Nirmal Jingar, Technology Leader and Advisor specializing in AI strategy, modern platforms and enterprise transformation.gettyFor years, executives have talked about supply chain visibility as if it were the finish line. If they could see inventory, shipments, delays and supplier issues in one place, they assumed the hard part was over. It was not. Visibility tells leaders what is happening. It does not tell them what to do next, who should act or how one fix may create a new problem somewhere else.The old supply chain model was built for a slower economy. It depended on manual planning, periodic reporting and isolated teams. Procurement, manufacturing, logistics and finance often worked from different data and different priorities. That structure could support industrial scale, but it struggled with volatility, short product cycles and sudden disruption.That is why the next phase will involve both digital supply chains and intelligent supply chains. Digital supply chains connect systems. Intelligent supply chains use those connections to sense, predict, reason and adapt. I wrote a book about this shift that looks at the evolution from Industry 4.0 to Industry 5.0. Industry 4.0 gave us automation and connected data. Industry 5.0 brings the human back into the center with resilience, sustainability and better judgment.The real change for the C-suite is not the technology itself. It is the decision model. Too many organizations still use analytics as a reporting layer. A planner gets an alert, a manager reviews it and a meeting gets scheduled. That is an expensive way to run a network. Decision orchestration is different. It coordinates related decisions across procurement, production, inventory, logistics and control towers so one move does not damage another part of the chain.Think about what that means in practice. A retailer might see a supplier delay, a regional demand spike and a port congestion issue at the same time. A dashboard can show all three. A better system can recommend which orders to reroute, which SKUs to prioritize and which inventory policies to change before the situation worsens.Large language models make this shift much more usable for enterprises. Their strength is not that they replace planners or buyers. They can work across structured and unstructured information at scale. In supply chains, the most important signal is often not sitting neatly in a table. It lives in emails, contracts, reports, shipment notes, supplier messages and exception logs. I've found that LLMs can help interpret those inputs and turn them into actionable context for planning, procurement, logistics and control towers.That said, executives should not confuse fluent output with trustworthy output. LLMs can hallucinate. They can reflect bias in training data. They can produce answers that sound right but do not hold up in production. Leaders need to prioritize retrieval, validation, benchmarking and constraint-aware reasoning. In plain language, that means the model should be grounded in real enterprise data, tested against real outcomes and limited by real business rules.This matters most in planning and forecasting. Supply chain planning is still one of the highest-leverage areas in the enterprise. In my experience, LLMs can support demand sensing, scenario analysis and sales and operations planning by combining historical records with market signals, customer input and supplier updates. That does not eliminate the planner. It gives the planner better context, faster.Procurement, inventory and production are changing in the same way. Supplier intelligence is no longer a spreadsheet exercise. Procurement agents can monitor supplier performance, analyze spend, surface contract risk and support sourcing decisions. Inventory optimization is no longer just about holding more safety stock. Multiechelon reasoning can help companies look across the full network and balance service, cost and resilience.That is where I've seen many companies still lose money. One function makes a decision that looks good locally but hurts the network overall. A sourcing change may lower unit cost but create a logistics bottleneck. A production fix may improve throughput but raise inventory in another region. A transportation change may improve route cost but weaken service levels. Decision orchestration exists to stop local optimization from becoming enterprise damage.Logistics and distribution show the same pattern. Transportation planning, route intelligence, warehouse optimization, last-mile delivery and supply chain control towers are becoming more adaptive and more connected. This is where I've found agentic control towers especially helpful. These systems do not just monitor. They detect exceptions, recommend responses and, in some cases, initiate actions within governance boundaries.Risk management may be the clearest business case of all. In my experience, many supply chain risks first appear in unstructured sources such as news, supplier communications, social media and field reports. That means the earliest warning is often outside the ERP system. It is in the noise around the system. AI can help detect those signals, but only if the company has a process for continuous monitoring, validation and response.The same is true for resilience and sustainability. Leaders need to prioritize resilience with stress testing, contingency planning, supplier diversification and digital monitoring. This also includes championing ESG initiatives, circular supply chains and regulatory compliance. That is the right executive framing. A resilient supply chain is not simply one that survives disruption. It is one that stays efficient, responsible and compliant while it does so.The last issue is governance. As supply chains become more autonomous, companies need stronger rules around explainability, privacy, security, fairness and value measurement. Intelligent supply chains only create value when leaders can trust outputs, explain decisions and manage the workforce change that comes with them.That is the message leaders should take seriously. The next supply chain advantage will not come from collecting more data or buying another dashboard. It will come from orchestrating decisions better than competitors can. I believe companies that do that will move faster, recover faster and run with more confidence across the entire network.​​​Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?