According to Forbes, the upcoming January 2026 National Retail Federation (NRF) Big Show in New York, which draws about 40,000 attendees, will see an even more intense focus on AI and AI agents than the 2025 event. The Innovation Showcase will feature 50 startups, with almost every exhibitor offering AI-based capabilities, but now sharply focused on specific functions like merchandising, pricing, and store operations rather than general use cases. Examples include Birdzi, which claims to help grocers achieve a 30% increase in basket size and 2.5x higher customer retention, and 7Learnings, whose ML pricing software reportedly boosts profitability by up to 10% while cutting manual work by 80%. The broader shift is toward measurable, trip-level personalization and practical automation, as seen with companies like Brij, which scales pre- and post-purchase personalization for over 150 brands. The implementation of these technologies is expected to be a long, culturally disruptive process requiring top-level commitment, fundamentally changing how retail decisions are made.
The Point Solution Pivot
Here’s the thing about the 2026 AI landscape in retail: the era of the magical, do-everything AI platform is over. At least for now. The smart money, and seemingly all the startups, are betting on point solutions. And it makes perfect sense when you think about it. AI development is brutally hard and fast-moving. Trying to build a monolithic system that handles pricing, inventory, customer experience, and supply chain for a massive retailer is a recipe for failure for a startup. But the bigger reason is human nature. Implementing AI isn’t just a software install; it’s a workflow revolution. Asking a merchandising team, a pricing team, and a logistics team to all change how they work simultaneously is organizational suicide. It’s too much change at once. So the winning strategy is to land with one killer use case—say, dynamic pricing with 7Learnings—prove the value, and then expand from there. Even a platform like Envive, which Forbes notes aims to be a “merchandising brain,” knows it has to start with a single point of entry. This is how real, gritty tech adoption actually works, not with a big bang, but with a focused wedge.
The Scary Human Cost of Efficiency
Now, let’s talk about the elephant in the room. The Forbes piece doesn’t shy away from it: this shift is scary. The chart they mention from Publicis Sapient says it all—many people who make decisions today will soon find themselves managing software that makes those decisions. We’re not just talking about automating spreadsheets; we’re talking about software that sets prices, predicts what to stock, and personalizes offers autonomously. The potential for efficiency gains is enormous. A 10% profit boost? An 80% reduction in manual work? Those are numbers that CEOs and boards literally cannot ignore. But achieving them means a cultural earthquake. This isn’t like rolling out a new CRM. This changes job descriptions, power structures, and what it means to be an expert. Forbes says this could take decades, and I believe it. Resistance is guaranteed. The companies that win won’t just be the ones with the best algorithms; they’ll be the ones whose leaders can shepherd their people through this profoundly unsettling transition. That’s the real bottleneck.
Why a Consolidation Wave Is Inevitable
So we have a market flooded with hyper-specialized point solutions. What happens next? According to the analysis, a massive consolidation is brewing, and the logic is airtight. Look, no retail tech team has the bandwidth to properly evaluate dozens of AI vendors for every single function. Great companies will die in obscurity simply because they can’t get seen. Furthermore, all these startups are burning insane amounts of capital just to shout over each other in a deafeningly noisy market. It’s wildly inefficient. Combine a few of them, and suddenly your marketing dollars go much, much further. But the killer argument for consolidation is integration risk. Every vendor promises seamless compatibility, but legacy retail systems are famous for being ancient and brittle. Plugging in five different AI point solutions from five different vendors is a IT nightmare waiting to happen. Consolidation reduces those integration points and lets providers offer a more coherent, less risky suite. It’s not a matter of *if*, but *when*.
The Long, Hard Road Ahead
Basically, the Forbes preview lays out a very clear, very challenging roadmap. AI in retail has moved past the hype cycle and into the messy, difficult implementation phase. The technology is crystallizing into powerful, specific tools that deliver undeniable, measurable ROI. But unlocking that value requires a level of organizational change that most companies are simply not built for. It requires a commitment from the very top that goes beyond budget approval—it needs active, persistent leadership. The retailers who try to dabble or delegate this shift to a mid-level IT director will fail. The ones who understand that they are fundamentally redesigning their company’s decision-making DNA, and who have the stomach for a multi-year—maybe multi-decade—journey, are the ones who will survive. And yeah, it’s exciting. It’s also terrifying. Both can be true. The race isn’t to the swiftest technology, but to the most adaptable culture.
