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There’s been a lot of talk about autonomous supply chains that can run themselves lately, but new research from Gartner suggests it could be years before most companies get there. The firm says that by 2030, just 5% of organizations implementing some form of supply chain planning automation will make at least 10% of their planning decisions autonomously.
Still, companies continue to invest heavily in technologies that promise to reduce manual planning tasks and give supply chain professionals more time to focus on higher-level decisions. In surveying 243 senior executives at organizations with annual revenues of at least $500 million, Gartner found that 83% had already spent $3 million or more on supply chain planning automation, including AI.
More than half (51%) had invested between $3 million and $10 million. Despite those investments, the firms expect a gradual transition to more autonomous planning. Still, issues like data quality, technology capabilities and organizational readiness will have to be addressed before planning decisions can be managed by automated systems.
“Spending millions on supply chain planning automation can expand technical capabilities, but investment alone does not create AI readiness,” said Gartner’s Buse Aras in a press release. “Leaders must establish the necessary decision, talent and technology foundations before scaling AI-enabled planning. Otherwise, they risk funding technology that does not improve the planning decisions that matter most.”
What’s an Autonomous Supply Chain?
Autonomous supply chains use AI and predictive analytics to continuously monitor operations, anticipate disruptions and make decisions across inventory planning, carrier selection and last-mile delivery, all with minimal human intervention. That’s a mouthful, but basically these systems take much of the heavy lifting out of day-to-day planning and leave the experts to handle exceptions, solve problems and tackle bigger-picture decisions.
It all sounds good in theory, but the reality is that we’re not quite there yet. Sure, AI has made major inroads in supply chain planning over the last couple of years, but the day when companies can confidently hand off routine planning decisions to autonomous systems is still a ways off. In fact, Gartner is saying that only a small percentage of organizations will be making even 10% of their supply chain planning decisions autonomously by 2030.
In other words, even with all the progress and usage of AI that’s happening in the business world right now, four years from now autonomous supply chain planning will still be largely in the experimental stage.
A Look Under the Hood
As the technology behind autonomous supply chains continues to advance, different systems work behind the scenes, making decisions and responding to changing conditions. GEP says these five core technologies work together to make that happen:
- Agentic AI. Software agents that can independently plan, make decisions and carry out multistep tasks across supply chain functions.
- Predictive and prescriptive analytics. Models that forecast demand, supply risks and potential disruptions, then recommend or initiate appropriate responses.
- Digital twins. Virtual replicas of physical supply chains that allow companies to simulate different scenarios and test decisions before implementing them.
- IoT and real-time data platforms. Sensors and connected systems that continuously collect and supply the data autonomous systems need to make decisions.
- Orchestration. The connective tissue that helps planning, procurement and logistics systems coordinate decisions across the end-to-end supply chain.
With these five players working together, companies get supply chains that respond to changing conditions with less human involvement. “Think of it this way,” GEP says, “an autonomous supply chain is an AI-native way of running operations where the software itself notices changes in demand, supply, logistics and risk, and then makes and executes decisions without waiting on you to sign off on every single move.”
What’s Next?
Looking ahead, Gartner expects companies to adopt autonomous supply chain technologies at different rates depending on the types of decisions they want to automate. Routine activities like replenishment and order prioritization are better candidates for autonomous planning, while more complex decisions involving network design and inventory policies will continue to require human judgment.
The research also foreshadows changes ahead for supply chain planners themselves. As companies adopt more AI-supported and automated planning tools, Gartner predicts that planners will spend less time administering data and more time coordinating decisions across the supply chain.
To get more from their investments, Gartner recommends that companies start by evaluating the planning decisions they’re considering for automation. “Classify priority decisions as strategic, tactical or operational,” it says, “[then] define the desired business outcome and determine whether AI should support, augment or automate each decision based on its value, complexity, risk and need for human judgment.”
