Managing your data effectively across the supply chain has long been the holy grail for organisations of all shapes and sizes. With millions of barcodes and RFID tags being read by thousands of data collection devices, the scale of collected data has never been higher.
As almost all our daily systems continue to become augmented with Artificial Intelligence (AI), we’re about to experience a transformative shift, redefining how logistics professionals handle data, make decisions, and gain actionable insights. Here are some of our thoughts on where that shift is likely to happen over the next 12-24 months.

Smarter Filtering of Data
The sheer volume of transactions in supply chains is staggering. AutoID technologies, such as barcode and RFID systems, capture data at every process step. However, valuable insights can quickly get buried without the right tools to filter and process this data. AI will enhance this process by using algorithms to sift through millions of data points, identifying patterns, anomalies, and actionable information in real time. This will allow data to be filtered and, where necessary, excluded before it even hits operational systems – reducing data clutter and lowering costs.
From Raw Data to Human-Readable Reports
Raw data is rarely helpful without context. AI will help bridge this gap by transforming the massive streams of AutoID data generated into clear, human-readable reports. Automated systems can already create dashboards, summaries, and visualisations highlighting critical metrics, trends, and KPIs, but they are often driven by human input. Moving forward, we will see much more AI generating these reports based on previous usage and what’s happening across the supply chain.
Conversational Data Analysis
One of the most exciting advancements in AI is the shift towards conversational data analysis. Imagine asking your supply chain system questions like, “Which suppliers consistently fail to meet delivery deadlines?” or “What are the main causes of delays in the past week?” Rather than manually querying dashboards or combing through reports, AI-powered conversational interfaces will provide direct answers in plain language. This approach will simplify decision-making, making advanced analytics accessible to everyone, regardless of technical expertise.
Real-World Applications
The synergy of AutoID and AI is already making waves in supply chain logistics:
Inventory Management: AI-driven insights are being used to optimise stock levels, reducing overstock and shortages.
Predictive Maintenance: Monitoring and analysing equipment can self-predict failures before they happen.
Demand Forecasting: AI models can process historical and real-time data to predict demand accurately.
Improved Traceability: Combining AutoID with AI ensures end-to-end visibility in the supply chain, which is critical for compliance and quality assurance.
Amazon, Maersk, Unilever, DHL, and Walmart have all publicly announced that they are working on supply chain projects where AI drives change. These include predictive analytics for inventory management, improving fuel efficiency in logistics, improving stock availability, and detecting overall inefficiencies across the supply chain.

Learn More
To dive deeper into how AI and AutoID transform supply chain logistics, check out our recent webinar, where our team explore real-world use cases and future trends. Watch the webinar here.
By leveraging the combined power of AI and AutoID, the supply chain industry is stepping into a future where data is collected, understood, and utilised. It’s time to move beyond dashboards and reports and ask more intelligent questions—because the answers are already waiting for us.