers equally well._

In my UX research, I classify shoppers into three categories. Inspirational shoppers browse without a clear goal, often on Instagram or TikTok. Research shoppers are eager to learn and explore the best option, diving into Reddit threads or YouTube reviews. High-intent shoppers are ready to buy but looking for specific product information, visiting brand websites and combing through reviews. It's easy to see how all these needs can now be met through a conversation with LLMs like ChatGPT, Claude, Gemini, or Perplexity.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 3

How has online shopping changed over the past 25 years?

Accepted Answer

_Twenty-five years later, online shopping looks surprisingly familiar._

Surprisingly, e-commerce hasn't changed much in the last 25 years. If you compare Amazon in 1999 to Amazon today, the core structure is essentially the same. You still need to select a category, then a subcategory, and you better know what you want and where it fits. The 1999 version had long written lists. Today looks slicker with more images, but shopping is still complicated. Most of the time, subcategories let you filter by stars or price, but they don't really describe product dimensions. For those details, you still need to click into the product and read if you care. It's still a transactional act of buying.

— [AI in E-Commerce](https://www.lutzfinger.com/transcript/2024-10-03-ai-in-e-commerce/) · _The Keynote on AI_

Question 4

How has the shift from SEO to GEO changed what websites need to do for brands?

Accepted Answer

_Websites now feed AI rather than convert human visitors directly._

Websites used to be designed to convert human visitors, but now their main purpose needs to be feeding data into AI. The three-party model of searcher, Google, and end content is disintegrating into a two-party model. Decisions are getting made before consumers hit the website, so the website is no longer the main conversion point. Instead, websites should be clean data delivery mechanisms to computers, very explicit about who you sell to, your target use case, pain points, and the entire buyer journey. If it's not explicit, the AI has no way to know and might recommend somebody else.

— [Marketing to Humans Changed, with Alex Dees](https://www.lutzfinger.com/transcript/2026-03-24-marketing-to-humans-changed-with-alex-dees/) · _The Keynote on AI_

Question 5

How have search queries changed with LLM-style interfaces compared to traditional search?

Accepted Answer

_Queries grew from one word to 23 words with conversational interfaces._

The way people search is evolving dramatically. In the past, users typed one or two words like camera. Now, when shown more natural and detailed responses, they respond in kind with much longer, conversational queries like "What's a compact camera for wildlife photography that fits in a carry-on?" Semrush backs this up: average query length is now 23 words, and sessions last over 6 minutes. Users expect answers that feel personalized and human. In our interviews, shoppers said they felt more understood and better about their purchase.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 6

How is AI changing e-commerce?

Accepted Answer

_Fine-tuned models, attribution, category death._

> To explore this question, I looked at one industry: e-commerce. In my online certificate programs, I've explored AI use cases across many industries such as healthcare, media, coffee, finance and e-commerce. While healthcare tends to be slowest to adopt AI, e-commerce consistently leads.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 7

How is AI changing the way consumers shop online?

Accepted Answer

_The shift from browsing product pages to asking AI questions._

Yesterday, shoppers browsed; today, they ask. Instead of scrolling through endless menus or filtering product grids, consumers now turn to AI assistants, and the answers drive their purchases. A new front door to retail has opened, but it no longer belongs to the retailer or Google or Amazon. It belongs to ChatGPT, Claude, Gemini, and Perplexity. Just as media outlets once lost homepage traffic to Google and Facebook, retailers are now facing the same shift, only faster. Consumers aren't browsing your carefully designed website anymore; they're asking AI assistants.

— [AI Is Changing The Rules Of Web Traffic — A GEO Playbook For Online Retailers](https://www.forbes.com/sites/lutzfinger/2025/08/20/generative-engine-optimization-geo-a-playbook-for-online-retailers/) · _Forbes_

Question 8

How is r2decide using multimodality to transform the online shopping experience?

Accepted Answer

_Merging search, browse, and chat into one seamless shopping flow._

At r2decide, we're using multimodality to merge Search, Browse, and Chat into one seamless flow. In an online jewelry store, a user searching for "green" would see results based on both text and images, since our AI encodes images into a shared latent space. Users can also search for broader contexts like "wedding," "red dress," or "gothic." This capability even extends to brand names like "Swarovski," surfacing relevant items even if the shop doesn't officially carry Swarovski products.

— [Multimodal AI In 2025: From Healthcare To eCommerce And Beyond](https://www.forbes.com/sites/lutzfinger/2025/01/06/multimodal-ai-in-2025-from-healthcare-to-ecommerce-and-beyond/) · _Forbes_

Question 9

How is the Amazon homepage dying?

Accepted Answer

_Retail unbundling, AI assistants as the new aisle._

> The days of big online retail as we know it are over. Amazon, Walmart, Best Buy, and many others will all need to reinvent themselves as e-commerce changes. Once again, the homepage is dead. What will this mean for the big brands?

— [The End Of Amazon, Walmart, Best Buy? AI-Driven Retail Unbundling](https://www.forbes.com/sites/lutzfinger/2025/06/30/the-end-of-amazon-walmart-best-buy---ai-driven-retail-unbundling/) · _Forbes_

Question 10

How much more valuable is LLM traffic compared to traditional search traffic?

Accepted Answer

_LLM traffic delivers nine times the value of traditional search._

In my research I show that the traffic from LLMs is 9x as valuable as traditional search traffic. This dramatic difference underscores why the shift to AI-powered assistants is so significant for retailers. For traditional retailers, this means the customer's path to your product no longer runs through your digital storefront. When AI becomes the curator, advisor, and shopping guide, the traditional digital mall will die. This is why retailers need to fundamentally rethink their strategies for the age of AI discovery.

— [The End Of Amazon, Walmart, Best Buy? AI-Driven Retail Unbundling](https://www.forbes.com/sites/lutzfinger/2025/06/30/the-end-of-amazon-walmart-best-buy---ai-driven-retail-unbundling/) · _Forbes_

Question 11

How should brands handle product page personalization instead of using generic chatbots?

Accepted Answer

_Personalize product pages by query, not by generic chatbot._

The fix is to weave conversation into the experience instead of pasting a clone on top. The clearest example is the product page. A product page no longer has to be average, stuffed with every keyword to please search while burying the reader in detail they never asked for. It can personalize to each shopper, based on their clicks and queries, surfacing what matters and hiding what does not. Based on my own A/B tests, this approach delivered 8.6 times better conversion.

— [Three Mistakes Brands Make In The Age Of AI-Driven E-Commerce](https://www.forbes.com/sites/lutzfinger/2026/05/23/three-mistakes-brands-make-in-the-age-of-ai-driven-e-commerce/) · _Forbes_

Question 12

What advice do you have for someone considering building a fintech or launching in Africa?

Accepted Answer

_Hard lessons from exploring Africa and fintech opportunities_

For Africa, most successful businesses are traditional, non-tech businesses like furniture or services. Building something successful requires being hands-on, spending 10 years in the country, and building local relationships. It's really a lifestyle question. For fintech, the space has been extremely hot over the last four or five years. I think you either need to go very close to the rails, like payment rails and banking APIs, or do something very verticalized like payments for healthcare in Europe connecting insurance refunds. Otherwise it's super difficult to create something that works in fintech.

— [AI Products: Why ‘Good Enough’ Beats Perfect](https://www.lutzfinger.com/transcript/2024-11-14-ai-products-why-good-enough-beats-perfect/) · _The Edge_

Question 13

What are AI-generated nudges and how do they work in r2decide's system?

Accepted Answer

_Contextual recommendations that guide shoppers toward the best options._

Alongside search results, r2decide also generates AI-driven nudges, which are contextual recommendations designed to guide users effortlessly toward the most relevant options. These nudges provide chat-like advice, helping shoppers make better decisions without having to manually filter through endless product listings. By combining multimodal understanding with these intelligent prompts, the system transforms the traditional eCommerce interface into something more interactive and helpful, moving beyond the keyword-and-scroll experience that has dominated for 25 years.

— [Multimodal AI In 2025: From Healthcare To eCommerce And Beyond](https://www.forbes.com/sites/lutzfinger/2025/01/06/multimodal-ai-in-2025-from-healthcare-to-ecommerce-and-beyond/) · _Forbes_

Question 14

What are the three survival strategies for traditional e-commerce retailers?

Accepted Answer

_Three ways retailers can survive the AI-driven transformation of commerce._

First is price leadership, the Walmart model. LLMs will query retailers about price, likely via agent protocols like Model Context Protocol, and companies with substantial purchasing power will win. Second is distribution network leadership, Amazon's edge. Speed and reliability in delivery matter even as homepages fade. Third is content and advisory leadership. Retailers will win by delivering expert advice, like REI for outdoor equipment or Tom's Guide instead of Best Buy. Brands with unique and authentic takes on questions will be remembered by the LLM.

— [The End Of Amazon, Walmart, Best Buy? AI-Driven Retail Unbundling](https://www.forbes.com/sites/lutzfinger/2025/06/30/the-end-of-amazon-walmart-best-buy---ai-driven-retail-unbundling/) · _Forbes_

Question 15

What are the two major shifts coming after basic answer engine optimization?

Accepted Answer

_Paid LLM ads and autonomous agents will transform brand discovery._

Two even bigger shifts are on the horizon. First, paid discovery will change. LLMs will soon integrate advertising directly into their answers. Google, Perplexity and OpenAI have all confirmed this, probably by early 2026. New supply-side bidding platforms will emerge that can feed LLMs with conversational ad snippets tailored to the user's prompt. Second, agents everywhere via Model Context Protocols. OpenAI's protocols allow ChatGPT to check stock, answer personalized questions, even schedule deliveries. Brands will need to build an agent layer that can plug into these conversations, respond with tailored info, and complete the customer journey without sending users back to your website.

— [Answer Engine Optimization — What Brands Need To Know](https://www.forbes.com/sites/lutzfinger/2025/06/19/answer-engine-optimization-aeo--what-brands-need-to-know/) · _Forbes_

Question 16

What content should brands create to engage LLMs instead of just listing products?

Accepted Answer

_Move from product listings to authentic conversations that LLMs understand._

Your brand has unique knowledge and vision. Don't hide it behind generic product listings. If someone searches for a retirement watch, don't just list five SKUs. Explain what makes a great retirement watch: legacy, legibility, sentimental value. Engage the customer into an authentic conversation. That's the kind of context LLMs are trained to pick up. Show the real conversations you're already having. Look at your site search queries, your sales team scripts, your support chats. That's gold. Build content around real questions people ask and provide short clear answers upfront.

— [Answer Engine Optimization — What Brands Need To Know](https://www.forbes.com/sites/lutzfinger/2025/06/19/answer-engine-optimization-aeo--what-brands-need-to-know/) · _Forbes_

Question 17

What content strategy works for generative engine optimization?

Accepted Answer

_Structured, authentic Q&A content wins over keyword stuffing._

The old SEO playbook, keywords, backlinks and blogspam, won't work. AI assistants don't crawl for short-form content. They rely on authentic, Q&A-rich, structured data. Here's the playbook: leverage real customer language from support tickets, forums and user feedback. Use structured Q&A formats so LLMs can parse them easily. Integrate FAQs into product pages, placing context-rich answers directly where decisions happen. Prioritize trust and transparency with verified, concise, well-sourced information. Training LLMs is expensive, so models prioritize information that is authentic, novel, and trusted. Your goal is to teach the models who you are.

— [AI Is Changing The Rules Of Web Traffic — A GEO Playbook For Online Retailers](https://www.forbes.com/sites/lutzfinger/2025/08/20/generative-engine-optimization-geo-a-playbook-for-online-retailers/) · _Forbes_

Question 18

What conversion rate difference did you find between LLM-driven traffic and traditional search traffic?

Accepted Answer

_LLM traffic converts nearly nine times better than traditional search._

In A/B tests I conducted with Cornell Master's students, we compared regular keyword search with an AI-guided, conversational search experience inside the site search of several e-commerce stores. The difference was stunning: LLM-generated traffic converted at almost 9x higher rates than traditional search. This isn't just about volume, it's about value. LLM-driven traffic behaves more like a personal recommendation than a keyword query, which explains why users convert at dramatically higher rates when they follow those links or act on suggestions.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 19

What creates a defensible moat in the age of AI-driven e-commerce?

Accepted Answer

_AI models commoditize. Your unique shopping data does not._

I argued back in 2023 that AI models do not create moats. Models commoditize weekly. What cannot be copied is your record of real intent and real purchases. Every conversation and every click is, by definition, unique and authentic, the one signal no general model has. With it you can power discovery, personalize the page, and earn your place in AI answers. That is why the future belongs to branded AI models, trained on a brand's own behavior.

— [Three Mistakes Brands Make In The Age Of AI-Driven E-Commerce](https://www.forbes.com/sites/lutzfinger/2026/05/23/three-mistakes-brands-make-in-the-age-of-ai-driven-e-commerce/) · _Forbes_

Question 20

What did your analysis of ShopTalk 2025 vendors reveal about generative AI adoption in e-commerce?

Accepted Answer

_Only 1% of 700 vendors offer truly integrated generative AI solutions._

I analyzed all 683 vendors at ShopTalk, the biggest e-commerce conference. While 40% claim to offer AI capabilities, only 25% (169 vendors) mention generative AI explicitly. That's surprisingly low given the hype. Even more striking, I found only seven companies, just 1% of all vendors, offering merged solutions that combine search, content personalization and chatbots using multimodal capabilities. Only one of those seven was an established player; the rest were startups. About 70% of companies focused on data and AI were startups, suggesting generative AI in e-commerce is still nascent.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 21

What does the article say about specialized models versus one general model?

Accepted Answer

_Specialized models for specific business tasks will dominate, not one universal model._

There will not be one model to rule them all. Even OpenAI uses multiple specialized approaches under the hood. GPT-5 wasn't an AGI breakthrough but an orchestrator of narrower models. In the next decade we'll see many workflow-aware models designed for specific business tasks. For example, e-commerce retailers will run specialized large language models that represent their brand, understand their product hierarchy, and support their sales and marketing workflows. The future IP will be the specialized knowledge the models have.

— [Good News For Consultants. Google CEO: No Company Is Immune To AI](https://www.forbes.com/sites/lutzfinger/2025/11/18/good-news-for-consultants-google-ceo-no-company-is-immune-to-ai/) · _Forbes_

Question 22

What does your ShopTalk analysis suggest about the timeline for generative AI disruption in business?

Accepted Answer

_Generative AI disruption may take longer than Silicon Valley expects._

The floors at ShopTalk reveal that generative AI in e-commerce is still nascent, even though the direction is clear. Despite working in AI for 35 years and believing generative AI will change every industry, the current reality surprised me. Business leaders are still figuring out how to use generative AI. Maybe disruption takes longer than expected? Maybe this is like the tale about self-driving cars that we were promised for decades and are only now arriving? It seems early for generative AI, suggesting Silicon Valley may be getting ahead of itself.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 23

What happened to media companies during unbundling, and how does this relate to retail?

Accepted Answer

_Media's unbundling foreshadows what's happening to retail today._

When HTML and social media transformed media, homepages lost their power. Readers no longer started on whatevernews.com but landed on single articles via Facebook, Twitter, or Google. The article became the atomic unit of value while media brands receded. Many scaled down, and only top outlets like The New York Times or The Economist built new businesses. The winners were creators and journalists on platforms like Substack and Medium. Retail is now entering the same cycle of disruption as AI becomes the new interface for shopping.

— [The End Of Amazon, Walmart, Best Buy? AI-Driven Retail Unbundling](https://www.forbes.com/sites/lutzfinger/2025/06/30/the-end-of-amazon-walmart-best-buy---ai-driven-retail-unbundling/) · _Forbes_

Question 24

What industries has Lutz already identified as being changed by AI agents?

Accepted Answer

_Coding, finance, and e-commerce are already being transformed by AI agents._

Lutz has already looked at several areas being impacted. IDE, or how we code, has been changed. Finance, or how we underwrite risk, has been changed. E-commerce is being changed by AI in how we sell and shop, though it's not yet clear who is driving whom in that space. He mentions that many industries will be impacted by AI agents, and his research aims to understand how far different sectors have evolved in response to this transformation.

— [AI Agents - The Internet Is Being Rewritten - Survey Users Vs Brands?](https://www.forbes.com/sites/lutzfinger/2025/07/24/ai-agentsthe-internet-is-being-rewrittensurvey-users-vs-brands/) · _Forbes_

Question 25

What is Generative Engine Optimization (GEO)?

Accepted Answer

_Why being discoverable to AI assistants is the new SEO._

> For brands a new playbook is emerging: AEO. AEO is just the beginning.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 26

What is OpenAI's stated ambition for AI agents according to this article?

Accepted Answer

_OpenAI aims to become the universal interface for all internet activity._

According to a recent OpenAI memo, their aim is to become the dominant interface for everything on the internet. Sam Altman's vision is clear: he wants to be the agent for healthcare, finance, e-commerce, and many other areas. Some founders have described this vision as wanting to forward integrate into their business or be Everyone's Agent, much like Amazon once wanted to be The Everything Store. OpenAI is extending the idea that Perplexity started with Shop Like a Pro to cover everything users do online.

— [AI Agents - The Internet Is Being Rewritten - Survey Users Vs Brands?](https://www.forbes.com/sites/lutzfinger/2025/07/24/ai-agentsthe-internet-is-being-rewrittensurvey-users-vs-brands/) · _Forbes_

Question 27

What is the core discovery mechanism behind multimodal AI, and how does it relate to Amazon's recommendation approach?

Accepted Answer

_Finding close connections across data types, like Amazon's recommendations scaled up._

Multimodal AI is more of a discovery tool. Different data modalities are stored by the AI, and once a new data point is input, the AI finds topics that are close. For example, inputting sleep data from a smartwatch alongside information about atrial fibrillation episodes might find indications of sleep apnea. This is the scaled-up version of what Amazon popularized: "people who shopped for this item also bought this item." In this case, it becomes "People with this type of sleep pattern have also been diagnosed with AFIB."

— [Multimodal AI In 2025: From Healthcare To eCommerce And Beyond](https://www.forbes.com/sites/lutzfinger/2025/01/06/multimodal-ai-in-2025-from-healthcare-to-ecommerce-and-beyond/) · _Forbes_

Question 28

What is wrong with adding a chatbot that mimics ChatGPT to a retail site?

Accepted Answer

_Bolting on a ChatGPT clone creates friction, not service._

Brands rush to add a chat box trying to mimic ChatGPT, and they fail. We saw the same pattern in the early days of Google, when every site tried to build search as good as Google's and could not. I launched a consultative bot for Decent in 2024 that nobody asked for. It was fun, but users did not really use it. Amazon later shipped Rufus, a clunky bolt-on that is often more wrong than right. A chat window you have to summon is friction, not service.

— [Three Mistakes Brands Make In The Age Of AI-Driven E-Commerce](https://www.forbes.com/sites/lutzfinger/2026/05/23/three-mistakes-brands-make-in-the-age-of-ai-driven-e-commerce/) · _Forbes_

Question 29

What makes generative AI the 'Holy Grail' for personalization compared to traditional AI tools?

Accepted Answer

_Multimodal generative AI enables true one-to-one personalization at scale._

Yesterday's tools rely on manual pre-written templates that AI dynamically selects. For example, ads have to be prewritten and AI just selects the best one for a user. Filters and landing pages stay static. Personalization happens on the margin; Amazon 1999 and 2025 look essentially the same. Real personalization would require billions of unique templates, filters and images, which wasn't feasible until now. Generative AI changes this. Our ability to store all kinds of data formats like product data, user-generated content and images, this multimodality makes it possible to switch and adjust each modality for the user.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 30

What mistakes do brands make in AI-driven e-commerce?

Accepted Answer

_Common pitfalls and how to avoid them._

> And underneath it all, brands risk losing their narrative to an intermediary that now owns the customer touchpoint. Having spent years building fine-tuned AI models for online retail, I keep watching e-commerce executives respond to all of this by making the same three mistakes. Each one is avoidable, and each one is expensive.

— [Three Mistakes Brands Make In The Age Of AI-Driven E-Commerce](https://www.forbes.com/sites/lutzfinger/2026/05/23/three-mistakes-brands-make-in-the-age-of-ai-driven-e-commerce/) · _Forbes_

Question 31

What problem does your e-commerce AI startup solve that existing technology cannot?

Accepted Answer

_Enabling conversation-based product discovery for e-commerce brands_

We built fine-tuned models to help e-commerce companies offer the right products at the right moment on their websites. For example, if you go to Cartier's website, you're now used to a chat-like interface from ChatGPT where you can say, I want a retirement watch. But what does a retirement watch look like? Should it be round, with leather? Today, Cartier can't handle that. The brand understanding specific to Cartier or any other brand is not necessarily baked into ChatGPT, Perplexity, and others. We created fine-tuned models to enable these conversational search experiences that understand specific brand contexts.

— [After the Gold Rush, with Kurt Wagner](https://www.lutzfinger.com/transcript/2025-10-21-after-the-gold-rush-with-kurt-wagner/) · _The Keynote on AI_

Question 32

What replaces SEO in the LLM era?

Accepted Answer

_Strategies for being discoverable to AI assistants._

> But based on research I conducted with Cornell Master's students, that shift is happening much faster. LLM-driven traffic is already starting to outperform traditional search — not in volume, but in value. Traffic from LLMs converts at nearly 9x higher rates than traditional search. This is the biggest disruption to search since the dawn of the internet.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 33

What should I monitor to optimize my brand for AI assistants?

Accepted Answer

_Start with questions, not metrics. Understand what customers actually ask._

Don't run and start to monitor your brand. Instead, try to understand the best set of questions to monitor. The challenge for brands is to predict what users will be looking for. Companies should be tapping into customer support tickets, community forums, social media conversations, and user interviews. In other words, you need to get the questions right first. I've built data and monitoring tools for two decades, and I've seen brands obsessively measure mentions without asking the deeper question: what exactly should we measure? Understanding authentic customer language is the foundation.

— [AI Is Changing The Rules Of Web Traffic — A GEO Playbook For Online Retailers](https://www.forbes.com/sites/lutzfinger/2025/08/20/generative-engine-optimization-geo-a-playbook-for-online-retailers/) · _Forbes_

Question 34

Who is investing in these early-stage generative AI e-commerce companies you identified?

Accepted Answer

_Top VCs attend ShopTalk as startups drive generative AI innovation._

About 70% of the companies focused on data and AI at ShopTalk were startups, so it's no surprise that many top VC firms attend the event as well. I participated in a roundtable with Martin Casado from a16z at the conference. The fact that established VCs are present while most generative AI innovation comes from startups rather than established players, with only one out of the seven merged-solution vendors being an established company, shows where the smart money is watching this nascent space develop.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 35

Why are some brands invisible when I ask AI assistants for product recommendations?

Accepted Answer

_Visibility depends on what AI models learned during training._

If your brand isn't present in AI answers, you're effectively invisible. The reason is training data. Models surface answers based on the content they've been exposed to. For example, when someone asks ChatGPT about hiking jackets, it might recommend Outdoor Research, Arc'teryx, and Patagonia, but brands like Mammut, Columbia, or The North Face are absent. That's because companies like Patagonia and REI have done a better job supplying structured, high-quality information to AI systems. If you haven't taught the models who you are, you won't appear in their recommendations.

— [AI Is Changing The Rules Of Web Traffic — A GEO Playbook For Online Retailers](https://www.forbes.com/sites/lutzfinger/2025/08/20/generative-engine-optimization-geo-a-playbook-for-online-retailers/) · _Forbes_

Question 36

Why did Amazon's B2B distribution model fail for complex industrial products?

Accepted Answer

_Simple products worked, but complex specs exposed a critical gap._

Amazon's B2B distribution worked fine for simple products like paper towels, but the moment specs get tricky, its model breaks down. Most industrial products live or die on context: temperature thresholds, compliance codes, compatibility quirks. Amazon lacked this contextual ingredient. That's precisely what large-language models excel at. Transformer models can embed context, turning the messy details of industrial distribution into valuable assets for an industry still playing catch-up on technology.

— [AI For Private Equity — The Future Of B2B Distribution](https://www.forbes.com/sites/lutzfinger/2025/07/15/ai-for-private-equity---the-future-of-b2b-distribution/) · _Forbes_

Question 37

Why did you choose e-commerce to study generative AI adoption rather than other industries?

Accepted Answer

_E-commerce leads AI adoption, making it the ideal test case._

In my online certificate programs, I've explored AI use cases across healthcare, media, coffee, finance and e-commerce. Healthcare tends to be slowest to adopt AI, while e-commerce consistently leads. E-commerce already uses AI for targeting ads and emails, product recommendations, and SEO. Since e-commerce leads in AI adoption generally, I assumed they would readily embrace generative AI. That's why I chose to analyze this industry at ShopTalk, expecting to see the generative AI future already happening there if anywhere.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 38

Why did you leave your healthcare company to start an AI e-commerce company?

Accepted Answer

_From healthcare prediction models to e-commerce AI startup founder_

I was president of a NASDAQ listed company in New York in the healthcare space, running product and technology for a third party administrator. We built predictive algorithms to reduce the burden of diseases for our members. I left to build a startup focused on fine-tuned large language models for e-commerce because I saw an opportunity. The technology behind it, transformer models, exists since 2017, but how everyone uses it creates new questions. I realized I could create value by knowing things the industry didn't know yet, specifically solving search and discovery problems in e-commerce with this new architecture better than anyone else.

— [After the Gold Rush, with Kurt Wagner](https://www.lutzfinger.com/transcript/2025-10-21-after-the-gold-rush-with-kurt-wagner/) · _The Keynote on AI_

Question 39

Why do LLMs convert better than search?

Accepted Answer

_Trust, personalization, and conversion lift from AI traffic._

> Some predict that by 2028, more people will discover products and information through large language models (LLMs) like ChatGPT and Gemini than through traditional search engines. But based on research I conducted with Cornell Master's students, that shift is happening much faster. LLM-driven traffic is already starting to outperform traditional search — not in volume, but in value.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 40

Why do you say the website is dead, and what does that mean for brands?

Accepted Answer

_Websites lose traffic but gain higher intent visitors via agents._

It's hyperbolic. The website is not dead. The newspaper is not dead, the homepage is not dead. It's only reduced in importance. An agent can go look up websites, read those websites, do the research, compare it, create a metric for themselves to say what is the most explosive or most fruitiest and then give me back an answer. Your traffic goes down, but your revenue probably doesn't because you should see more high intent consumers. Consumers that used an agent to be informed and then they come to your website.

— [From Google to Cornell: Rethinking AI Workflows | Lutz Finger | Build AI Podcast 17](https://www.lutzfinger.com/transcript/2026-04-16-from-google-to-cornell-rethinking-ai-workflows-lutz-finger-build-ai-podcast-17/) · _Build AI_

Question 41

Why does creating more AI-generated content fail at generative engine optimization?

Accepted Answer

_More AI content does not win at generative engine optimization._

Executives wrongly assume that because more pages once won at SEO, more AI-generated content will win at GEO. The opposite is true. AI trained on AI degrades, and model providers actively suppress pages that read like machine-generated filler. Pumping out slop is the fastest way to become invisible to the very engines you are chasing. The fix is to give models what they actually reward: novel, unique, and authentic content. That is exactly why large language models lean so heavily on sources like Reddit and LinkedIn when they train.

— [Three Mistakes Brands Make In The Age Of AI-Driven E-Commerce](https://www.forbes.com/sites/lutzfinger/2026/05/23/three-mistakes-brands-make-in-the-age-of-ai-driven-e-commerce/) · _Forbes_

Question 42

Why does e-commerce need fine-tuned AI?

Accepted Answer

_Why general-purpose LLMs aren't enough._

> To explore this question, I looked at one industry: e-commerce. In my online certificate programs, I've explored AI use cases across many industries such as healthcare, media, coffee, finance and e-commerce. While healthcare tends to be slowest to adopt AI, e-commerce consistently leads.

— [ShopTalk 2025: Just 1% Of Vendors Use Generative AI To The Max](https://www.forbes.com/sites/lutzfinger/2025/03/21/state-of-genai--only-1---shoptalk-2025-in-numbers/) · _Forbes_

Question 43

Why does traffic from AI assistants convert better than other channels?

Accepted Answer

_AI recommendations convert nine times better through personalized trust._

Studies show that traffic originating from LLMs converts up to nine times better than other channels. Why? Because recommendations feel personal, contextual, and trustworthy. One example stands out: a consumer uploaded their blood results into ChatGPT and immediately purchased €200 worth of vitamins with no browsing, no comparison, pure trust. AI-driven traffic is still small in volume, but its impact is outsized. The personalized, context-aware nature of AI recommendations creates a level of trust that traditional search channels can't match.

— [AI Is Changing The Rules Of Web Traffic — A GEO Playbook For Online Retailers](https://www.forbes.com/sites/lutzfinger/2025/08/20/generative-engine-optimization-geo-a-playbook-for-online-retailers/) · _Forbes_

Question 44

Why is expert knowledge becoming the winning strategy in retail unbundling?

Accepted Answer

_Specialized knowledge will define winners in the new retail landscape._

Just as the media landscape now thrives with niche creators, e-commerce will follow the same path. Retail brands focusing on knowledge that general LLMs don't yet have will succeed, similar to how specialized bloggers like Ben Thompson emerged in media. The winners will embrace specialization, personalization, and advisory power. Two and a half years ago, when LLM hype started, I predicted the future would be indie, and that's exactly what we're seeing with retail brands now. Not everyone needs to be Amazon, Walmart or Best Buy.

— [The End Of Amazon, Walmart, Best Buy? AI-Driven Retail Unbundling](https://www.forbes.com/sites/lutzfinger/2025/06/30/the-end-of-amazon-walmart-best-buy---ai-driven-retail-unbundling/) · _Forbes_

Question 45

Why is Lutz conducting this survey on AI agents and generative engine optimization?

Accepted Answer

_Research aims to track how users and companies adapt to AI._

Lutz wants to find out how far users, organizations, and the ecosystem have evolved in adapting to AI agents. He's already looked at many areas like IDE for coding, finance for risk underwriting, and e-commerce. To track how users versus companies are adapting, he partnered with Chase Binnie from RetailWire to launch a survey focused on GEO. The data will help understand how brands show up in AI-generated answers, what strategies work, and what tooling is missing. All findings will be published openly.

— [AI Agents - The Internet Is Being Rewritten - Survey Users Vs Brands?](https://www.forbes.com/sites/lutzfinger/2025/07/24/ai-agentsthe-internet-is-being-rewrittensurvey-users-vs-brands/) · _Forbes_

Question 46

Why should brands stop manually overriding AI-driven product rankings?

Accepted Answer

_Manual ranking overrides lower revenue in AI-driven retail._

Brand teams overwrite AI results by hand, pinning products and forcing rankings the algorithm did not choose. Fighting a modern AI system this way usually lowers revenue, not raises it. The fix is to let transformers and longitudinal behavioral data predict the next best product. As surely as we can finish life is like a box of, and you already thought chocolates, we can predict what a shopper most wants after a given query. The result is higher conversion and a lower return rate.

— [Three Mistakes Brands Make In The Age Of AI-Driven E-Commerce](https://www.forbes.com/sites/lutzfinger/2026/05/23/three-mistakes-brands-make-in-the-age-of-ai-driven-e-commerce/) · _Forbes_

Question 47

Why was it difficult to measure LLM traffic conversion, and how did you solve it?

Accepted Answer

_Tracking LLM conversions is hard because users don't leave clean trails._

Good numbers are hard to come by because LLM traffic doesn't always leave a clean trail. Users might just copy and paste a product name and head to Amazon, making it hard to track. To get better data, we created a ChatGPT-style experience inside the site search of several e-commerce stores. This let us run A/B tests comparing regular keyword search with an AI-guided, conversational search experience. That's how we discovered the almost 9x higher conversion rate for the conversational approach.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Q&A, E-commerce

How are users and brands responding differently to AI agents in e-commerce?

How do you categorize shoppers and how do LLMs serve all three types?

How has online shopping changed over the past 25 years?

How has the shift from SEO to GEO changed what websites need to do for brands?

How have search queries changed with LLM-style interfaces compared to traditional search?

How is AI changing e-commerce?

How is AI changing the way consumers shop online?

How is r2decide using multimodality to transform the online shopping experience?

How is the Amazon homepage dying?

How much more valuable is LLM traffic compared to traditional search traffic?

How should brands handle product page personalization instead of using generic chatbots?

What advice do you have for someone considering building a fintech or launching in Africa?

What are AI-generated nudges and how do they work in r2decide's system?

What are the three survival strategies for traditional e-commerce retailers?

What are the two major shifts coming after basic answer engine optimization?

What content should brands create to engage LLMs instead of just listing products?

What content strategy works for generative engine optimization?

What conversion rate difference did you find between LLM-driven traffic and traditional search traffic?

What creates a defensible moat in the age of AI-driven e-commerce?

What did your analysis of ShopTalk 2025 vendors reveal about generative AI adoption in e-commerce?

What does the article say about specialized models versus one general model?

What does your ShopTalk analysis suggest about the timeline for generative AI disruption in business?

What happened to media companies during unbundling, and how does this relate to retail?

What industries has Lutz already identified as being changed by AI agents?

What is Generative Engine Optimization (GEO)?

What is OpenAI's stated ambition for AI agents according to this article?

What is the core discovery mechanism behind multimodal AI, and how does it relate to Amazon's recommendation approach?

What is wrong with adding a chatbot that mimics ChatGPT to a retail site?

What makes generative AI the 'Holy Grail' for personalization compared to traditional AI tools?

What mistakes do brands make in AI-driven e-commerce?

What problem does your e-commerce AI startup solve that existing technology cannot?

What replaces SEO in the LLM era?

What should I monitor to optimize my brand for AI assistants?

Who is investing in these early-stage generative AI e-commerce companies you identified?

Why are some brands invisible when I ask AI assistants for product recommendations?

Why did Amazon's B2B distribution model fail for complex industrial products?

Why did you choose e-commerce to study generative AI adoption rather than other industries?

Why did you leave your healthcare company to start an AI e-commerce company?

Why do LLMs convert better than search?

Why do you say the website is dead, and what does that mean for brands?

Why does creating more AI-generated content fail at generative engine optimization?

Why does e-commerce need fine-tuned AI?

Why does traffic from AI assistants convert better than other channels?

Why is expert knowledge becoming the winning strategy in retail unbundling?

Why is Lutz conducting this survey on AI agents and generative engine optimization?

Why should brands stop manually overriding AI-driven product rankings?

Why was it difficult to measure LLM traffic conversion, and how did you solve it?