Tuesday, February 17, 2026 · Arturo Torres Arpi Acero
After early AI agent pilots failed to deliver measurable operational or P&L impact, supply chain leaders are resetting automation strategies by focusing on decision ownership, governance, data integrity, and constrained autonomy instead of full end-to-end automation.
Monday, February 16, 2026 · Tim Russell, Abdullah Alsukairi and Olivia Morton
MIT Capstone study models fuel distribution capacity in the New Madrid Seismic Zone to identify infrastructure, labor, and policy interventions that can strengthen emergency fuel resilience before a major earthquake disrupts critical supply chains.
To achieve a true Perfect Order in today’s regulatory environment, companies must add a “right data” requirement, integrating accurate, traceable, and compliant information into ERP and EDI systems to meet mandates and retail vendor compliance expectations.
In the volatile 2026 trade environment, commercial EV manufacturers must move beyond lowest landed cost and adopt a portfolio-based Resilient-Grid sourcing model to manage tariffs, capital constraints, and material volatility.
Thursday, February 12, 2026 · Andrew Byer and Mike Dobslaw
A supply chain control tower is a centralized organizational and digital hub that integrates data, people, and processes to provide real-time visibility, coordination, and decision-making across broad portions of the supply chain.
Wednesday, February 11, 2026 · Srinivasan Narayanan
During ERP cloud transformations, manufacturers often see fill rates decline not because of technology failures, but because long-standing assumptions about sourcing, planning, and multi-DC execution are exposed under real operating conditions.
Tuesday, February 10, 2026 · Rodney Thomas and Remko van Hoek
Most organizations use AI to cut costs and move faster, but the companies that will lead their industries are using AI to improve decision quality, deepen insight, and build differentiation, not just efficiency.
As retailers move from AI experimentation to execution, embedded AI agents powered by clean, real-time data and governed by clear guardrails are emerging as the foundation for reliable, scalable retail decision-making in 2026.
Procurement teams facing tighter budgets and higher expectations in 2026 can unlock real value from AI by focusing on practical, modular use cases—GenAI drafting, spend analytics, and supplier risk monitoring—that deliver measurable results without replacing core systems.
AI data center projects slip not because GPUs are late, but because procurement fails to lock long-lead power, networking, and cooling components that quietly define the true critical path to usable compute.
Staples Canada transformed its warehouse operations by replacing manual picking and legacy conveyors with AMRs, cutting errors and cycle time while doubling productivity and improving employee experience across its Canadian fulfillment network.
Tuesday, February 3, 2026 · Baber Farooq, senior vice president and head of market strategy, SAP Ariba
Procurement leaders can only unlock AI’s full value by modernizing data, redesigning processes, and upskilling teams; treating AI adoption as an enterprise transformation rather than a technology rollout.
AI delivers real supply chain value only when it is embedded into operational workflows and paired with process change, not layered on top of broken decisions.
As warehouse put-away logic grows more complex, AI-assisted WMS models offer a potential path to reduce configuration burden by shifting bin-level decisions from static rules to data-driven, real-time optimization.
Manufacturers are rapidly deploying AI across production and supply chains, but new research shows their governance, cybersecurity, and compliance controls are lagging—creating growing exposure to adversarial AI attacks, regulatory scrutiny, and third-party supply chain…
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