Liliana Sanchez

A Shift in the Narrative for 2026 In a recent conversation, Scott Luton spoke with Mark Gilham, Vice President & Head of Global Advisory at Enable, about what supply chain and commercial leaders should expect from the year ahead. While many annual outlooks attempt to forecast the next major disruption, Gilham offered a different lens: 2026 may become the “year of no excuses.” After years defined by a global pandemic, inflationary shocks, geopolitical instability, supply shortages, and the rapid rise of AI, organizations have already endured extraordinary volatility. Businesses not only survived, but in many cases adapted and grew. According to Gilham, that reality weakens the argument that disruption alone explains underperformance. Disruption is not disappearing, he cautioned, but leaders can only lean on it for so long.   Why a Calmer Year Raises the Bar Gilham argued that if external conditions stabilize even slightly, the pressure on leadership actually increases. A less chaotic environment removes convenient explanations and shines a brighter light on internal shortcomings. Process gaps, misaligned incentives, and execution failures become harder to ignore when the world is not on fire. Rather than waiting for certainty, Gilham believes leaders should act decisively. This does not mean radical…

Special Guest Blog Post written by Matt McKinney, Co-Founder and CEO of Loop   I spend most of my time with supply chain and innovation leaders at major enterprises who are sitting on significant AI budgets but struggling to show measurable business impact in an increasingly complex and volatile supply chain environment.   These conversations have evolved dramatically. A year ago, executives were asking basic questions about AI feasibility. Today, the questions have shifted to strategic implementation at enterprise scale.   Based on hundreds of these discussions, three questions consistently emerge that separate companies making transformational progress from those stuck in pilot purgatory.   How do we move from AI experiments to enterprise-scale impact?   Most organizations have yet to see organization-wide, bottom-line impact from AI use. This is the strategic challenge keeping C-suite leaders awake at night.   The problem isn’t the technology. It’s the application of the technology. Too many enterprises are trying to treat AI like a magic wand they can bolt onto existing systems. But garbage in, garbage out. If your underlying data is fragmented and inconsistent, AI won’t solve your problems; in fact they’ll get worse.   At its core, anything automated is powered by…