📈 Shopify says agents are replacing personal shoppers, NVIDIA unveils 3D digital twins & Profound hits unicorn

Profound, the startup that tracks and influences what ChatGPT, Gemini, and Perplexity say about brands, raised a $96M Series C led by Lightspeed, with Sequoia and Kleiner Perkins participating. The company now works with more than 700 enterprise clients including Target, Walmart, and Figma, and total funding stands at $155M. The round closed this week.

Why it matters: If AI answer engines can shift up to 90% of their cited sources over time, brands need active monitoring and optimisation, not a content strategy they revisit once a quarter. Profound's unicorn status signals this is now a boardroom priority. 📰 Fortune

Announced at NVIDIA's GTC conference on 16 March, the partnership embeds NVIDIA's computing infrastructure into Adobe Firefly Foundry, GenStudio, and Experience Platform to power AI agents capable of handling campaign creation end to end. The headline addition is a cloud-native 3D digital twin solution that generates consistent pack shots, lifestyle imagery, and configurable virtual product experiences at scale, without a physical shoot.

Why it matters: For marketing teams bottlenecked by creative production, agents that respect brand identity while generating assets across formats could remove one of the biggest blockers in the go-to-market process. 📰 NVIDIA Newsroom

Speaking at the Upfront Summit in Los Angeles on 16 March, Shopify president Harley Finkelstein said the company is going all-in on agentic commerce, where AI personal shoppers discover, compare, and buy products on behalf of consumers. Shopify has already launched Agentic Storefronts, which surface merchant products inside ChatGPT, Perplexity, and Microsoft Copilot, and co-developed the Universal Commerce Protocol with Google as an open standard for commerce across AI channels.

Why it matters: Unlike search, where ad spend buys visibility, agentic commerce is merit-based. Brands that are well-structured in product data and optimised for LLM citation stand to gain disproportionately. Brands that are not will simply be invisible.. 📰 TechCrunch

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HBS professor, Tsedal Neeley, joins HBR editor-in-chief Amy Bernstein at Harvard's Strategy Summit to make the case that successful AI adoption requires a minimum organisational change threshold she calls the 30% rule. Neeley argues that without a baseline understanding of AI across the workforce, transformation stalls regardless of the tools a company deploys - listen here.

The overview: sitefire.ai is a YC-backed marketing suite designed for the agentic web. This workflow produces a live picture of where your brand is being cited (or ignored) across AI answer engines, and surfaces the content changes most likely to improve that.

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Pro tip: Cross-reference your sitefire citation data with your Google Analytics referral traffic to see whether AI-referred visitors convert differently from organic search, and adjust your content investment accordingly.

The Shopify announcement at Upfront Summit was not a product launch in the traditional sense. It was a statement of direction, and it joins a growing body of evidence that the way consumers find and buy products is shifting in a way that makes traditional search optimisation look like a fairly blunt instrument.

How AI agents are changing the discovery funnel
Traditional product discovery starts with a search query and ends with a results page full of options, many of them paid. Agentic commerce skips that entirely. An AI personal shopper receives a preference or task, queries multiple sources, evaluates options, and returns a recommendation or completes a purchase. Brands that are well-structured in product data and positioned as trusted sources in LLM training get surfaced. Brands that are not simply do not appear.

What Shopify's Universal Commerce Protocol means for marketers
The Universal Commerce Protocol, co-developed with Google, is an attempt to make merchant product data legible to any AI agent across any platform. This is significant because it moves the infrastructure question from "how do I advertise on each AI channel?" to "how do I make my products discoverable across all of them at once?" For performance marketers, it changes the unit of investment from the ad to the data feed.

The brand implications of merit-based discovery
Finkelstein specifically noted that agentic commerce is merit-based in a way traditional search is not. In a world where an AI agent is recommending trainers, the brand that wins is the one whose product data, reviews, and LLM presence make it the most defensible answer. Price, product quality, and brand authority all become re-weighted inputs. For marketers, this is both a threat and an opportunity: the floor for mediocre brands rises, but so does the ceiling for brands that have invested in being genuinely known.

Our takeaway: Agentic commerce is not a channel to add to your media plan, it is a shift in how consumers discover products that requires rethinking product data infrastructure, content authority, and what it means to be findable in the first place. Start there before you worry about ads.

📖 Read the full article at TechCrunch

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