Supply chain management (SCM) software with agentic AI capabilities will grow from less than $2-billion in 2025 to $53-billion in spend by 2030, according to Gartner.
The forecast highlights the rapid expansion in both availability and enterprise spend on SCM software that includes AI assistants and simple AI agents. It also reflects increasing spend on advanced AI agents with agentic AI capabilities.
“Simple AI agents are capable of executing discrete supply chain tasks, increasingly enabling organisations to automate routine workflows and freeing up bandwidth of humans to complete more complex tasks,” says Balaji Abbabatulla, VP analyst in Gartner’s Supply Chain practice. “As supply chain organisations begin to realise, measure and demonstrate business value from such simple AI agents over the next 12 to 18 months, leaders in these organisations will start prioritising investments in clusters of simple AI agents to enable orchestration of multi-step workflows with or without humans in the loop.”
New phase for agentic AI in SCM software
The initial wave of AI-assistant SCM software has already had a substantial impact on the SCM market. It is now entering a new phase in which providers are seeking competitive advantage through investments in AI agents to execute simple tasks either individually or in collaboration with other agents.
“Procurement criteria are also evolving with AI assistant features becoming a mandatory requirement for SCM software selection, and AI agents a common requirement,” says Gartner. “Software vendors that successfully deploy advanced AI agents will gain a sustainable competitive advantage through the latter half of this forecast period.”
Gartner predicts that by 2030, 60% of enterprises using SCM software will have adopted agentic AI features – up from 5% in 2025 – as businesses move from planning to deploying agentic AI within supply chain workflows. However, enterprise deployments of AI-driven SCM will lag behind general availability of such capabilities from SCM software providers due to the increasing gap between the technology and other layers of the supply chain operating model.
“While SCM tech providers will be delivering AI agents of various denominations to retain their competitive position in a rapidly evolving software market, supply chain data management, operations management, AI-readiness of the workforce, and network-centricity need to evolve to enable deployment of AI-driven supply chain at scale,” Abbabatulla says.
As chief supply chain officers and supply chain technology leaders evaluate and plan for the adoption of agentic AI capabilities, it is essential for them to determine and deploy appropriate levels of human-in-the-loop for supply chain management decisions – particularly during the early stages of AI-driven SCM software deployment.
“Leaders should focus their change management investments in adjacent layers of the supply chain operating model such as data management, operations management, workforce AI-readiness, and network-centricity,” says Abbabatulla. “Additionally, developing strategic partnerships with AI-driven SCM platform providers is crucial to ensure robust support for multi-agent, multi-vendor AI agent orchestration.”