By Stephen Dombroski, Director, Consumer Markets, QAD | Redzone
FSMA 204 delays don’t reset the clock. Retailers and consumers are already demanding end-to-end lot traceability now, regardless of regulatory timelines.
True farm-to-fork traceability isn’t a single platform purchase. It requires integrating people, processes, and systems across every enterprise in the supply chain.
2026 is the year to build the infrastructure (people alignment, process redesign, and cross-enterprise data integration), so 2027 can be spent tuning it, not starting it.
FSMA 204 has been delayed, again. And I know what some of you are thinking, thank goodness. We can exhale. Take some refreshment, kick the can right? Wrong!
Let me be straight with you. The clock is not waiting. The consumer is not waiting. And no matter how many times a regulatory deadline gets pushed, the market does not care about your compliance schedule. The market keeps moving and does not follow the regulatory schedule. It moves to its own drummer.
But here is the thing about kicking a can down a road that is already packed with interconnected systems, enterprise-wide data gaps, and a consumer base that increasingly demands a digital dossier on everything they put in their bodies: eventually you hit a wall. And 2026 is that wall. Not because the government says so. Because the ecosystem says so. Because if we do not do the hard work of connecting people, processes, and systems this year, 2027 becomes a year of chaos instead of calibration, and 2028 becomes a very public failure.
This is not a compliance article. This is a challenge.
Stop thinking about one system
Here is where most organizations get it wrong. They hear “automated traceability” and they start shopping for a platform. One system. One dashboard. One vendor. Done.
That is not how food moves. That is not how supply chains work. That is not how the real world is built.
A finished good sitting on a retail shelf has a story that runs through dozens of hands, hundreds of touchpoints, and potentially thousands of data records. The ingredients in that product came from growers who track in one system. The co-manufacturer that blended or cooked or assembled that product operates in another. The packaging that wrapped it came from a supplier on yet another platform. The 3PL that staged it in cold storage has its own WMS. The distributor who moved it to the retailer runs their own ERP. And somewhere in the middle of all of that, a quality team is manually reconciling spreadsheets and hoping nothing got lost between point A and point Z.
That is not traceability. That is a liability waiting for a recall to expose it.
True farm-to-fork traceability in 2026 and beyond is not about one system. It is about the intelligent, automated linkage of multiple systems across multiple enterprises, with the ability to pull a single coherent record that tells the complete story of that product. It is about what it is, where it has been, who touched it, under what conditions, and when. That is the digital passport. And building it requires a fundamentally different mindset than buying software.
The three connective failures nobody talks about
Ask any supply chain leader about their traceability posture and they will tell you about their ERP, their blockchain pilot, their QR code initiative. What they will not volunteer are the three connective failures that live between those systems and silently destroy traceability integrity.
The first is the people gap. Technology does not trace food. People do. A system is only as good as the human beings entering data into it, validating it, and acting on it. When you talk about building an automated traceability infrastructure, you are simultaneously talking about retraining your workforce on the floor, in the warehouse, in procurement, in quality, in logistics. If your receiving team is still writing lot numbers on paper tickets and entering them two days later, your real-time traceability system is fiction. The people have to change before the data gets clean. And clean data is the entire foundation.
The second is the process gap. Most organizations have processes that were designed around how traceability used to work; siloed, reactive, and built for audits rather than operations. Those processes were never designed to feed live data into a connected ecosystem. Retrofitting a new system onto a broken process does not fix the process. It just automates the broken parts faster. Before you integrate, you have to redesign. Before you go live, you have to go deep on process mapping across every enterprise in your supply chain; upstream and downstream. Then you need to align on what data gets captured and by whom. That alignment work is unglamorous. It does not have a ribbon-cutting moment. But it is the most important thing you will do in 2026.
The third is the enterprise gap. This one is the hardest because you cannot fix it alone. Your traceability is only as strong as your weakest supplier link. If your Tier 2 ingredient supplier is still running on a legacy system that cannot export a structured lot record, your digital passport has a hole in it. Getting enterprise-to-enterprise data exchange right means rolling up your sleeves and doing the integration work which includes API connections, EDI bridges, and standardized data schemas. It might also mean that you need to help smaller suppliers upgrade their capabilities just to participate in your chain. That is a partnership investment, not just a technology investment.
The consumer is already there. Are you?
Forget FSMA 204 for a moment. Look at what is happening in the market.
Retailers are demanding traceability data from their suppliers. They are demanding now, not in two years, now. Major grocery chains have already issued requirements to their private label and branded suppliers for end-to-end lot traceability that can be surfaced at the product level. QR codes on packaging are no longer a novelty. They are a demand signal. When a consumer scans that code, they are asking a real question: where did this come from, what went into it, who handled it, and can I trust it?
That question is no longer aspirational. It is transactional. Brands that can answer it clearly and completely will win loyalty. Brands that serve up a dead link, a generic landing page, or worse, nothing are sending a bad message.
The finished product is just the entry point. The consumer increasingly wants visibility into the WIP. They want to know the batch of tomato paste that went into that sauce. They want to know the farm where the basil was grown. They want to know if the packaging film meets food contact safety standards. That level of transparency does not happen without a connected, automated, data-rich traceability backbone that runs from raw material through every transformation to the shelf. And it absolutely does not happen if you are waiting until 2027 to start building it.
Why 2026 is where the details have to land
Think about what 2027 has to be. It has to be the year of fine-tuning, of training, of stress-testing your system under real operational conditions. It has to be the year your teams build confidence in the data, your AI tools begin learning the idiosyncrasies of your specific supply chain, and your supplier network has time to align their outputs to your inputs. That is a full year of productive work.
But if 2026 is still the year you are debating platform selection, negotiating data sharing agreements, and trying to reconcile what a Critical Tracking Event means to your third-party co-packer versus what it means to your ERP team then 2027 has nothing to work with. And 2028, when regulatory and market forces converge in ways that cannot be deferred, becomes a crisis.
2026 is the year where every critical decision has to be made. Which systems will talk to which systems. What data standards will be adopted across your enterprise network. How AI will be layered onto the traceability infrastructure to handle the inevitable complexity that lives inside every real supply chain. The lot splits, the co-manufacturing exceptions, the multi-origin blends, the repack events that shatter the linear traceability chain and demand intelligent inference to put it back together. These are not edge cases. These are the daily realities of food manufacturing and distribution, and they are the exact places where manual traceability falls apart and automated intelligence has to step in.
The AI imperative in a multi-system world
Here is the reality of traceability in a complex food operation: the data is messy, the rules are inconsistent across enterprises, and the exceptions outnumber the clean records by a ratio nobody wants to admit publicly.
That is not a data quality failure. That is the nature of a supply chain that spans thousands of human decisions made under real-world operational pressure. Lots of consolidations happen. Partial shipments happen. Cross-contamination events happen. Rework happens. The traceability record for a finished good is rarely a clean, linear data chain from farm to fork. It is a tangled web. Trying to walk that web backward in the event of a recall or forward in the event of a proactive market withdrawal, requires intelligence that scales beyond what any human team can manage manually.
This is where AI earns its place in traceability. Not as a buzzword. Not as a dashboard feature. But as the cognitive layer that sits on top of your multi-system infrastructure and does the work of connecting records that do not connect cleanly on their own. That means intelligent lot linkage, anomaly detection in data chains, and predictive flagging of traceability gaps before they ever become compliance exposures Another critical element is natural language querying of traceability records so that a quality manager at 2 AM can ask a real question and get a real answer in seconds rather than hours.
Building that AI capability takes time, and it takes data. Lots of clean, structured, consistently formatted data flowing from your integrated systems. Which means the integration work of 2026 is not just a compliance prerequisite, it is the training ground for the AI that will define your competitive advantage in 2028 and beyond.
The challenge, plainly stated
The digital passport is not a product you buy. It is an infrastructure you build across systems, across processes, across enterprises, and across the people who operate all of the above. It is the most complex operational initiative most food companies have ever undertaken, and it cannot be delegated to IT or handed off to a consultant. It has to without question span the entire business ecosystem.
It requires leadership that understands the stakes. It requires a supply chain organization that is willing to do the hard, unglamorous work of data alignment before the exciting work of AI deployment. It requires a supplier network that is treated as a partner in this journey rather than a downstream compliance burden. And it requires an honest reckoning with the fact that the consumer is already ahead of the regulation and they don’t care about your implementation timeline.
2026 is where the details land. 2027 is where you tune, train, and harden. 2028 is where you lead or where you explain why you are not ready. And pay for it.
The challenge has been issued. The passport is waiting to be written.
Stephen Dombroski is QAD’s Director for the Consumer Products and Food & Beverage vertical markets. Steve has over 30 years experience in manufacturing and supply chain, and has helped multiple companies in a number of industries to implement S&OP concepts and processes.
