In the United States, food safety has evolved from a regulatory requirement into a strategic priority. Increasing pressure from the Food Safety Modernization Act (FSMA), along with rising consumer expectations and growing supply chain complexity, is forcing organizations to rethink how they manage information across operations. While automation and transportation have advanced significantly, one of the most critical transformations is happening inside warehouses: the ability to digitize and interpret unstructured data.
Every day, millions of food products move through warehouses carrying essential information such as lot numbers, expiration dates, origin details, and PTI (Produce Traceability Initiative) labels. However, much of this data remains trapped in labels, printed documents, and supplier paperwork. This creates a visibility gap that directly impacts traceability, compliance, and operational efficiency.
Artificial Intelligence-powered Optical Character Recognition (OCR) is addressing this challenge by redefining Warehouse Management Systems (WMS) and strengthening food safety across the United States.
The Visibility Challenge in Food Supply Chains
Food supply chains involve multiple stakeholders, each generating data in different formats. This variability creates friction inside warehouses, particularly during receiving and inventory processes.
Manual data entry remains common, increasing the likelihood of errors in lot codes, expiration dates, and compliance documentation. In recall scenarios, these inefficiencies can significantly delay response times and increase financial and operational risks.
Studies in AI-driven supply chains show that the lack of real-time data capture negatively affects logistics performance and inventory accuracy. In a system where safety and speed are critical, limited visibility becomes a systemic risk.
From OCR to Intelligent Data Capture
Traditional OCR systems were limited to text extraction and struggled in dynamic warehouse environments. AI has transformed OCR into an intelligent data capture solution.
Modern AI-powered OCR combines computer vision and machine learning to interpret context, not just text. These systems can identify lot numbers, SKUs, expiration dates, and PTI labels across different formats, adapting to supplier variability and packaging differences.
They also validate data in real time, reducing the risk of errors entering operational systems. This transforms OCR into a key enabler of decision-making within warehouse operations.
Redefining WMS Through AI and OCR
The integration of AI-powered OCR into WMS platforms is shifting warehouses from static storage locations to intelligent operational hubs.
At receiving, OCR enables automatic data capture from labels and documents, ensuring accurate inventory registration from the point of entry. This eliminates manual processes and improves data reliability.
Traceability is significantly enhanced, allowing real-time tracking at the lot level. In the event of a recall, organizations can quickly identify affected products and respond with precision.
OCR also supports expiration management by enabling FEFO (First Expired, First Out) strategies through direct reading of expiration dates. This reduces waste and improves inventory turnover.
Additionally, digital audit trails created through OCR support regulatory compliance, simplifying audits and ensuring alignment with FSMA requirements.
Labor efficiency is another key benefit. By reducing manual data entry, organizations can optimize workforce allocation and improve productivity in environments where labor shortages remain a challenge.
From Concept to Reality: Garland Verify Edge
The impact of AI-powered OCR becomes clear when applied in real operations.
At Garland, we developed Garland Verify Edge, an AI-powered OCR application integrated into shopfloor operations. The system focuses on capturing and validating PTI labels and critical product data in real time.
The solution has been deployed across operations managing over 300,000 cases for major U.S. retailers. This implementation enabled real-time validation at receiving and shipping, reduced labeling errors, improved traceability, and strengthened compliance processes.
Garland Verify Edge demonstrates that OCR is not just a support tool but a core operational capability. By embedding intelligence at the edge, it transforms data capture into actionable insights.
Food Safety as a Data System
Food safety is not only a regulatory function; it is the result of a data-driven system. Accurate data capture, real-time visibility, and end-to-end traceability are essential.
AI-powered OCR strengthens these capabilities by reducing data gaps and improving accuracy. Better visibility also contributes to reducing food waste and improving supply chain efficiency.
As supply chains become more complex, the ability to capture and use data effectively will define operational success.
Challenges and the Path Forward
Despite its advantages, implementing AI-powered OCR requires addressing key challenges. Data variability across suppliers requires continuous model training. Integration with WMS and ERP systems is essential to unlock full value.
Organizations must also invest in training and change management to ensure adoption. Technology alone is not sufficient; processes and teams must evolve together.
The Future of Intelligent Warehousing
The convergence of WMS, AI, and OCR is shaping a new generation of intelligent warehouses. These facilities will act as real-time decision centers, integrating data from multiple sources and enabling predictive capabilities.
Future developments will include integration with IoT devices, advanced analytics, and enhanced traceability solutions. OCR will remain a foundational component of this transformation, enabling the shift toward fully digital supply chain operations.
About the Author
Luis Polo is an Electrical Engineer and Supply Chain and Operations leader with over 15 years of experience in the food industry, including leadership roles at Nestlé, Fonterra, and Garland Food. He is a Senior Member of IEEE (Institute of Electrical and Electronics Engineers) and a Fellow Member of the British Computer Society (BCS). He holds an MBA, a Master’s in Logistics, and is a Certified Supply Chain Professional (CSCP).
He specializes in AI-driven supply chain transformation, developing solutions in OCR, computer vision, demand forecasting, and logistics optimization. During 2025, his AI-driven applications were recognized at the Supply Chain Excellence Awards USA for their impact on visibility, efficiency, and food safety.
He is the author of the books Supply Chain and AI: Transforming Logistics and Operations in the Digital Age and Inventory Variation in Raw Materials in the Food Industry: A Practical and Analytical Approach (2016), published in three editions, along with multiple research publications on AI in food supply chains.
He currently serves as Supply Chain & Operations Manager at Garland and is a professor in the MBA program at South Florida International College (SFIC)
