A Gartner survey found that 56% of chief supply chain officers (CSCOs) consider integrating AI with legacy systems a major challenge.
The survey included 140 senior supply chain leaders from organizations with annual revenues of $250 million or more.
The survey was conducted from October to November 2025.
Gartner defines an AI-native supply chain as a model designed from the ground up to leverage AI, not just adding AI to existing workflows.
Snigdha Dewal, Director Analyst in Gartner’s Supply Chain practice, stated that the greatest friction in scaling AI is legacy environments, not the technology itself.
Dewal noted that bolting AI onto analog-era foundations locks in inefficiencies and yields only local optimizations.
Leading CSCOs are reimagining supply chain operating models, team roles, and technology layers to build AI-native supply chains.
Early lessons show that investing in AI requires evolution in tech-adjacent organizational layers.

A Gartner survey of 140 senior supply chain leaders from large organizations (annual revenues of $250 million or more) reveals that 56% identify integrating AI with legacy systems as a major challenge. The survey, conducted between October and November 2025, highlights that while AI is often applied incrementally to existing workflows, the primary obstacle to scaling AI is not the technology itself but the legacy environments in which it is deployed. Gartner defines an "AI-native supply chain" as a model designed from the ground up to leverage AI, rather than retrofitting it into traditional processes. The report suggests that simply adding AI to outdated systems perpetuates inefficiencies and limits optimization. Leading supply chain officers are reimagining their operating models, team roles, and technology layers to build AI-native supply chains, recognizing that organizational structures must evolve alongside AI adoption.
The findings indicate that early adopters of AI-native supply chains are learning that successful integration requires more than technological upgrades—it demands a transformation of organizational culture and processes. The pressure to deliver quick results often leads to superficial AI implementations, but Gartner's research underscores the need for a more fundamental redesign to unlock AI's full potential in supply chain management.

The Gartner survey highlights a critical tension in AI adoption: the gap between incremental technological fixes and systemic transformation. The strongest version of this narrative is that legacy systems are the real bottleneck, not AI itself, and that true innovation requires rethinking entire operating models. This aligns with broader patterns in digital transformation, where superficial upgrades often fail to deliver meaningful change. However, the framing risks oversimplifying the challenge—legacy systems persist for reasons beyond mere inertia, including regulatory constraints, workforce expertise, and risk aversion. The call for AI-native supply chains is compelling, but it assumes organizations have the resources and appetite for such radical redesign.
Patterns detected: none
The root cause here is the clash between the pace of technological advancement and the inertia of established organizational structures. The narrative echoes historical shifts like the transition from manual to automated manufacturing, where piecemeal adoption often underperformed compared to holistic redesign. The implications for human agency are significant: while AI promises efficiency, its success hinges on human-led reimagining of roles and processes. The costs of this transition—training, restructuring, potential job displacement—are borne disproportionately by workers, while the benefits accrue to organizations that can afford the upfront investment.
Bridge questions: What specific organizational barriers prevent the shift to AI-native supply chains beyond legacy technology? How might smaller organizations, without the resources of large enterprises, navigate this transition? What evidence exists that AI-native models deliver superior outcomes compared to incremental AI integration?
Counterstrike scan: If this were part of a coordinated influence campaign, the playbook might involve exaggerating the urgency of AI adoption to pressure organizations into costly consulting engagements or technology purchases. However, the content here is aligned with Gartner’s role as a research and advisory firm, offering a measured assessment of challenges rather than a sensationalized call to action. No structural alignment with manipulative tactics is detected.