Where Retail AI Is Headed In 2026

Every January, the National Retail Federation Big Show (NRF) brings retailers and technology vendors together in New York. It’s the largest retail trade show of the year drawing about 40,000 attendees and a great place to see what the next wave of retail technology innovation.

At the last Big Show in January 2025, the major story was artificial intelligence and it was the first time many retailers learned about agentic commerce. It became so ubiquitous that during the course of 2025, I often heard retailers joke about how glad they were when they didn’t have to talk about AI and AI agents.

But agentic commerce isn’t going away.

(If you need a refresher, an AI agent is software that can interpret a situation, decide what to do based on goals and instructions you set and take action autonomously — adapting to many changes including shifting demand, supply chain conditions and user preferences. In retail, it’s now often found in pricing, shelf replenishment and inventory management.)

At the NRF show, the Innovation Showcase features 50 startups worth watching. This coming January, the spotlight on AI and AI agents has gotten even more intense and focused.

Almost every company exhibiting is offering some kind of artificial intelligence-based capability. But this year, rather than offering everything to everyone, they’re shifting away from general use cases and into specific functions like merchandising, pricing, search and store operations.

All the companies map to four categories:

– Business and Trend Analysis

– E-commerce Facilitation and User Experience

– In-Store (brick and mortar) Shopping

– Logistics (like supply chain and shipping)

Some examples of Innovation Showcase companies I previewed are:

Birdzi (pronounced Birds Eye) helps grocers interpret and predict shopper behavior to engage customers with more relevant in-store experiences and offers. Birdzi says clients see about a 30% increase in basket size, roughly double the frequency of store visits and 2.5x higher customer retention. The broader takeaway is that personalization at NRF is shifting from broad AI promises to measurable, trip-level impact.

7Learnings uses machine learning-based pricing to forecast demand at different price points, helping retailers optimize dynamic pricing and performance marketing before changes go live. 7Learnings combines a client’s data with external signals like weather, tariffs, seasonality and competitor activity to anticipate outcomes. The company says its software has increased profitability by as much as 10% and reduced related manual work by up to 80% by better synchronizing marketing with pricing.

Lumi. In my first job as an investment banker, I’d be told “Look at this specific company, find the relevant performance metrics, uncover the non-obvious issues and what needs to be fixed. Write a one-page summary a CEO can read in three minutes.” Sometimes that work took me a day, sometimes it took a week. Lumi says it compresses that workflow for retailers into about 30 seconds, saving hours while surfacing novel insights using natural language prompts. The company says Kroger is a client and that it has a marketing partnership with Deloitte. I wish I’d had this as my secret tool at that first job.

Brij works with over 150 brands like Skullcandy, Momofuku, Gozney Pizza Oven, Feastables and Black Diamond to turn data from warranty registrations, email signups, sweepstakes and rebates (“first-party data”) into personalized content and offers. The 2026 signal is that Brij is making AI-driven pre- and post-purchase personalization practical at scale. It can automate customized landing pages, content recommendations and delivery workflows within brand-defined guardrails without burning managers’ time.

Each of these companies is offering a “point solution” rather than a giant AI solution that addresses multiple aspects of AI implementation in numerous departments in a retailer or brand. There are two reasons for this:

– AI development is hard and it’s changing very rapidly. Having an AI solution that addresses multiple departments is too enormous a task for most startups.

– The more important reason is that AI is such a big change in how people work that implementing more than one point solution at a time is very challenging because of the organizational disruption it creates.

One company I previewed is an exception to the point solution approach:

Envive’s software is a “merchandising brain” platform designed to improve conversion, revenue, personalization, search and customer acquisition efficiency. But even Envive, which has an all-encompassing AI solution to enhance the core skills of a brand or retailer, starts with just one point and uses a “land and expand” strategy.

Timing

It’s going to take a very long time. Unlike other historical implementations of new technology, this one will change the way everyone works.

It’s human nature to resist that kind of shift. But making it happen is an imperative because once one retailer makes the leap, others will feel forced to follow.

The cultural change required to deliver these performance improvements needs CEO and board-level commitment, leadership and participation or it won’t happen.

This could even take decades. The chart at the top of this article, from Publicis Sapient, makes the point succinctly: AI will be used everywhere. Many people who make decisions now will find themselves managing software that increasingly makes those decisions.

It’s scary, it’s exciting, it’s both at once.

Business Combinations

Another force shaping retail technology is going to boil over: consolidation.

I have almost never seen a business sector as ripe for consolidation as retail technology is right now. There are a few reasons why that’s true:

– There are so many retail technology AI offerings being developed that no retailer has the resources to evaluate them all. If AI vendors don’t combine, they may never even be seen by their likely customers.

– The amount of capital needed to be raised for an AI vendor to market is highly inefficient. A great deal of that capital is invested in marketing because the market is so noisy. If there were fewer competitors because of combinations, marketing would be much more efficient.

– The growing number of point solutions creates real integration risk. Vendors all promise compatibility but decades-old retail systems make integrations hard to predict. Consolidation will allow providers to reduce the risk that their software will cause unexpected disruptions.

So There It Is

AI isn’t going away, it’s becoming entrenched because the opportunity of it can’t be ignored.

Cultural changes are coming to retail. Any company that doesn’t make the changes will find it increasingly hard to compete.

It’s going to take time, a long time, but those who adapt best and fastest are going to win.

This is hard. Adopting new technology and changing cultures are some of the hardest things to do at work.

Good luck.