AI in Supply Chain

Why It Matters

Embedding AI into core supply‑chain workflows unlocks tangible cost and efficiency gains, turning hype into scalable business value.

Key Takeaways

• AI must be embedded directly into supply‑chain workflows, not layered.
• Strong data and process foundations are prerequisites for scalable AI.
• Real‑time item similarity analysis can cut duplicate SKUs by 15‑20%.
• Ownership and cross‑functional alignment drive AI projects from pilots to scale.
• Measurable outcomes require disciplined piloting, measurement, and integration.

Summary

The webinar, hosted by the Digital Supply Chain Institute and APQC, brought together AI experts from Samsung SDS’s AMRO unit and APQC to discuss how supply‑chain leaders can move from AI experimentation to operational execution.

Panelists highlighted that AI’s rapid advances have shifted the focus to practical deployment: common use cases now include inventory optimization, spend analysis, control‑tower visibility and demand forecasting. Yet scaling remains limited because organizations struggle with fragmented data, misaligned processes, and unclear ownership.

Ian Ranken showcased a concrete example – an item‑similarity analyzer embedded in the procurement intake workflow. By flagging duplicate SKUs at creation, customers reduced duplicate items by 15‑20%, accelerated onboarding, and improved spend visibility. Marissa Brown reinforced that success hinges on solid data foundations, clear business‑outcome goals, and disciplined pilot‑to‑scale pathways, while also emphasizing the human change‑management element.

The discussion underscores that AI should be treated as an operational capability, not a standalone technology project. Companies that embed AI into existing decision‑making processes, secure cross‑functional ownership, and invest in data/process readiness can realize measurable cost, speed and resilience gains across the supply chain.

Original Description

AI experimentation is everywhere—but measurable results are harder to achieve.

In this on-demand webinar, experts from DSCI and APQC cut through the hype to explore what it really takes to turn AI investments into tangible supply chain outcomes.

Featuring:

Vivek Ghelani, Director of Research, DSCI

Marisa Brown, Senior Principal Research Lead, APQC

Ewan Rankin, Executive, Global Business Team, emro

In this session, you’ll learn how to:

✅ Tie AI initiatives directly to KPIs that operational leaders care about

✅ Build the right data foundation for scalable AI

✅ Address security and governance in private and hybrid AI environments

✅ Design pilots that drive momentum—not unnecessary complexity

✅ Separate real solutions from vendor hype

Watch the replay to learn how to move beyond experimentation and make AI deliver real value for your supply chain.

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