Agentic AI and physical AI are among the top supply chain technology trends for 2026, according to Gartner.

Advances in AI technologies are enabling chief supply chain officers (CSCOs) to drive business value, strengthen resilience and reimagine operating models. These trends are shaped by three overarching themes: autonomy and agency; specialisation and intelligence; and trust and governance. These themes reflect a shift towards intelligent, self-directed and accountable systems that operate seamlessly across digital and physical environments.

“This year’s trends highlight the growing role of AI as the foundation for more autonomous, intelligent and adaptive supply chains,” said Christian Titze, Gartner vice president. “As organisations move towards hyperconnected, AI-driven environments, leaders must focus not only on deploying advanced technologies, but also on ensuring they work together to deliver measurable value and long-term resilience. These trends represent more than incremental improvements. They are catalysts for transforming supply chains. Organisations that proactively evaluate and integrate these technologies in line with their business objectives will be better positioned to navigate disruption, scale innovation and maintain competitive advantage.”

Advances in AI, machine learning and robotics engineering are enabling robots to take on multiple tasks beyond their original design. These flexible systems offer a new workforce model, particularly in environments facing labour shortages, though widespread adoption will evolve over time.

Physical AI technology combines AI models with IoT sensors, robotics and automation systems to enable real-time sensing, analysis and execution across supply chain environments. It enhances operational efficiency, safety and adaptability across manufacturing, warehousing and transportation.

Agentic AI is a class of AI systems that is introducing a virtual workforce of agents that move beyond insights to execution, capable of planning, acting and adapting to achieve goals in complex environments. As adoption expands, organisations must establish guardrails to ensure explainability, accountability and responsible use.

Extending the capabilities of individual AI agents, collaborative multi-agent systems enable multiple agents to work together across workflows and environments, each specialising in a specific task or domain. By coordinating these agents, organisations can automate complex, multistep processes and improve scalability and adaptability, while requiring strong governance to manage emerging risks.

Enhancing traditional modelling approaches, intelligent simulation integrates AI, machine learning and analytics into simulation models to improve predictive capabilities and decision making. It enables more dynamic planning across logistics, transportation and warehouse operations, supporting a shift towards proactive and adaptive supply chain management.

Designed for targeted business needs, domain-specific language models are trained or fine-tuned for specialised supply chain use cases, delivering greater accuracy, reliability and compliance than general-purpose AI models. They enable improved performance in areas such as knowledge management, compliance, workflow automation and decision support.

Growing demand for transparency and regulatory compliance is driving the need to trace and verify the origin and journey of products across the supply chain. Technologies such as AI, blockchain and knowledge graphs are advancing the ability to scale provenance across complex supply networks.

As AI adoption scales, organisations are implementing frameworks and guardrails to govern AI-enabled decision making, ensuring transparency, accountability and compliance. This approach is essential to building trust and enabling high-quality, auditable decisions across complex supply chain processes.

To learn more, go to www.gartner.com/en/supply-chain/trends/ai-native-supply-chain.

• A report from UK delivery expert Parcelhero has found that AI has moved from boardroom experiment to operational backbone across global supply chains, and the transformation is accelerating faster than anyone predicted. The report (www.parcelhero.com/en-gb/resources/ebooks/putting-the-ai-into-supply-chains-industry-report) says the proportion of UK transport and storage firms using AI leapt from 16.1% to 27.1% in the first three months of 2026 alone. More than 20% of remaining firms plan to adopt AI within Q2.

“Firms are no longer piloting or exploring AI, they are embedding it,” said report author David Jinks, but added the picture was not without complications. “Many firms are held back not by the technology itself but by what lies beneath it: legacy systems, batch-processed data and manual workflows that are simply incompatible with the real-time data flows that AI requires. Getting the foundations right is every bit as important as choosing the right AI tools. Only 16% of logistics and supply chain organisations say they are unlikely to adopt AI within five years, but the readiness gap is real and it needs to be addressed honestly.”