In this webinar, Elenna Dugundji, Director, Deep Knowledge Lab for Supply Chain and Logistics Research Scientist with MIT explores why data discipline remains the foundational driver of supply chain optimization. Our discussion will examine the critical role of data…
True supply chain visibility in 2026 depends less on tracking shipments and more on synchronizing data across systems, ensuring a trusted single source of truth, and building AI-driven decision tools on high-quality, interoperable freight data.
Supply chain leaders implementing warehouse automation should avoid overly customized systems and instead prioritize modular, composable architectures that improve scalability, reduce operational risk, and adapt to changing fulfillment demands.
While enthusiasm for generative AI in supply chains is high, most companies remain trapped in pilot programs because successful deployment requires workflow-level problem definition, embedded agents, and disciplined governance rather than simply applying new AI models.
Wednesday, March 4, 2026 · Amanda Dyson, VP of marketing, FourKites
As AI agents increasingly automate supply chain execution, companies must redesign talent strategies to prioritize relationship management, critical thinking, and organizational influence rather than traditional process-based operational skills.
Tuesday, March 3, 2026 · Tom Davis and Dennis Oates
As generative AI reshapes knowledge work, supply chain leaders must orchestrate people, processes, and intelligent systems, shifting from automation to integration to unlock real performance gains.
APQC research shows that while organizations pursue aggressive AI adoption and Net Zero emissions goals, most fail to account for AI’s energy use and GHG impact—creating a growing disconnect between digital transformation and climate commitments
Supply chains are expanding the use of AI across functions, and that expansion means more data storage and more computation, which all require more electricity use and potentially more greenhouse gas (GHG) emissions during electricity production.
Monday, March 2, 2026 · Dean Alms, chief product officer, Aravo
A review of 2025’s AI predictions shows that while agentic AI and automation advanced in supply chains, data readiness, governance gaps, and third-party risk oversight will determine whether organizations realize real AI ROI in 2026.
As AI accelerates both cyberattacks and defenses, supply chain leaders must shift from prevention-only strategies to resilience-driven models built on third-party visibility, governance, and rapid recovery.
Agentic AI is transforming supply chain operations by moving beyond chatbot-style assistance to governed, ontology-backed execution systems that autonomously detect, decide, and act within defined guardrails.
The 2026 NextGen Supply Chain Conference is now accepting speaker submissions for its practitioner-led event in Nashville, inviting supply chain leaders to share real-world case studies focused on AI, automation, workforce transformation, and measurable operational impact.
Wednesday, February 18, 2026 · Meghan O’Doherty, Senior Director Procurement Advisory, Gartner Supply Chain Practice
AI is transforming procurement by automating transactional sourcing work while creating entirely new AI-driven roles that require CPOs to rethink talent strategy, upskill teams, and redesign how procurement creates value.
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.
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