AI in Supply Chains: Trusted Data Makes AI Work

Special Guest Blog Post written by Chris Cunnane with InterSystems 

Artificial intelligence is rapidly becoming a strategic priority across industries. Organizations are investing in AI to improve productivity, automate workflows, and unlock new business value. For supply chain leaders, however, the opportunity extends far beyond efficiency gains. AI has the potential to transform how organizations anticipate disruptions, make decisions, and coordinate activities across increasingly complex global networks. [ 

But there is an important reality many companies are learning: AI is only as valuable as the data that powers it. Without accurate, connected, and governed information, even the most sophisticated AI models can generate incomplete insights and unreliable recommendations. Success with AI starts with creating a trusted foundation of enterprise data.  

The Challenge: Too Much Data, Too Many Silos

Supply chains generate vast amounts of information every day. ERP systems, warehouse management applications, transportation platforms, manufacturing systems, supplier networks, IoT devices, and third-party data sources all contribute critical operational intelligence. Yet most organizations struggle with fragmented information spread across hundreds of disconnected systems.  

As a result, when disruptions occur, teams often spend more time gathering and validating data than solving the actual problem. Decision-making slows down, opportunities are missed, and organizations are forced to react instead of proactively managing risk. AI cannot overcome these challenges if it only has access to pieces of the picture. It requires a complete, trusted view of operations. 

Why Unified Data Matters

At InterSystems, AI is not viewed as a standalone technology. Instead, it should be embedded within business processes and powered by trusted, real-time enterprise information. By connecting data across existing systems, organizations can create a unified and governed foundation without replacing the technology investments they already have. 

This approach helps organizations:

• Break down data silos.
• Deliver trusted information to AI models.
• Improve real-time visibility across operations.
• Strengthen governance and security.
• Establish a single source of truth for decision-making. 

When AI is built on trusted data, it becomes more than an experimental tool. It becomes a reliable business partner capable of supporting operational decisions at scale.  

From Visibility to Decision Intelligence

For years, supply chain leaders have focused on visibility. Dashboards, analytics platforms, and reporting tools have helped organizations understand what is happening across their operations. But visibility alone does not drive better outcomes. Organizations increasingly need intelligence that helps them understand what will happen next and what actions should be taken. [ 

This is where AI can create significant value.

Rather than simply reporting low inventory, AI can recommend optimal reallocation strategies. Instead of alerting users to a supplier delay, AI can identify alternative sourcing options before production is impacted. Instead of reporting missed service levels, AI can suggest corrective actions before customer experience suffers. 

This shift from descriptive analytics to decision intelligence represents the next stage of supply chain transformation, helping organizations move faster, improve resilience, and make more informed decisions.  

Introducing InterSystems AI Assistants

To help organizations realize these benefits, InterSystems has introduced AI assistants for both InterSystems Supply Chain Orchestrator® and InterSystems Data Studio™. These new capabilities are designed to make enterprise data and intelligence more accessible to business users while supporting more effective decision-making. 

The InterSystems Supply Chain Orchestrator AI Assistant enables users to interact with supply chain information using natural language. It can help users access and analyze operational data, better understand the business logic behind recommendations, and maintain business context through advanced memory and context-management capabilities. The platform also includes specialized AI agents that support data exploration, workflow coordination, exception management, and operational decision support. 

The InterSystems Data Studio AI Assistant extends these capabilities through a low-code generative AI environment. Organizations can explore structured and unstructured information, create custom AI assistants, and leverage multi-agent workflows to support more sophisticated business analysis. By working from a trusted, governed information layer, these capabilities help improve the quality and reliability of AI-generated insights. 

Final Thought 

As supply chains become more interconnected, success with AI will depend on more than advanced algorithms. It will require trusted data, interoperability, governance, and the ability to turn intelligence into action. Organizations that can connect their information and operational processes will be best positioned to realize the full potential of AI. Read the full article to learn how InterSystems is helping organizations transform fragmented data into AI-enabled decision intelligence and supply chain orchestration. 

InterSystems Can Help

For over 45 years, InterSystems has helped businesses unlock value from data – quickly, safely, and at scale. Our AI-enabled supply chain decision intelligence platform predicts disruptions before they occur, and optimally handles them when they do, so you will be ready to manage the unexpected with confidence. It includes a real-time data gateway that unifies disparate data sources, and a set of next-generation supply chain solutions that complement your existing technology infrastructure to accelerate decision-making and time to value, driving efficiencies throughout your entire supply chain. Learn more at InterSystems.com/SupplyChain.