Business
5 min readIt’s no secret that I don’t look forward to New York in January for NRF each year - 40,000 people in the retail industry converge on the Javits Center, where the walk from the hotel gives your eyeballs frostbite and leaves your lips chapped for weeks - but we still show up because, well, it’s NRF.
40,000 people representing 5,000 brands and 1,000 vendors while having 175 sessions over 3 days. Enough said.
You can’t mention GenAI these days without a shout-out to NVIDIA; their presence at NRF did not disappoint. Retail Shopping Assistants personified the hype. Google also got in on the action, talking about its Agents to help Retailers while touting its partnership with NVIDIA. Microsoft also touted a Store Operations Agent to help with policies and procedures as part of Microsoft Cloud for Retail.
The potential of Agent AI is significant. Imagine a future where your inventory management system can automatically reorder supplies when stock is low based on factors like price, shipping, and availability. Or a manufacturing plant that can proactively order replacement parts before equipment fails by detecting wear and tear through IoT sensors. This agent-to-agent automation could revolutionize supply chains and operations.
Agent AI could transform the customer experience beyond procurement. Retailers are exploring AI shopping assistants that can understand a customer's needs, preferences, and purchase history to make personalized recommendations and even complete transactions on the customer's behalf. This could lead to a frictionless shopping journey, where AI agents handle various tasks while humans focus on high-value interactions.
Of course, the rise of Agent AI also raises important questions about transparency, accountability, and the role of human decision-making. As these AI systems become more autonomous, retailers must carefully design governance frameworks to align with business objectives and customer expectations. They will also need to build trust and explainability so that customers understand how the AI makes decisions on their behalf.
Overall, the emergence of Agent AI represents a significant shift in how businesses will operate in the coming years. Retailers who embrace this technology and develop the right strategies and safeguards will be well-positioned to drive efficiency, enhance the customer experience, and maintain a competitive edge.
While the hype around Agent AI grabbed headlines, the NRF conference highlighted the growing adoption of "everyday AI" in retail operations and marketing. Digital merchandisers and marketers leverage various AI tools to streamline and optimize workflows.
In digital merchandising, AI automates tasks like image and product description generation. Retailers can leverage large language models to create SEO-friendly content at scale, drawing on product data and specifications to craft unique and compelling descriptions. This frees merchandisers to focus on higher-level strategy and curation rather than getting bogged down in repetitive content creation.
AI is becoming an indispensable tool for content creation, campaign testing, and audience targeting in marketing. Marketers use language models to generate social media posts, email copy, and even advertising slogans, freeing up their time to focus on strategy and creative direction. AI-powered A/B testing also allows them to rapidly iterate on campaigns and identify the most effective messaging and visuals.
The key insight from NRF is that this "everyday AI" is no longer a futuristic concept – retailers are widely adopting it to drive efficiency, personalization, and data-driven decision-making. When asked, “Will GenAI replace my job?” one of my favorite executive replies was, “No, but someone using GenAI may replace you.”
Despite the rapid advancements in AI and digital transformation, the NRF conference also highlighted the ongoing challenges of achieving true Unified Commerce for retailers.
Many retailers struggle to align their in-store and e-commerce operations with separate systems for managing pricing, offers, promotions, and inventory. This siloed approach creates friction in the customer experience, particularly regarding returns and exchanges. Customers expect a seamless, omnichannel journey, but the reality is that retailers are often still juggling multiple platforms and data sources.
The problem extends beyond just online and offline channels. As retailers expand their sales footprint to new platforms like Instagram, they face additional integration challenges. Onboarding new sales channels often requires adopting proprietary payment solutions and fulfillment workflows, making it difficult to maintain a unified view of the customer.
Solving these Unified Commerce challenges will require a concerted effort on multiple fronts. Retailers must invest in modern, cloud-based technology stacks like Broadleaf Commerce that can easily integrate disparate systems and data sources. They must also develop robust data governance and master data management practices to ensure a "single source of truth" across the organization.
Equally important is fostering a culture of collaboration and cross-functional alignment. Siloed teams and legacy mindsets can hinder progress toward Unified Commerce. Retailers must break down these organizational barriers and empower their teams to work together toward a seamless, omnichannel customer experience.
While the path to Unified Commerce may not be quick or easy, the NRF conference clarified that this remains a critical retailer priority. Those who can successfully unify their operations and data will be better positioned to adapt to changing customer expectations, leverage emerging technologies like Agent AI, and maintain a competitive edge in an increasingly complex retail landscape.