Proof that travels.

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“In practice, AEO begins where SEO stops,” said Dustin Engel, founder of consultancy company Elegant Disruption. “AEO is the next layer of discovery,” or “zero-click discovery.” In this new world where agents synthesize answers, users may never even see an enterprise’s website, click-through rates decline, and attribution and citability (rather than pure visibility, or showing up at the top of a list of blue links) become critical. “The new default is closer to a citation map: Where the model is pulling from, how often you show up, and how you are described,” Engel said

Smart marketers will recognize that the challenge isn’t just explaining a price hike; it’s reinforcing the brand-customer relationship during a moment of tension. It’s giving consumers a reason to trust, not just transact. That might mean creative breakdowns of how prices are built. It might mean interactive UX that lets consumers choose subscription tiers with or without tariff-affected SKUs. It might mean rethinking how value is conveyed altogether.

"If you remove the tool and people can still ship work the same way with a small inconvenience, that is usage,” said Dustin Engel, co-founder of Elegant Disruption, who advises enterprise leadership teams on AI adoption and operating models. “If removal forces measurable degradation in throughput or quality, or a meaningful reallocation of labor and time, that is indispensability."

About 25% of creators used URLgenius recommendation and alert features during the year. These tools highlight high-performing products and monetization opportunities at the moment a creator generates a link. The feature reflects a broader shift in the creator economy toward real-time monetization decisions, where creators choose affiliate opportunities as they publish content rather than researching programs after the fact.

This week, we take a look at how some fashion retailers and consumers are responding to the rise of AI shopping agents. While the technology is growing in adoption, both retailers and consumers have concerns about security, fraud, reliability and the loss of advertising revenue. As AI-powered shopping agents increasingly become a part of modern e-commerce, not everyone is happy about their growth.

In fashion’s race toward agentic commerce, the industry has quickly discovered that intelligence alone isn’t enough. Reliability and trust — especially around fit and sizing — have emerged as a key constraint. For True Fit, this has become the opportunity. Earlier this year, the company introduced its “Fit Intelligence Layer,” a new architecture designed to power artificial intelligence shopping agents built on real outcomes.

LLM costs often mirror organizational complexity, added Dustin Engel, co-founder and principal consultant at Elegant Disruption, a strategy and AI-focused consulting firm in Philadelphia.

57% say that ads in AI chatbots would reduce trust in the advertised brand, per a Partnercentric survey. The challenge may be greater for ChatGPT because it must convince users of the objectivity of its recommendations and advertisers of the value of their spending. Just 24% of consumers say AI chatbots offer the least biased recommendations, compared with 41% for Reddit and 29% for product review websites, per Partnercentric.

Within the category of AI, we started with machine learning, then deep learning, and now generative AI. But for me, the core job has stayed the same: take a massive amount of data and information, and translate it into shopping experiences that are genuinely useful for a shopper at the moment of purchase to remove friction. And in apparel and footwear, so many of those questions come back to fit and size. What’s interesting is that “fit” is rarely just “what size should I buy?” It’s preference and feel: Will it feel tight in the shoulders? Does the fabric have stretch? Will it cling? Is the cut flattering? Will I be comfortable moving in it?

Survey finds 43% bought a product recommended by an AI chatbot in the past 3 months. Creator trust and reviews remain key to converting AI visibility into holiday purchases.

For Dustin, the shift is happening inside collaborative workspaces. "For true success, we should think about using agentic AI as a kind of strategic sidekick," Dustin says. His team is now successfully building autonomous tools that support workshops, planning sessions, and innovation sprints. "It’s great when you’re juggling multiple teams and can’t be everywhere at once. We've seen projects move from vague ideas to clear decisions in far less time. Clients with less experience in structured strategy work feel more confident when they have our AI agents there to back them up.”

“Email is especially effective for BNPL because it gives retailers room to explain both the value and the terms before a shopper gets to checkout, where the message can otherwise feel rushed or purely transactional," says Stephanie Harris, CEO & founder, PartnerCentric, in a comment sent by email. "As BNPL moves beyond a Gen Z checkout perk and becomes something Millennials and middle-income households are using more routinely, retailers have an opportunity to position it as a practical, transparent payment option for planned purchases, seasonal spending, and everyday categories where shoppers are already thinking carefully about affordability.”