The growing discourse around artificial intelligence (AI) is riddled with lofty promises and technical jargon, making AI compliance a fuzzy, almost mythical concept for many in the F&B industry—talked about often, but rarely understood in practical terms. While the promise of AI-driven automation suggests a future where compliance tasks are streamlined and error-free, the reality is far less clear. For many professionals, AI remains a black box, sparking both curiosity and skepticism. How does it actually work? Can it truly adapt to the complexities of regulatory compliance? And most importantly, can it be trusted with critical processes like verifying certificates of analysis (COAs)?

Despite the growing presence of AI in the food industry, most teams are still relying on rigid, rule-based systems that offer only partial automation. Traditional tools like optical character recognition (OCR) have provided some relief by extracting data from COAs, but they often struggle to capture the nuances of supplier variations and ever-changing regulatory requirements. This gap between expectation and reality leaves many wondering: Is AI compliance just another overhyped trend, or is it finally reaching a point where it can deliver meaningful, reliable improvements?

This blog marks the beginning of a series where we aim to separate fact from fiction and debunk general myths surrounding AI in F&B compliance. We’ll explore the misconceptions holding some teams back and showcase the real potential AI offers for transforming workflows.

OCR paved the way and AI redefines the path forward 

OCR was a big step forward at its inception, but it suffered from a key limitation. Namely, OCR-based COA processing has traditionally relied on processes that demand consistency from inconsistent sources. OCR systems, while once a revolutionary step forward, operate based on templates. They excel at extracting data, but only within rigidly defined boundaries. A small adjustment to a supplier’s document layout, for example, could impact the entire process. This reliance on manual intervention for setup, troubleshooting, and adjustment is what makes OCR so labor-intensive despite being marketed as “automation.”

The misconception that AI is essentially OCR with a tech-savvy rebranding misses the mark. This belief stems from familiarity with OCR’s limitations, which have long impacted operations across the industry, along with the fact that OCR solutions have used AI-related technologies to improve their effectiveness. Skepticism is understandable, but AI-powered tools for F&B represent not just an upgrade, but a fundamental shift in how COA workflows are managed. The transformation is more profound than many realize, and its impact stretches across efficiency, adaptability, and what’s possible for food safety and compliance teams. 

With the arrival of TraceGains’ intelligent document processing (IDP), an AI-driven solution for material compliance and lot-level ingredient quality control, a new standard has been set for the F&B industry. Designed on OpenAI’s cutting-edge foundation model, TraceGains’ IDP also leverages a proprietary, industry-specific data layer to ensure unmatched accuracy and context-aware processing.

How AI enhances COA processing efficiency

Purpose-built AI has adaptability at its core. Rather than relying on rules and templates, TraceGains’ system is able to interpret context. It does this by pairing the sophisticated natural language processing capabilities of cutting-edge generative AI with unique data insights, structures, taxonomies and rule sets based on nearly two decades of industry data management experience and insight. This is a key distinction. Imagine processing COAs from dozens, or even hundreds, of suppliers who each have their own format. AI trained on rich contextual data doesn’t require you to teach the system every possible variation up front. Instead, it learns from the information presented, evolving as more data flows through the system. This means COA processing no longer buckles under variability—instead, it thrives on it.

TraceGains’ IDP breaks new ground

TraceGains’ IDP solution demonstrates the true impact of this unique AI in practice. With an impressive accuracy rate right out of the gate, TraceGains’ IDP dramatically reduces the margin of error compared to OCR systems. This higher precision is critical when processing compliance data, where even minor errors can have significant repercussions. By alleviating the need for constant corrections and rework, the system allows teams to process COAs with greater confidence and far less effort. 

However, the goal isn’t necessarily to remove humans from the equation. While IDP can identify and flag potential issues with impressive accuracy, it also serves those issues up for human validation and intervention in an intuitive user interface. Human experts can focus on the issues that require their attention, and can always correct, amend or even override the system’s findings. And when they do, the system remembers. Machine learning models accept input, identify patterns, prioritize relevant data fields, and improve themselves based on human input level. Ultimately, the time saved doesn’t just lie in getting data processed more quickly. End-users also gain back hours previously wasted on rework. With TraceGains’ AI capabilities, teams can reallocate resources to strategic decision-making, leaving repetitive manual tasks behind, and creating a more reliable and streamlined workflow from the start.

Revolutionizing COA workflows in the food industry

But the real disruption that TraceGains’ AI brings lies in its ability to reimagine outdated processes. For years, compliance professionals had little choice but to work within the confines of what OCR or manual effort allowed. Data had to be reshaped and organized around the limitations of the tools at hand. Today, AI does the reshaping instead, flipping the script entirely.

For example, traditional COA workflows often involve large teams, each handling individual segments of the compliance process to account for inefficiencies in automation software. With AI processing, one unified system can tackle these tasks holistically. From extracting allergen declarations to verifying ingredient specifications against internal standards, there’s no need for disparate workflows or repeated checkpoints. A single AI-powered engine cuts straight through the noise, delivering clarity and reducing the likelihood of human error.

Debunking the OCR myth 

The myth that “AI is just OCR with a fancy name” oversimplifies the transformative capabilities AI brings to the table. While OCR served as an important stepping stone, AI-powered technology has moved on, opening up new possibilities for adaptability, efficiency and accuracy. Rather than clinging to old definitions of what automation looks like, it’s time to reimagine the possibilities. 

TraceGains’ intelligent Supplier Compliance represents more than an evolution over OCR; it’s a revolution for compliance workflows. For F&B companies looking to reduce bottlenecks, gain actionable insights, and enhance product safety, the leap to AI isn’t just feasible. It’s inevitable. The only question is, how will you use it to stay ahead? 

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