Gartner Identifies Top Supply Chain Technology Trends for 2025

Advancements in technology will provide supply chain technology leaders and chief supply chain officers (CSCOs) with opportunities to support digital value realization, enhance workforce productivity, and innovate new operating models. Among these emerging opportunities, Gartner has identified the top supply chain technology trends for 2025 that will aid leaders in pursuit of these objectives.

“This year’s trends highlight the transformative potential of connectivity and intelligence in supply chains, enabling leaders to enhance operational efficiency and adaptability,” said Christian Titze, VP Analyst and Chief of Research in Gartner’s Supply Chain practice. “By evaluating and integrating advanced technologies like agentic AI and intelligent simulation, organizations can achieve specific goals, foster innovation and achieve long-term competitive advantage.”

This year’s supply chain technology trends are driven by two broad themes: the need for supply chain leaders to leverage emerging technologies to enhance connectivity, and tools that foster intelligence to drive competitive differentiation and operational efficiency (see Figure 1).

Ambient Invisible Intelligence
Enabled by ultra-low-cost, small smart tags and sensors, ambient invisible intelligence allows for large-scale, affordable tracking and sensing, providing real-time visibility into end-to-end supply chains. This technology is particularly useful for monitoring perishable goods and ensuring compliance with environmental regulations through enhanced traceability.

Augmented Connected Workforce (ACWF)
ACWF initiatives leverage digital tools to improve decision accuracy and reduce variability, addressing the significant skills gap in today’s workforce. By digitizing standard operating procedures, organizations can accelerate employee onboarding and enhance productivity across manufacturing and logistics operations.

Multimodal UI
A multimodal UI enables users to interact with systems through multiple modes of communication, enhancing user experience and efficiency. For example, this approach is being adopted in logistics to improve driver safety and productivity through voice-activated controls and gesture-based interfaces.

Polyfunctional Robots
Polyfunctional robots can take on multiple tasks and adapt to new roles, providing a flexible workforce solution. These robots are increasingly used in warehouses to perform tasks ranging from sorting to packaging, reducing the need for human intervention.

Agentic AI
Agentic AI systems offer a virtual workforce of AI agents that autonomously execute decisions, enhancing adaptability and efficiency in supply chain operations. As an example, these agents can optimize inventory management by autonomously adjusting stock levels based on real-time demand forecasts.

Autonomous Data Collection
Technologies such as drones and mobile robots autonomously capture data, enhancing productivity and reducing labor in supply chain operations. For example, drones are used in warehouses for inventory checks, significantly reducing the time and risk associated with manual counts.

Decision Intelligence (DI)
DI combines decision modeling, AI, and analytics to support, augment, and automate decision making, driving business outcomes. This technology allows supply chain leaders to understand how tools come to decisions and then improve those based on feedback.

Intelligent Simulation
Integrating AI and ML into traditional simulation models, intelligent simulation enhances predictive capabilities and decision making in supply chain operations. As one example, intelligent simulation allows companies to optimize logistics routes and warehouse layouts, improving efficiency and reducing costs.