Despite rapid advances in artificial intelligence, supply chain leaders are holding back from using this technology to radically transform their operations. A Gartner survey conducted in November 2025 with 140 senior supply chain leaders revealed that only 17% of organizations are pursuing immediate transformational redesign of their processes and workflows using AI. The remaining 83% are either applying AI incrementally to specific use cases or gradually scaling it into integrated processes.
The primary driving force behind this trend is that most organizations are still grappling with fundamental challenges such as data readiness gaps, the need to upskill existing employees on AI, and fragmented vendor landscapes. Caleb Thomson, Senior Director Analyst in Gartner's Supply Chain practice, stated, "Persistent volatility is driving interest in evaluating AI‑orchestrated capabilities, but investment remains constrained by foundational readiness." He further emphasized that even among leading supply chain organizations that have demonstrated performance gains and ROI from their AI investments, few have truly embedded AI into their core operations.
Barriers identified within the same research include 56% citing the challenge of integrating AI with legacy systems and processes, and 50% reporting limited internal expertise or talent to implement and manage AI. According to Gartner analysts, orchestration depends on data quality, yet many organizations struggle with foundational master data alignment that technology alone cannot fix. Additionally, data quality challenges extend across the supply network, as information from trading partners can often be incomplete or unreliable. Human expertise remains essential—achieving greater decision autonomy requires sustained upskilling and gradual adoption—with AI augmenting rather than replacing human judgment.
Gartner analysts emphasize that today's technical and organizational feasibility challenges should not be reasons to delay pursuing the underlying capabilities needed for AI-powered supply chain orchestration. Thomson noted, "Gartner research shows that the business value will be transformative, as it lays the groundwork for future agentic orchestration across the end-to-end supply chain network." Organizations are settling for AI as a tool for incremental improvements to legacy workflows under pressure to demonstrate quick results; however, AI leaders are actually reimagining entire operating models around AI-driven workflows.
Note: This summary draws on SupplyChainBrain's publicly visible headline + subhead + opening paragraph and on sector background on AI maturity.
Key Takeaways:
1. Only 17% of organizations pursue immediate AI-driven transformation per Gartner survey of 140 CSCOs; 83% adopt incremental approach
2. Top AI integration barriers: 56% legacy system integration challenges and 50% insufficient internal expertise/talent
3. Data readiness and quality constraints limit technology scaling—master data alignment and supplier data inconsistencies are widespread issues
4. Human expertise remains critical; AI augments rather than replaces human judgment, requiring sustained upskilling
5. Gartner indicates incremental gains will lay foundations for future end-to-end agentic orchestration, delivering transformative long-term value
