THE TRANSFORMER
Rethinking AI
Supply chain organizations should take a page from the past and re-think talent, processes, and culture around Artificial intelligence, focusing on human- centered change management rather than simply reacting to technology deployments. RECOMMENDATIONS: Keeping humans in the loop starts at the beginning of AI scoping and feasibility. Use Design Thinking and Agile principles to deconstruct processes, identifying tasks and decision-making that can be easily automated while prioritizing human intervention. Develop flexible, cross-functional talent and build broader Plan- Source-Make-Deliver knowledge. Future-fit versatilists will flow to work in AI-enabled, demand- driven supply chains. Leadership should have a framework for action but empower bottom-up decision- making. Meeting in the middle and encouraging workers to have a voice in co-creating new ways of working is a critical success factor in change management. Build organizational mechanisms for continuous on-the-job learning, including:
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As supply chain organizations experiment with AI, it’s important they have a framework for capturing and sharing learnings from both success and failure, what is known and unknown. Boston University’s Dynamic Learning Matrix is an apt paradigm for better understanding knowledge sufficiencies and deficits.
or a job fair, go deeper and explore collaboration opportunities around the future of work. 3. Create an internal gig economy. Structured learning (courses, certificates, degrees) builds literacy. But for employees to develop skillset fluency and mastery, they need a space to apply learning on the job in a real- world environment. Resource constraints remain an innovation challenge within many supply chain organizations. It’s a nature of the function. Supply chain has traditionally been viewed as a back- office cost center. Success was predicated on process optimization and defect elimination. Roles were specialized and static. There was an aversion to experimentation and failure. Times are changing. As digital transformation reshapes legacy systems and processes, supply chain functions need to become more innovation- oriented. How do you meet the day-to-day needs of the business while allowing time for employees to grow and develop future- fit skills? Or train for new roles? Oftentimes enterprises will outsource special projects to third-party consultants, thereby losing valuable on-the-job learning experiences, and failing to address the root cause problem. Instead, organizations should develop
do people readily share when work goes awry. 2. Partner with academia. Higher Education is at a crossroads as the “admissions apocalypse” and declin- ing enrollment pressure universities and colleges to seek alternative revenue streams. Executive and enterprise edu- cation is a ripe area for growth. Also, with few exceptions, corporate HR should not be in the business of creating curriculum. Rather, it should be focusing resources on curating the wealth of learning and development content that exists outside the enterprise. Beyond education, universities are good partners to help beta test versatility in an AI-native world. Future-fit skills include cross-functional collaboration, Critical Thinking, Design Thinking, Agile, Data literacy, Change Management, and AI engineering/ fluency among others. Role-playing real-world, future ways of working is a win-win opportunity for both academia and corporate supply chains. What better way to develop future- fit capabilities than before prospective recruits enter the workforce? Internships and Co-ops are great “feedback loops” to test, learn, and iterate with AI in mind. The next time your organization engages a university for recruiting
• Internal gig marketplaces
• Market intelligence communities of practice
• University partnerships
• Peer-learning networks
76 Inbound Logistics • July 2026
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