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.
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.
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…
Retailers are moving beyond seasonal planning toward integrated, AI-driven decision frameworks that connect real-time demand signals, financial guardrails, and execution at the store level.
Thursday, January 22, 2026 · Andrew Byer and Mike Dobslaw
Democratizing supply chain data means giving frontline planners and operators across U.S. and global supply chains real-time access to accurate, usable information, turning data into a business asset that improves planning, execution, and accountability rather than an…
Supply chain visibility is shifting from passive tracking to prescriptive, real-time execution using sensor data and analytics to trigger the right actions before disruptions, spoilage, or compliance failures occur.
As U.S. supply chain leaders move past stalled AI pilots, Agentic AI embedded in Integrated Business Planning, digital twins, and human-in-the-loop execution is delivering measurable operational value.
As global volatility intensifies, artificial intelligence is transforming supply chains from reactive, siloed operations into predictive, resilient, and increasingly autonomous systems.
Self-aware supply chains use AI, agentic systems and real-time data to move beyond visibility dashboards, enabling U.S. and global supply chain leaders to sense disruptions early, interpret conditions intelligently and take proactive action before risks escalate.
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