Trend Analysis from NRF Retail’s Big Show 2026
40 000+ visitors
5 000+ brands
1 000+ exhibitors
175+ sessions
Agentic Commerce: the next platform shift in retail
In hindsight, NRF Retail’s Big Show 2026 will likely be regarded as a milestone in the evolution of modern commerce. A true turning point, when the retail industry decisively stepped into a new era: Agentic Commerce. The AI snowball that started rolling at NRF 2025 has, in just one year, generally meant that AI has gone from being a tool retailers experimented with to becoming core infrastructure affecting the entire value chain—from inventory and logistics to the customer experience itself, and everything in between.
NRF continues to evolve as an event, but it has also shifted from being merely a three-day conference to becoming a broader meeting place that includes off-site events with deep knowledge content and Store Tours exploring the latest retail concepts in Manhattan. The Scandinavian retail community traveling to New York tends to grow every year, which in itself creates valuable networking opportunities where people from different parts of the retail ecosystem discuss the future of commerce.
This trend analysis will examine various aspects of Agentic Commerce: how AI agents are changing consumer behavior so that a store or website is no longer the obvious starting point in a purchase journey; how this impacts stores, warehouses, and logistics; and what strategic consequences it has for retailers and brands when everything must be connected end-to-end. Let’s dive in.
AI: from a tool to core infrastructure
You could almost feel the weight of history when Sundar Pichai, CEO of Google, opened the first day of NRF by launching UCP (Universal Commerce Protocol). In short, UCP is a new framework developed together with leading industry players (such as Shopify, Walmart, and Target) to facilitate interaction between AI agents, e-commerce platforms, payment systems, and physical stores.
Through UCP, a technical industry standard is created that allows AI agents to easily understand, interpret, and act on data from retailers and brands in ways that were previously impossible. A shared structure for product and pricing data, inventory status, terms, and delivery options enables seamless interoperability between AI agents and retailers’ business systems.
The message was clear: AI is no longer a side tool – it is becoming the infrastructure of future commerce.
Retailers have always strived to meet consumers where they are. As people increasingly use and trust AI agents in everyday life, the purchase journey is also beginning to move to this platform. Through these agents, many of tomorrow’s searches, recommendations, purchase decisions, and transactions are expected to take place, meaning that parts of the buying process will gradually be delegated from humans to machines.
This is not merely an evolution of today’s e-commerce – it is a paradigm shift that moves boundaries and reshapes the balance of power within the retail ecosystem. The historical evolution of platforms can be illustrated as shown below.
Development of platforms in retail
What is Agentic Commerce?
In its simplest form, Agentic Commerce can be described as next-generation commerce where AI agents act on behalf of consumers during parts of—or the entire—purchase journey. In a short time, AI tools have evolved from passive assistants that answer questions (chatbots) to active actors that guide customers through the buying process (agents).
Instead of a consumer typing “best running shoes 2026” into a search engine, a conversation with an AI agent begins with a needs-based prompt such as: “I’m running the New York Marathon and need new shoes suitable for asphalt that take my pronation into account. Can you help me?” And instead of clicking through countless websites to move forward in the purchase journey, that phase is delegated to the AI agent with a prompt like:
“I like quality at a good price. Which shoes are best for me?”
AI agents thus become the new primary interface between consumers and retailers by searching for information, discovering relevant products, filtering, comparing prices and reviews, evaluating offers, and ultimately making purchase decisions, completing transactions, and following up on orders and deliveries.
Discovery, decision, delivery
The development has been rapid. Traditional search has declined by 20–50% in a short time, while roughly every second consumer uses AI in connection with search, according to estimates from McKinsey’s report New Front Door to the Internet: Winning in the Age of AI Search (October 2025). Additional data presented at NRF reinforced this trend. About 20% of shopping in the U.S. during Black Friday 2025 was conducted with the help of an AI agent (source: McKinsey), and another study showed that nearly eight out of ten people used an AI assistant during the 2025 holiday season.
So far, AI agents are mainly used in the early stages of the purchase journey (discovery and decision), but development is unlikely to stop there. Shopify CEO Harvey Finkelstein revealed that the number of actual orders placed by AI agents on their platform has increased fourteenfold over the past twelve months (delivery). From low levels, admittedly – but still significant. The evolution is moving from B2C to A2A (Agent-to-Agent), and it is no exaggeration to say that the shopping experience is now becoming truly personalized.
Two types of AI agents: onsite and offsite
Today, there are two types of AI agents: onsite and offsite. Onsite agents are those developed by retailers for their own websites, such as Amazon’s Rufus or Ask Ralph (Ralph Lauren). The goal is to create better customer experiences on the retailer’s own platform and ideally increase conversion. A beneficial side effect is the ability to gather more data through increased interaction and thus learn more about the customer.
Between January and November 2025, more than 250 million people tested Rufus, either on Amazon’s website or in its app. Amazon has also launched a “Buy for Me” button enabling autonomous purchases even from websites outside Amazon’s own ecosystem—though this service has not been without controversy.
At the same time, offsite agents such as ChatGPT, Google Gemini, and Meta AI are growing rapidly. These have a broader scope and are fundamentally brand-neutral in context, making them natural starting points for consumers. If this trend continues, it implies a shift in how marketplaces are perceived and an intensifying battle for the initial consumer touchpoint.
What does this mean for retailers and brands?
Agentic Commerce means that retailers and brands must accept that the customer relationship is partially owned by AI agents and that traffic no longer primarily comes via traditional search, but rather depends on how well AI agents can interpret the data on retailers’ websites.
This has major implications. Below are eight areas that will determine success in an AI-first world:
- From SEO to AEO (Agent Engine Optimization)
- From CX to AX (Agent Experience)
- Unified Commerce as a prerequisite for success
- AI requires PI (Process Intelligence)
- Invest in stores and warehouses ready for Agentic Commerce
- From omnichannel to omnimodal
- Don’t forget the company’s “why”
- The need for new KPIs
1. From SEO to AEO (Agentic Engine Optimization)
It is said that roughly half of all internet traffic today is already machine-driven. If AI agents will primarily manage the purchase process in the future, websites must be optimized for machines – not just humans. This also affects how data is made available, as machines and humans search differently and look for different types of information. Large Language Models (LLMs) favor machine-readable structures, open and standardized data channels, clear product data and terms, and transparent customer reviews to identify relevant content to pass on to consumers. This leads to a shift from traditional SEO (Search Engine Optimization) to AEO (Agentic Engine Optimization).
2. From CX to AX (Agentic Experience)
It is no longer sufficient to work only with Customer Experience (CX); retailers must also focus on Agentic Experience (AX). In plain terms, this means making it easier for AI agents to navigate a website. Their “experience” of a site differs from that of a human. Data quality, transparency, structure, and verifiability become critical factors in building trust with an LLM. Agents need easy access to accurate and validated product data, customer reviews, delivery terms, inventory, and pricing. AX becomes a new competitive dimension and a measure of digital maturity. In an AI-first world, agents’ trust in information will be at least as important as human trust and will determine market visibility. Put simply: well-structured product data will be as important to a retailer as a store window or homepage.
3. Unified Commerce – a prerequisite for success
Investing in robust IT infrastructure and data quality is therefore key to success. Without structured data, there is no visibility to AI agents – plain and simple. To benefit from and scale AI opportunities, Unified Commerce is a foundational requirement. At NRF 2026, Unified Commerce was discussed less than in previous years, but that does not mean its importance has diminished. On the contrary, it has become a hygiene factor: all sales channels must be integrated into a common platform, communicating with inventory and logistics in real time.
4. AI requires PI (Process Intelligence)
We are living in a transformative era, and AI challenges established assumptions. In a session with AWS, a study from MIT was cited showing that 95% of generative AI pilot projects so far have failed to create direct, tangible business value. The explanation was that many focus too much on technology and too little on business value – and that success requires combining AI with Process Intelligence (PI).
Implementing new technologies also demands changes in workflows, organization (roles and skills), and company culture. The conclusion: success depends less on the technology itself and more on how well the organization is prepared for change.
5. Invest in stores and warehouses ready for Agentic Commerce
Since the pandemic, there have been repeated claims about the death of physical stores. However, even if e-commerce gains new momentum through Agentic Commerce, physical retail will remain larger than online commerce for the foreseeable future. According to the latest forecast from Svensk Handel, e-commerce will account for 33–40% of total retail by 2035.
Agentic Commerce is still in an early phase, but it makes the trinity of inventory, logistics, and stores even more important. While this article has focused mainly on the transformation of the digital customer interface, AI also drives deeper integration between stores, warehouses, and logistics—enabling more autonomous decision-making across the supply chain.
This increases the need to upgrade store infrastructure. Investments in RFID, AI-powered kiosks, smart shelf labels, and other IoT devices provide AI agents with the data they need to plan, optimize, and act in real time.
6. From omnichannel to omnimodal
Retailers and brands will continue investing in store development—both by adapting to changing consumer behaviors and making stores more experiential and community-driven, and by leveraging digitalization and AI. Through sensors, networks, and terminals, stores and warehouses become “agent-ready” and central nodes in the retail ecosystem.
Last year at NRF, the term “post-omnichannel” was introduced without a clear definition of what would follow. Perhaps we now have the answer. If omnichannel focused on integrating the customer journey across channels, we are now entering a phase where AI integrates the entire value chain – inventory, stores, online, and logistics – in real time. We have moved from an omnichannel to an omnimodal world.
Omnichannel
Focus on integrating the customer's purchase journey across all channels.
Omnimodal
Focus on the entire value chain and connecting warehouse, store, online and logistics – in real time.
7. Don’t forget the company’s “why”
New technologies are primarily enablers. They change how businesses operate, but rarely why they exist. What needs are being met? What makes the business unique? Who is the audience that finds it authentic and culturally relevant?
At NRF, leaders from several successful new retailers were interviewed. One of the most fascinating examples was Gymshark. Founder Ben Francis emphasized the importance of staying true to the company’s “why,” maintaining a startup mentality despite rapid growth. Instead of aggressively expanding product lines and store openings, Gymshark chooses thoughtful growth without compromising its DNA.
Similar stories emerged from other leaders. In a fast-changing world, focusing on fundamental value creation and cultivating uniqueness is critical. As someone wisely put it: if customers don’t want to buy what you sell, it hardly matters how much technology you invest in.
8. The need for new KPIs
Agentic Commerce will also drive the need to update metrics and measurement tools. Will traditional KPIs such as clicks, page views, or time spent on site remain relevant? Probably not. Instead, new KPIs may emerge, such as AVI (Agent Visibility Index), MRS (Machine Readability Score), LRP (LLM Ranking Position), or ACA (Agent Conversion Attribution).
Zero-click commerce: brave new world?
In the closing keynote at NRF, Jason “Retailgeek” Goldberg painted a vision of Zero Click Commerce – a future where consumers no longer need to spend time clicking around the internet. A problem or need description initiates a process that delivers relevant information, options, and decision recommendations through a single channel: the AI agent.
Goldberg also suggested that future phases may not even require consumers to initiate the purchase journey themselves. As agents learn more about our needs and preferences, they will proactively present relevant information and offers – sometimes even before the need arises.
Digital inflation drives the need for human interaction
Discussions about AI in retail often drift toward dystopian scenarios—robots replacing humans, stores becoming empty autonomous spaces, or disappearing altogether.
That was not the impression at NRF. On the contrary, human interaction and physical environments seem to grow in importance as AI accelerates digitalization and automation. The need for physical stores, social meeting places, and human connection is unlikely to diminish—if anything, it will increase.
AI should primarily be seen as a way to amplify human creativity and capability. Several examples showed how store staff could provide faster, more personalized advice, handle complex issues, and receive better support in solving customer problems. With AI, employees became more engaged and could focus on relationships and service rather than administration.
Focus on AI as a way to enhance human strengths – not replace them.
In summary
NRF Retail’s Big Show 2026 marked the beginning of a new era. Over the past year, Agentic Commerce has gone from buzzword to action. We actually identified the concept already in last year’s NRF trend analysis, but then it was more of a future vision.
“Agentic commerce” – the future of commerce?
Bill Gates said just a few years ago that everyone will have an “AI-powered virtual assistant” within five years. If we continue this idea in the tangential direction, it would mean that at least parts of consumption in the future will be something that happens in dialogue between people’s own virtual AI assistants and retailers’ AI agents.
The idea is a bit misleading in any case, and the fact is that concepts like “Agentic Commerce” have already started to be used, pointing to clear upsides from both the consumer and retailer perspectives.
Excerpt from Lexit’s trend intelligence from NRF 2025
One year later, it has become a new platform that is changing – every day – how consumers search for information, make decisions, complete purchases, discover products, compete, and reshape value chains.
With some perspective, we can conclude that we are now in the midst of the third wave of AI in retail:
First wave: Personalization
AI as a tool to better understand consumers (optimizing websites)
Second wave: Predictive
AI as a tool to better forecast market needs (running the business)
Third wave: Agentic
AI as a tool to act on behalf of consumers (a new platform for the purchase journey)
This third wave forces retailers and brands to ask new questions: what opportunities and threats will agent-based commerce create? How can strong consumer relationships be maintained? And how can agents be encouraged to act on your behalf and ensure visibility in these new channels?
For now, there are more questions than answers—but it is hardly an option to sit back and wait. The future is not hiding around the corner. It is already here.
