In a Connected World, AI Alone Won’t Suffice: We Need to Listen
For years, brands and retailers have relied on data-driven insights from multiple sources. Retail, however, doesn’t wait, and neither do consumers; they make decisions in the moment — at the shelf, in the aisle, mid-checkout, often at home.
Now, AI is moving to the edge, where decisions happen instantly, redefining what’s possible but not necessarily explaining why.
That’s why AI alone isn’t enough. The smartest brands and retailers aren’t just analyzing data; they’re observing behavior — watching and listening to better understand how shoppers move, browse, and buy. Real-world insights sharpen AI’s ability to predict, personalize, and anticipate needs in a way that feels human, not just algorithmic.
Beyond Personalization: The Era of Anticipatory Retail
Retailers often talk about AI-driven personalization, but the real leap forward is anticipation — predicting intent before it’s expressed. AI, combined with real-time data, edge computing, and behavioral insights, is redefining retail and product development.
Retailers and brands can best leverage AI’s ability to anticipate shopper needs before they are articulated. By integrating AI with computer vision, IoT sensors, and real-time behavioral analysis, trading partners can dynamically adapt to shifting preferences.
- AI-Driven Demand Sensing: AI can detect emerging trends before they go mainstream, enabling retailers to optimize stock, pricing, and promotions.
- Frictionless Commerce: AI-powered checkout systems reduce friction and enhance convenience.
- Automated Merchandising: AI-driven store layouts and product placements adjust based on demand.
- AI as a Decision-Maker: AI becomes a core decision-making framework, guiding inventory, workforce optimization, and marketing.
A compelling example is Amazon Go, where AI-powered vision and deep learning eliminate traditional checkouts. Customers grab-and-go, with AI handling payments. This not only reduces friction but also provides Amazon with real-time insights into shopping behavior, influencing inventory decisions and personalized recommendations.
Eliminating Data Lag: The Role of Edge AI
Traditional AI insights suffer from latency — delays between data collection and action. Edge AI eliminates data lag, enabling real-time decision-making within stores and warehouses. Imagine AI tracking demand and automatically rerouting stock from one store to another before a stockout occurs.
AI-driven micro-fulfillment centers further enable real-time logistics, minimizing waste and responding to demand surges instantly. Predictive analytics and autonomous systems are redefining how retailers manage inventory and optimize supply chains.
AI as the Trading Partner Operating System
AI is no longer just an efficiency tool; it’s the foundation for the next evolution in trading partner collaboration. Manufacturers and retailers who embrace AI as a shared operating system will foster proactive relationships in serving today’s better-connected, more discerning, and demanding shoppers.
AI will drive critical functions across procurement, manufacturing, distribution, merchandising, and marketing, ensuring a seamless consumer experience whether in-store or online. For all this to work, however, our industry needs to think beyond AI as an application and instead integrate it into the combined sector’s digital architecture — where cloud AI handles large-scale data processing and edge AI executes immediate decisions at the point of engagement, wherever and whenever that might be.
Brands and Retailers Must Act Now
Manufacturers and retailers hesitant to adopt AI-driven edge computing risk falling behind in a rapidly evolving market. The future of the consumer markets isn’t just about using AI to improve processes. It’s about operating at the speed of thought — or as close to that edge as might be possible — to reshape commerce in real time.
It’s no longer enough to optimize what exists. Forward-thinking brands and retailers need AI to redesign business models entirely. AI-driven insights must be fused with consumer psychology, contextual awareness, and adaptive execution to create predictive, personalized experiences.
For instance, Walmart has embraced AI in its smart stores, using real-time shelf-scanning robots to monitor inventory and predict demand before shelves run empty. By incorporating AI as a continuous feedback loop, Walmart improves logistics, staffing, and on-shelf availability, enhancing both customer experience and operational efficiency.
Similarly, Mars has leveraged AI to accelerate product development. The company’s in-house generative AI tool, Brahma, generates up to 50 product concepts daily by analyzing consumer insights and market trends in real-time. This allows Mars to bring innovations to market faster, reducing risk while increasing alignment with consumer demand.
The question isn’t whether AI will be essential — it already is. The real differentiator is who can move beyond data to listen, learn, and serve consumers in ways that feel intuitive and personal. AI can optimize, but only brands and retailers who blend it with human understanding will truly lead.
Michael Forhez has nearly 30 years of experience in sales, marketing, and management consulting across the retail and consumer products sectors. A recognized industry evangelist, he is frequently invited to write and speak on topics shaping the future of the consumer markets. Throughout his career, Forhez has been dedicated to engaging with key stakeholders, ensuring their perspectives and evolving needs are understood and reflected in strategic decision-making.
