NRF 2026 – Retail’s Big Show, held January 11–13 at New York’s Javits Center, took place at a pivotal moment for the retail industry. The theme of the event, “The Next Now”, as described in Progressive Grocer’s coverage of the show, captured a clear shift in mindset: retail is no longer debating what comes next, it is responding to immediate, compounding pressures that demand faster, more resilient execution.

Artificial intelligence once again dominated the conversation, but NRF 2026 made one thing clear: AI is no longer discussed in isolation. It is increasingly positioned as a response to economic uncertainty, geopolitical tension, margin pressure, and shifting consumer behavior, all converging on retail operations at the same time.

The Broader Context: Resilience Under Pressure

During an NRF press briefing, Mark Mathews, Chief Economist and Executive Director of Research at the National Retail Federation, summed up the past year in a single line:

“Tariffs, politics and an AI boom — what a year.”

Despite a complex macroeconomic environment shaped by tariffs, political uncertainty, and uneven consumer confidence, U.S. retail has demonstrated notable resilience. Consumer spending remained broadly solid throughout 2025, even as sentiment stayed cautious, a dynamic often described as consumers “griping, but swiping.”

Looking ahead to 2026, economists described a demanding and uneven landscape:

• continued economic growth driven by productivity gains
• consumer confidence that remains fragile
• widening differences in spending power across consumer segments

This divergence is forcing retailers to operate with greater precision, making sharper trade-offs between value, pricing, availability, and margins, while staying agile in the face of mixed and sometimes contradictory signals.

Against this backdrop, AI is increasingly viewed not as a technology experiment, but as a practical operational lever to manage complexity, reduce uncertainty, and accelerate decision-making at scale.

Key Trends from NRF 2026

Agentic AI Moves from Concept to Execution

Agentic AI was the most frequently cited term at NRF 2026, but the conversation has matured. Retailers focused less on experimentation and more on AI systems capable of executing multi-step decisions across pricing, inventory, and operations.

As Vasudev summarized:

“Deploy technology that reduces friction for customers and enables faster, more accurate decisions across the business.”

In today’s environment, decision latency has become a liability.

Speed and Agility Become Survival Capabilities

Speed-to-market emerged as a core theme, particularly for private brands and fast-moving categories. Retailers described how simplifying decision ownership and reducing manual planning cycles helped them respond faster to demand while limiting inventory risk.

Target shared one of the most concrete examples. Rick Gomez, Chief Commercial Officer, noted:

“We’ve reduced our private-label go-to-market timeline from 27 weeks to about eight weeks. Speed isn’t just about chasing trends — it’s about reducing risk.”

Curation at Scale in a Fragmented Consumer Landscape

As assortments expand through marketplaces and digital channels, retailers emphasized the importance of curation, not just breadth.

Sarah Travis, EVP and Chief Digital & Revenue Officer at Target, explained:

“Marketplace plays an enormous role in helping us identify trends and curate at scale, while staying true to what Target stands for.”

Nordstrom echoed this approach. Miguel Almeida, President of Digital & Customer Experience, added:

“Marketplace allows us agility and speed without becoming the ‘everything store.’”

Marketplaces are increasingly viewed as risk-managed experimentation tools, not just assortment expansion engines.

Human–AI Collaboration Becomes a Core Operating Principle

While AI dominated the conversation at NRF 2026, retailers consistently emphasized that AI is designed to collaborate with humans, not replace them. Executives framed AI primarily as a productivity and decision-acceleration tool, reshaping how work is done rather than eliminating the need for human judgment and expertise.

As Ashley Kramer, VP of Enterprise at OpenAI, summarized:

“AI is here to amplify human intelligence.”

Retailers shared how this collaboration is already changing day-to-day operations. At Walmart, AI-driven automation is reducing the physical and repetitive nature of certain supply chain tasks, enabling employees to move into more analytical and technical roles. At REI, leaders emphasized that human experience, particularly product knowledge and real-world usage, remains a critical differentiator that AI cannot replicate.

Across these discussions, a clear theme emerged: the most effective AI strategies combine machine speed and scale with human context, judgment, and accountability.

Agentic AI Enters Core Retail Operations

Beyond customer-facing experiences, NRF 2026 showed clear momentum toward agentic AI embedded directly into core retail operations, particularly pricing, store execution, and inventory management.

Pricing stood out as one of the most urgent application areas. With inflation easing but value sensitivity remaining high, and tariffs still influencing cost structures, retailers need pricing systems that can react continuously, not periodically.

Matt Pavich, Senior Director of Strategy and Innovation at Revionics, explained:

“Retailers are being hit from all sides — tariffs, inflation, and customers relentlessly focused on value. Pricing can’t be static anymore.”

Across sessions and on the show floor, retailers highlighted practical agentic AI use cases already in production or active rollout, including:

• Dynamic pricing execution, where retailers move away from static price updates toward continuous adjustment based on demand, cost, and competitive pressure

• Automated promotion optimization, a capability discussed by grocery and mass retailers including Kroger, where AI agents evaluate promotion performance in-season and adjust depth, timing, or scope to protect margin while maintaining customer value perception.

• Inventory rebalancing across stores, highlighted by large omnichannel retailers such as Target, using real-time sell-through and availability data to move inventory faster, reduce out-of-stocks, and limit end-of-season markdown exposure.

• Store-level task prioritization, shared in grocery-focused sessions with retailers like Wegmans Food Markets, where AI dynamically sequences replenishment, production, markdowns, and operational tasks based on live store conditions, improving in-the-moment execution and reducing waste.

• Demand-aware replenishment decisions, increasingly adopted by fashion and specialty retailers such as Zalando, aligning order quantities and replenishment timing with short-term demand signals and supply constraints rather than static seasonal plans.

• Shrink and waste reduction, particularly in grocery and fresh categories, where retailers demonstrated how AI-driven production, allocation, and replenishment decisions are helping reduce overproduction and spoilage while improving on-shelf availability.

• Want a deeper dive? Explore our Top AI Use Cases for Retailers to see how these capabilities translate into measurable business impact across pricing, inventory, and execution.

Together, these examples reinforce a key takeaway from NRF 2026: agentic AI creates value when it is trusted to execute well-defined decisions at operational speed, not when it is limited to analysis or recommendations.

AI in Action: How Retailers Are Applying AI in Practice at NRF 2026

Beyond strategy, NRF 2026 highlighted concrete examples of AI already reshaping retail execution across different business models, from end-to-end commerce orchestration to merchandising, marketing, and customer engagement.

• Walmart × Google Gemini — Agentic commerce in action
  AI-powered conversational experiences now enable shoppers to discover products, make decisions, and complete purchases within a single interface. This use case illustrates how agentic AI can orchestrate end-to-end commerce journeys, while allowing retailers to retain control over pricing, fulfillment, and merchant-of-record responsibilities.

• Kroger — Simplifying choice at scale
  Kroger demonstrated how AI assistants turn customer intent into fully shoppable baskets, reducing friction in high-choice environments.
  

  “Consumers want choice, but too much choice creates friction. AI helps simplify the journey.”
  — Yael Cosset, Chief Digital and Technology Officer

• Dick’s Sporting Goods — AI as a productivity and decision-support tool
  AI is used to help teams operate more efficiently without replacing human judgment, reframing AI as an opportunity rather than a threat
  

  “I don’t think anybody should be afraid of AI.”
  — Ed Stack, Executive Chairman

• Ulta Beauty — AI + human expertise
  AI enhances associate effectiveness and service quality, reinforcing — not replacing — the human connection that differentiates the brand.

• PacSun — Community-driven AI engagement
  AI-powered platforms support creator ecosystems and community-led commerce with Gen Z.

• Fanatics — Speed and vertical integration
  AI supports a fan-centric, vertically integrated model that compresses product creation, merchandising, and fulfillment timelines.
  
  

  “A brand that has inverted the traditional retail model.”
  — Matthew Shay, NRF President & CEO

Key takeaway:
Across these examples, one pattern stands out, AI creates value when it is trusted to execute clear, well-defined decisions at operational speed, not when it is limited to generating insights.

Bamboo Rose at NRF 2026: Our Perspective from the Show Floor

At NRF 2026, the Bamboo Rose team spent three intense days on the show floor, meeting with retailers and brands a great mix of customers and  prospects who are all navigating the same reality: moving beyond AI experimentation toward decision-driven execution, under growing economic, pricing, and supply chain pressure.

From impromptu booth conversations to deeper working sessions, one thing was striking: while AI is everywhere, retailers are asking far more pragmatic questions than in past years. Less “what can AI do?”, more “how do we actually run the business better, faster, and with fewer surprises?”

Across discussions with customers like PacSun and other large retailers, several themes came up consistently.

Our key takeaways from NRF 2026:

• AI success depends on decision clarity, not just technology or model sophistication
• Speed and resilience require aligned decision frameworks across planning, merchandising, and execution teams
• Platforms must support real-world trade-offs, balancing margin, availability, cost, and speed in day-to-day decisions

What became clear on the show floor is that retailers aren’t looking to eliminate complexity,  they’re looking to manage it more intelligently. From our work with customers like, it’s evident that many are turning to Decision Intelligence to make trade-offs explicit, accelerate execution, and operate with greater confidence in an increasingly volatile environment.

Looking Ahead

NRF 2026 didn’t introduce a single breakthrough technology. It confirmed something more important: retail is entering an era where execution under pressure defines success.

In 2026, competitive advantage won’t come from deploying more AI.
It will come from making better decisions, faster, and at scale.

As one NRF speaker put it:

“AI isn’t the strategy. Decisions are.”

👉 To explore how leading retailers are operationalizing agentic AI in 2026, download our Retailer’s 2026 Playbook for Agentic AI, a practical guide to turning AI into execution across pricing, inventory, and operations.

Did you miss Bamboo Rose at NRF 2026?

Don’t worry — we showcased our AI-native TotalPLM platform, including innovative modules such as our Decision Intelligence Layer and its concrete use cases across the entire product lifecycle. We demonstrated how retailers can move from planning and merchandising to creative collaboration and execution with confidence.

From accelerating go-to-market timelines to responding faster to trends and market signals, Bamboo Rose helps teams operate with greater speed, clarity, and confidence. If you’re looking to turn AI into real retail execution, let’s continue the conversation.