Supply chain management is evolving rapidly, driven by advancements in AI and decision intelligence. As we move through 2026, integrating AI into supply chain operations is a necessity. AI-driven decision intelligence is transforming how organizations approach supply chain management, shifting from reactive to proactive strategies. This transformation is crucial for reducing decision latency and maximizing time to value. Companies can focus on future insights rather than past constraints.
In today’s fast-paced supply chain environment, disruptions are a constant challenge. From lane closures to unexpected demand spikes, these events can ripple across your entire supply chain, impacting service levels, costs, and revenue. To navigate these challenges, supply chain teams need solutions that allow them to practice and prepare for the future. Digital twins offer this capability, enabling teams to simulate various scenarios and responses before they occur in real life. This proactive approach ensures that when disruptions happen, the response is second nature, minimizing negative impacts.
In a recent webinar, Logility experts Scott Tillman, VP of Innovation, and Matt Johnson, Director, Product Management broke down the top forces influencing the year ahead and share how decision‑centric, AI‑enabled strategies can help teams navigate uncertainty with clarity, speed, and strategic impact. Read ahead for the highlights.
AI in Supply Chain Management
AI’s role in supply chain management has evolved from providing backward-looking analytics to becoming a collaborative partner. “Most organizations spend way too much time in the past. Yesterday’s demand. Yesterday’s constraints. Yesterday’s surprises,” shared Tillman.
Decision intelligence, combining analytics, AI, and decision models, shortens the distance from insight to action. This shift enables organizations to make informed decisions quickly, aligning with their strategic goals. For example, AI can simulate scenarios, such as the impact of a port shutdown or a supplier going offline to provide actionable insights in real-time. This capability is essential for navigating the complexities of modern supply chains and ensuring resilience in the face of disruptions.
The rise of agentic AI and autonomous supply chain agents marks a significant step forward in supply chain management. These digital teammates can reason, plan, and act within predefined guardrails, taking on procedural tasks that previously burdened human planners. By automating routine decisions, agentic AI frees up human talent to focus on strategic alignment and scenario design. This approach enhances efficiency and empowers supply chain teams to operate with greater precision and speed. The integration of agentic AI into existing workflows is seamless, providing industry-specific solutions that require minimal configuration.
“The organizations moving fastest aren’t the ones with the biggest systems. They’re the ones with the most adaptable systems,” explained Johnson.
Human-AI collaboration is reshaping the day-to-day experience of supply chain teams. AI acts as an always-on first draft analyst, filtering noise, assembling data, and surfacing scenarios. This shift from manual reconciliation to strategic reasoning elevates the role of human planners, allowing them to focus on high-value activities.
“The paradigm is shifting from AI being a copilot for humans to humans being the copilot for AI,” stated Tillman
Organizations that embrace this collaboration see improved confidence and alignment, as teams work from a unified set of scenarios. The transparency and explainability of AI recommendations build trust over time, enhancing the overall effectiveness of supply chain operations.
Webinar: Top 5 Trends for 2026: How AI Strategies Are Shaping the Future
In this webinar, Logility experts Scott Tillman and Matt Johnson will break down the top forces influencing the year ahead and share how decision‑centric, AI‑enabled strategies can help teams navigate uncertainty with clarity, speed, and strategic impact.
Access HereComposable Architectures and Digital Twins in 2026
Composable and modular architectures are becoming a strategic priority for supply chains in 2026. Traditional monolithic systems, while powerful, are rigid and slow to adapt. Composable architectures function like a fleet of synchronized drones, allowing organizations to add new capabilities quickly and safely. This agility is crucial in a volatile environment where demand swings, supplier instability, and regulatory shifts are common. Composable platforms enable continuous evolution, allowing companies to innovate without downtime and integrate new data sources seamlessly. This adaptability is a competitive advantage, positioning organizations to stay ahead of disruptions.
Digital twins must be dynamic and updated in real-time to be effective. This allows you to see ripple effects instantly and test alternate carriers, shift production, resequence fulfillment, or reshape inventory. By knowing the best path for your business before acting, you can make informed decisions with confidence. The real breakthrough comes when digital twins are combined with decision intelligence. While the twin shows every possible future, decision intelligence identifies the best possible one. Companies can simulate dozens of scenarios in minutes and execute the chosen strategy with confidence, having pressure-tested it across the network.
“Digital twins aren’t experimental anymore. They’re becoming strategic infrastructure,” said Tillman.
As we move towards 2026, digital twins are becoming a strategic infrastructure rather than experimental tools. They turn uncertainty into something you can model, navigate, and use to your advantage. Organizations that master simulation and respond quickly will make better decisions with fewer surprises. Continuous network optimization allows you to model your digital twin, suggesting optimization scenarios and comparing services and cost impacts side by side. This democratizes optimization, turning what used to be weeks-long consulting into something a planner can explore interactively in a day or a few hours.
To leverage these advancements, you need to reorient your organization around the decisions you’re making. Understand how decisions are made and orchestrated in processes, then analyze and dissect them to see how AI can enable these processes. Starting somewhere is key to a successful AI journey. Companies that lean into AI now are building the foundations for data and human-AI collaboration patterns that will define competitive advantage. The only real risk is being left behind, so start now, start small, and build from there.
The integration of AI and decision intelligence into supply chain management is transforming the industry. These advancements enhance efficiency, precision, and resilience, while composable architectures provide the agility needed to navigate a volatile environment. Moving deeper into 2026, organizations that embrace these trends will be well-positioned to achieve supply chain excellence and drive strategic growth.
