Gartner Highlights Three Building Blocks for Autonomous Supply Chain Future

Chief supply chain officers (CSCOs) must focus on building autonomous-ready capabilities across operations, intelligence and workforce to prepare their operating models to mitigate ongoing volatility and build future competitive advantage, according to Gartner, Inc., a business and technology insights company.

Attendees learned today during the Opening Keynote at Gartner Supply Chain Symposium/Xpo in Orlando how autonomous business capabilities are already beginning to reshape supply chain strategy and execution.

“As supply chains enter the autonomous business era, leaders must fundamentally rethink how decisions are made, who makes them, and how value is created,” said Lindsay Azim, Senior Director Analyst in Gartner’s Supply Chain practice. “This shift requires moving beyond efficiency-focused automation toward operating models that allow people and intelligent machines to act with greater independence, guided by clear outcomes, risk tolerance and human judgment.”

Gartner defines autonomous business as a strategy that uses self-improving, adaptable technology to make decisions, take action and create new types of value by increasing both people autonomy and machine autonomy. In supply chains, this represents a significant change due to the physical complexity of factories, warehouses, transportation assets and global networks, where digital intelligence must be coordinated with physical execution.

To help CSCOs navigate this shift, Gartner outlined three core building blocks to prepare for an autonomous supply chain: autonomous-ready operations, autonomous-ready intelligence, and an autonomous-ready workforce.

Autonomous-ready operations require a change in leaders’ mindsets from operating the supply chain as a sequence of automated, siloed tasks to a network of outcome-based decisions autonomously made or augmented by AI, informed by data and human judgment. Efficiency-focused automation alone will not support long-term competitiveness. Leaders must strike a balance between delivering near-term value creation from AI while also setting exploratory objectives to realize the transformative capabilities and new operating models made possible by autonomous operations.

Autonomous-ready intelligence centers on decision infrastructure. Azim noted that technology and data platforms on their own are insufficient. Effective autonomy depends on a “decision stack” that combines data, workflows, governance and human context. This includes clearly mapping critical decisions, defining guardrails for AI-driven actions, and capturing knowledge that traditionally resides in employee experience, enabling both people and machines to make consistent, aligned decisions at scale.

An autonomous-ready workforce focuses on role evolution rather than job elimination. Gartner research indicates that only 1% of layoffs in the second half of 2025 were driven by AI productivity, with most reductions linked to economic and cost pressures. For asset-intensive organizations, Gartner simulations predict that more jobs will be gained than lost due to AI. As autonomy expands, many roles will shift toward more versatile designs, where employees combine domain expertise with the ability to supervise, guide and improve AI-enabled systems.

“Autonomous supply chains will only succeed if people remain at the center of decision-making,” said Azim. “As organizations hand routine decisions to machines, human oversight, judgement and adaptability become even more critical. Leaders who invest now in evolving roles, building decision clarity and aligning autonomy with business outcomes will be better positioned to operate effectively amid ongoing volatility.”

More information on building an autonomous supply chain can be found here: The AI-Native Supply Chain.