THE TRANSFORMER [ INSIGHT ]
by Joseph O’Reilly, Digital Transformation Strategist
Back to the Future: Deconstructing Processes and Reconstructing Roles in an AI-native Supply Chain
Everything old is new again. It has become a common refrain as digital transformation wends its way through consumer supply chains. Take the path to purchase, for example. Recommerce is returning to vogue as consumers value more sustainable and economical options. Cost-conscious shoppers are also turning to generic, private label brands, eschewing the premiumization fad that consumed CPG for much of the early 2000s.
Indeed, given investment and time, technology will happen. Less certain is how people will respond to change. Solutions are becoming less specialized and more adaptable. Supply chain talent should follow suit. TPS AND DEMAND-DRIVEN LABOR A demand-driven approach to talent development embraces skillset diversity and flexibility. The past serves up inspira- tion. Toyota’s Taiichi Ohno recognized the importance of cross-training factory workers to manage myriad production processes and thereby level-set demand. It became a hallmark of the Toyota Production System in the post-WWII era. U-shaped manufacturing cells empowered workers to manage multiple machines and processes just in time, matching supply (labor) to demand and eliminating waste (material and time). 2 Ohno made human-in-the- loop fashionable. This is the essence of demand-driven supply chains. Multiskilled practitioners dynamically respond to changing demand signals—similar to how software development moves in agile sprints or
planning features that are converging with one another. Traditional point solutions are becoming less pointed, more utilitarian. Supply chain and IT leaders need to take a pulse check of their tech architecture. How will legacy systems play in an AI-native world? What is core? What is proprietary? And what is plug and play? It is also imperative that leaders consider the future roles of supply chain practitioners. Enterprises experimenting with AI-enabled processes need to understand the impact to organizational culture. “It’s easier to predict the trajectory of a technology than to predict the human usage of that technology,” suggests Gartner Research VP Mary Mesaglio. 1
Even the General Store concept (corner shop, Kirana, pulperias in different parts of the world) is a latter- day trend making a comeback as locally sourced community hubs lure digitally addled consumers looking for convenience, quality, and “social commerce.” The alacrity with which artificial intelligence (AI) is upending tech architecture, business processes, and decision making in the supply chain is also cause for pause. Generative AI (GenAI), notably, is creating a “best-of-breed bleed” in the technology marketplace. Visibility, risk management, network design/ optimization, and planning vendors are innovating new simulation and scenario
74 Inbound Logistics • July 2026
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