Enterprise investment in AI-driven supply chain software is set to accelerate rapidly, with Gartner forecasting that spending on solutions featuring agentic AI will grow from under $2 billion in 2025 to $53 billion by 2030.
For IT leaders, the projection signals a major shift in how supply chain platforms are designed, procured and deployed. What began with AI assistants is now evolving into a new phase centred on autonomous and semi-autonomous ‘agentic’ systems capable of executing tasks and orchestrating workflows across complex environments.
According to Gartner, early adoption is being driven by simple AI agents that can automate discrete tasks such as order processing, inventory updates or exception handling. These tools are already helping organisations streamline routine workflows and free up human capacity for higher-value activities.
However, the next stage of innovation lies in scaling these capabilities. IT leaders are expected to move from isolated use cases toward clusters of AI agents that collaborate across multi-step processes, potentially operating with limited human intervention.
This shift is already influencing procurement. AI assistant functionality is becoming a baseline requirement for supply chain management (SCM) software, while demand for embedded AI agents is rising quickly. Vendors that can deliver advanced, interoperable agent ecosystems are expected to gain a competitive edge through the latter part of the decade.
Adoption is set to increase significantly, with Gartner predicting that 60% of enterprises using SCM software will deploy agentic AI features by 2030, up from just 5% in 2025. However, enterprise rollout is likely to lag behind vendor innovation.
For IT, the challenge lies less in access to technology and more in readiness. Data quality, integration across systems, workforce capability and operating model maturity will all play a critical role in determining whether agentic AI can be deployed effectively at scale.
Gartner advises IT and supply chain leaders to prioritise investments in data management, AI-ready infrastructure and change management, while also establishing clear governance around human oversight in decision-making.
As supply chain platforms become increasingly autonomous, IT leaders will play a central role in orchestrating not just systems, but the interaction between humans, data and AI agents across the enterprise.
Photo by Reproductive Health Supplies Coalition on Unsplash
