NRF 2025: Four Takeaways from the Intersection of Retail and AI

National Retail Federation (NRF) is always an incredible opportunity for retail and tech leaders to come together to explore how the retail space is evolving. My focus was specifically on the future of CX in retail and how brands are innovating to transform the customer experience.  I was particularly inspired by how brands like L’Oréal and Lowe’s are using AI to improve online and in-store customer experience and Walmart’s innovative use of AI to improve inventory forecasting. It was exciting to see how commerce and culture are blending – such as Netflix's partnership with Google Lens to enhance the “Emily in Paris” show. 

My favorite part of NRF is speaking with industry CX leaders, many of whom were at The Retail CEO Dinner hosted by Stacy Berns and Berns Communications Group at Le Bernardin. A highlight was a great conversation led by Joanna Coles about what's ahead for brands this year – AI, Growth, and Data.

Here are my top four takeaways from NRF 2024: 

1. AI and Automation

AI-powered automation was a dominant theme, with retailers developing the ability to extract valuable insights from customer interactions to enhance service and loyalty. Two advances related to this emerged:

• AI Summaries: Retailers are really beginning to leverage real-time AI tools to summarize customer interactions and history for live agents. This ensures personalized interactions without requiring agents to sift through scattered data and reduces average handle time. The result is higher CSAT with improved personalization for customers and higher employee satisfaction with less after-call work.
• Context Engineering: By utilizing contextual data from across the enterprise, AI can mirror the conversational tone of live interactions, enhance customer engagement, and anticipate needs, especially in chat (both chatbots and voice chat). So much for the “if then” scenarios of the past! It is bringing in the full context, fueled by this real-time interaction data, that helps retailers deliver faster and more appropriate responses to help resolve issues, drive sales, and deliver growth for companies.

This level of automation empowers brands to engage with customers in a deeper and more meaningful way, learn more about individuals and trends across their customer base, and pivot faster in response to changing realities – all driving higher customer satisfaction, stronger brand loyalty, and sustained growth.

2. Making CX Real in the Contact Center

Retailers have long sought to improve contact center experiences, and we’re seeing real advances. Brands shared how they harness advanced data analytics to unlock broader and deeper customer intelligence and streamline operations. By analyzing multiple data sets, they’re delivering more personalized shopping experiences across channels and mediums, solving problems faster, boosting revenue, and even developing new business opportunities.

Personalization can lower acquisition costs by up to 50%, improve revenues by 5 to 15%, and enhance marketing spend efficiency by 10 to 30% (McKinsey).

The difference between past attempts to improve customer experiences and those of today is that AI technology enables businesses to gain a much deeper understanding of customer trends and individual customers in real time. This is transforming how brands can leverage AI/virtual and live agents in the contact center to solve problems and increase customer satisfaction in a truly meaningful way while aligning with the brand’s loyalty programs and other goals. 

3. AI with a Human Touch

Agentic AI wasn’t as omnipresent at NRF as it was at CES, and that’s not surprising because so much of the focus in retail is on leveraging AI responsibly to enhance CX with human interactions. 

Five9 has long contended that contact center chatbots and AI agents/interactive voice assistants won’t be stealing jobs away from human agents. Instead, they’ll be assisting them and enabling them to provide better service – working hand in hand together.

I discussed above how AI enables retailers to personalize interactions at scale. Part of this is using contextual data and engineering to enable human agents to provide more nuanced responses. With the right level of empathy and personal details, agents can ensure each customer with complex questions feels fully cared for. 

For example, if a VIP customer calls in, the system can instantly see that an order was supposed to arrive at the caller’s home the day before. This means the call could be related to a problem with the delivery. So, instead of sending the caller to a chatbot to gather information, the caller could immediately go to a live agent who would have all the information, ready to respond to whatever issue the caller has.

I like how Cassandra Napoli, head of marketing and events insight at WGSN, expressed it: “There’s a growing desire for authentic human-to-human connections” and “the focus of society and business will shift from isolation to interconnectedness and the recognition that individual needs are inseparable from the collective." Human agents will continue to play a vital role in most contact centers.

Agentic AI will definitely have its place in retail, but this will happen when AI implementation reaches the highest levels of trust and only for tasks not better suited to humans.

4. Context Engineering

As the focus on AI increases, so does the focus on data. That was true at NRF, with widespread recognition that a company’s data strategy will make or break its ability to use AI effectively. No matter how much data you have, AI isn’t particularly useful if it’s not informing and improving customer interactions. 

I’ve written before that capturing customer data is important to customer satisfaction because it enables retailers to hone the problem-solution formula using knowledge from real interactions, enabling a response that is the most likely to satisfy each customer. This satisfaction at scale then drives brand loyalty and increases revenue.

This sentiment was echoed in the conversations I participated in – the need for reliable, secure, and real-time data. The ability to collect and analyze all forms of data, from social media posts to how callers respond during live calls. There is a need for visibility and transparency into how data is collected, protected, and used. The ability to use this data to inform every aspect of the customer journey.

At Five9, we’re focused on enabling brands, like PING and Alaska Airlines, to develop their optimal data strategy, enabling them to train their AI models with context engineering that uses data from anywhere in the enterprise in any form, structured or unstructured, to instantly produce insights for both live and AI/virtual agents. 

If you’re interested in speaking to our team of AI and retail specialists, let us know.