AI Talk: Supply chain GenAI – from reactive to proactive decision-making 

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Supply chains in manufacturing and automotive are shifting toward AI-first operations, but true scalability requires clean data, standardized processes, and disciplined governance. As 2025 comes to a close, the coming year presents challenges and opportunities as noted for supply chain leaders as they seek to effectively embed AI in their efforts while upskilling employees and scaling efforts appropriately. Those who can solidify their foundations, especially processes and data management, while engendering trust among their employees will be best positioned to continue to navigate the turbulent macroeconomic landscape confronting businesses. Prior to any AI deployment, it’s key to build an AI strategy and understand what data systems exist and how they can be connected. Trust should be built between people, as well as people and AI systems, and this can be done by enhancing cooperation and collaboration rather than competition. AI has pushed down PoC time to months or sometimes even days. In addition to upskilling, workers must also be provided tools that they can leverage to access the data that wasn’t available for them earlier fast.  

 

Unifying fragmented systems 

2026 will probably bring single-pain-of-glass systems, offering more visibility and centralisation. Vertical AI agents will manage different systems, such as warehouses or ERP, which will be orchestrated by an agent of agents. Fragmented data will slow down any decision making – whether enhanced by AI or not. Composable systems, however, can reach across siloes. Glean’s Work AI Platform, for example, connects and indexes enterprise data from SaaS platforms and internal sources through connectors and APIs so users can retrieve relevant information with a single search. Another problem is competition at the top – between operations, executive leadership and IT. While the technology is already there, change management is still lagging behind. AI, however, is a great tool for addressing coordination challenges across the lifecycle – Glean uses AI agents to automate coordination, leveraging a unified Enterprise Graph to access, understand and act upon data. 

 

Connectors are key to aligning different data systems. With the evolution of AI, there will be a shift from gaining insights through LLMs for decision making to getting AI agents to make automated decisions based on the data available for them. AI can provide the level of visibility into enterprise systems that enables the alignment of these systems and the creation of a single source of truth. It can also show the trade-off that a certain decision involves, as well as speed up processes. Today, between an academic paper and a commercial product, it can take as little as a month. While intelligent vision is overshadowed by gen AI, it’s also an amazing tool to get data where it was previously impossible.  Gen AI in the supply chain can reduce latency, accelerate decision making, eliminate mundane manual work and improve the accuracy of forecasting.  

 

You can’t blindly trust AI from the very start but must build it gradually. It will also learn the company culture and the processes that drive decisions. Context is key for decisions and AI can do a great job at providing that and will keep doing so in 2026. The gap between data and a decision has never been a technological one but an execution latency gap. Gen AI has the capabilities to reduce that latency, while also forcing businesses to rethink what they mean by collaboration. It can automate about 30% of decisions made across a company – mostly the repetitive, rule-based ones. The number one skill you need for gen AI is no longer prompt but context engineering. You can give a chatbot data and ask it the types of questions that you would normally ask when you’ve built a sustainable system.   

 

The panel’s advice 

• With disconnected systems you’re bound to make disconnected decisions and without alignment, AI will only amplify this disconnect. 
• Don’t lose sight of technologies that were at the cutting edge before gen AI exploded. They are maturing as well.  
• AI is a torch that helps you see where your organisation could improve.  
• Anticipation without an aligned response is just a notification.  
• 5% of EBITDA can be captured using digital first methodologies, 80% of which will be driven by AI. 
• Glean has a 4 step strategy: simplify, standardise, digitise, automate.  
• Enable a culture of curiosity and tinkering and provide the required resources too.  

 

Glean is the Work AI platform that connects and understands all your company’s data to generate answers and automate work with AI. Learn more.