How Digital Twins and AI Are Reshaping Supply Chain Resilience in an Era of Permanent Volatility

The End of Efficiency-First Supply Chains

For decades, supply chain excellence was measured by efficiency metrics: cost per unit, just-in-time delivery, and minimal inventory. Companies built competitive advantages by eliminating waste and friction from their global operations. However, the foundational assumptions that supported this model—stable geopolitics, predictable trade rules, and reliable shipping lanes—have crumbled in today’s volatile landscape.

The End of Efficiency-First Supply Chains
From Reactive to Predictive: The Intelligence Revolution
AI Agents and the Data Advantage
The Digital Twin: Modeling Reality in Real Time
Breaking Down Silos: The Single Pane of Glass
Three Imperatives for Future Supply Chain Leadership
Engineering Resilience Through Connected Intelligence

“The current trade landscape is marked by widespread volatility and complete unpredictability,” Dean Bain, SVP of Supply Chain at Coupa, explained in a recent interview. “Businesses are grappling with rising costs, margin erosion, and the fundamental challenge of how to deal with this uncertainty while providing greater agility to their operations.”, according to technology insights

From Reactive to Predictive: The Intelligence Revolution

This recognition has driven technology providers to develop tools that embed scenario planning directly into supply chain management platforms. The objective is to enable companies to model alternative sourcing decisions and assess downstream impacts on cost and risk, effectively transforming trade volatility from a blind spot into a quantifiable variable.

“It’s the ability for companies to identify alternate sourcing options and use data to make decisions that ultimately protect profitability and market position,” Bain emphasized.

This shift represents a fundamental transformation in supply chain philosophy. Where the past five years focused on digitization, the next five years will center on intelligence—not merely collecting data, but acting on it autonomously. The planning function is evolving from a quarterly or annual exercise into a continuous, real-time process.

AI Agents and the Data Advantage

Coupa is already deploying artificial intelligence agents trained on what Bain describes as their “data moat”—$8 trillion of spend activity across their platform. These AI systems can autonomously manage sourcing, negotiate contracts, and identify emerging risks before human planners detect them.

“We’ve launched AI capabilities in the last year that just amaze us,” Bain noted. “Work that sometimes took days and weeks to perform is being completed in hours by AI.”, according to related news

More significantly, these systems don’t just automate tasks—they prescribe action. The concept of “AI prescriptions” represents a capability that continuously monitors supply chains for risk and proactively suggests considerations for users.

The Digital Twin: Modeling Reality in Real Time

At the heart of this transformation lies the digital twin—a dynamic, AI-driven model of the supply chain that can simulate disruptions and recommend responses instantly. Companies are increasingly building these virtual replicas of their operations to engineer resilience and agility directly into their supply chains., as as previously reported

“Understanding at any particular node what we can do to model a scenario, how we can understand the what-if questions—we do that through the power of AI,” Bain explained.

The digital twin represents more than just technological advancement; it enables a cultural shift from reactive, siloed decision-making to proactive, collaborative planning. Traditional supply chain functions were often disconnected, heavily reliant on manual processes and spreadsheets, with finance, procurement, and supply chain teams optimizing for their own metrics without understanding broader trade-offs.

Breaking Down Silos: The Single Pane of Glass

Today, these organizational barriers are giving way to what Bain calls a “single pane of glass”—a shared digital workspace where all functions collaborate using the same data. This convergence is powered by AI and advanced analytics that provide panoramic visibility across cost, risk, and resilience simultaneously.

“We’re moving from this reactive, siloed way of doing business, very manual and spreadsheet-based, into a much more digitized, proactive, and autonomous process,” he said.

The transformation extends beyond technology to how data itself is structured, shared, and connected across systems. “It’s no longer the single data lake,” Bain observed. “It’s the ability to connect different platforms together that can communicate with one another, that can inform one another.”

Three Imperatives for Future Supply Chain Leadership

Bain outlined three critical priorities for the next era of supply chain management:

Treat data as a core strategic asset rather than an operational byproduct
Leverage artificial intelligence for judgment at scale, not just automation
Create digital twins that serve as living models of the enterprise, reflecting vulnerabilities and opportunities in real time

Perhaps most importantly, Bain emphasized that technology alone isn’t sufficient. “Collaboration across functions—finance, procurement, supply chain—is what turns these tools into transformation,” he noted. “It’s not just a single view of the business. It’s a single decision that impacts not just one function, but the entire operation itself.”

Engineering Resilience Through Connected Intelligence

As businesses navigate what Bain terms “permanent volatility,” where trade wars, tariffs, and geopolitical shocks have become structural rather than episodic, resilience has replaced efficiency as the baseline for value creation. Companies must build around optionality, thinking systematically about how to manage multiple layers of risk.

“This will require the right data, the right indicators, built into our software, systems, and processes that engineer resiliency,” Bain concluded.

The evolution from efficiency-focused supply chains to intelligent, resilient networks represents one of the most significant business transformations of our time. As digital twins become more sophisticated and AI systems more autonomous, companies that embrace this connected intelligence approach will be better positioned to thrive in an increasingly unpredictable global landscape.