Jan 29, 2026
From Farm to Fork at Gulfood: How AI, Blockchain, and Human Talent Will Rewire Trust in the Global Food Chain
By Abdul Bari Kareem, Co-founder and CTO, T57
On January 26, 2026, I sat in the audience at Gulfood listening to our Founder, Chairman, and Head of Strategy, Afzal Hussain Mohammed Nakheeb, speak on the panel “Break-Through Technologies and AI-Powered Automations: Strategic Value Creators for an Intelligent Food System.” He was joined by Shail Khiyara, CEO of Swarm, Marc Oshima, CEO of Oshima Good Food, and Dr. Grace S. Thomson, Director of the AI Policy Clinics at the Center for AI & Digital Policy (CAIDP). Hearing them on that stage in Dubai, with the global food industry all around us, crystallized for me what we at T57 must focus our energies on.
Walk the aisles at Gulfood, and you can almost sense the underlying challenges flowing through the global food system. I spoke with industry insiders, and many alluded to shipments arriving late or spoiled, prices swinging wildly, and buyers still making decisions with partial, sometimes unreliable information. Yet the technologies to change this story—AI, blockchain, IoT, and new data governance models—are already here. The real question, as our panel clarified, is how fast we can turn them into trusted, usable infrastructure from farm to fork.
Across the food chain, everyone is flying partly in the dark. That is the terrible truth. Farmers rarely know in real time what demand and prices will look like in the weeks ahead. Buyers and chefs often receive goods that do not meet expected quality or shelf-life standards, forcing last-minute menu changes or write-offs. Consumers trust labels and branding more than verifiable data because that data is not accessible in a simple, human-friendly way. This is not just a technology gap; it is a systems gap. Data exists, but it is fragmented, hoarded, and rarely converted into decisions that protect margins and people simultaneously.
How can AI and local intelligence rebuild trust from farm to fork?
Afzal’s intervention on the panel went straight to the heart of this problem: AI in food cannot be one giant, generic model sitting in the cloud. It must be local—built on regional realities of weather, soil, water, and demand. He spoke about the need for smaller, regional AI models and for public-private partnerships in which governments, universities, and platforms like T57 co-create these models with proper governance and regulation baked in. That is exactly the architecture we want to pursue at T57: localized intelligence, tuned to a farmer’s actual conditions and buyer needs, but connected into a global network so shocks in one market can be anticipated by actors in another.
Can traceability reach every kitchen and consumer?
Traceability is the clearest expression of this transformation. During the Q&A after the panel discussion, a question from the hospitality side asked whether traceability could trickle down to kitchens and venues. Afzal painted a picture that mirrors what we are building at T57: imagine a restaurant in Dubai scanning a product and instantly seeing the exact farm in Abu Dhabi where it was grown, the date and time of harvest, the name of the producer, the storage temperatures at every leg of the journey, and whether the product was ever thawed and refrozen. AI helps interpret and act on this information, but blockchain and IoT make the data tamper-proof and real-time. When a refrigerated container is unplugged for a few hours at sea, everyone in the chain should know—and be able to price that risk accordingly.
This same visibility is essential for food safety, compliance, and sustainability claims. Non-GMO, organic, low-carbon, fair trade—these labels cannot rely on trust alone in a world of complex, multi-country supply chains. By combining sensor data, satellite imagery, logistics telemetry, and transaction records, AI can flag anomalies, predict quality outcomes, and surface risks before they become crises. For us at T57, this is not just a feature; it is the core of a new food operating system where data moves as freely and reliably as the goods themselves.
What will it take to make an intelligent food system usable for everyone?
But none of these matters if only a handful of highly educated actors can use it. One of the most powerful moments in the session was when Afzal described a simple use case: a buyer sending a voice note on WhatsApp—“I need the cheapest, best‑quality, organic, non-GMO oranges this week”—and having AI do the heavy lifting behind the scenes. Most people working in farming, trading, logistics, and even many kitchens are not data scientists or AI prompt engineers, and they should not have to be. In my role as CTO, that is a design constraint: interfaces must feel like messaging, not like programming.
The other panelists sharpened the human and governance dimensions we technologists cannot ignore. Shail emphasized that AI will not deliver value without people, and urged organizations to start with high-stakes decisions rather than abstract pilots. That resonated deeply with how we are focusing on our roadmap at T57: we are wiring AI into concrete choices—what to ship, where to source, how to price—before anything else. Marc, drawing on his experience in controlled-environment agriculture, spoke about vertical farms. These farms produce millions of data points that enable real-time course corrections, making yields more predictable and resilient. They show us the decision support we want to bring to open-field farmers and traders, too.
Dr. Grace Thomson anchored the conversation in ethics, law, and national strategy. She spoke about the UAE’s Food Security Strategy 2051, recommendations on AI ethics from global bodies, and the hard questions enterprises must ask vendors about data provenance, consent, bias, and accountability. As I listened, I saw our own stack through that lens: T57 is not just connecting data and models; we are also embedding transparency, auditability, and clear lines of responsibility for what our systems do.
For T57, Gulfood 2026—and that specific panel—was more than a conference slot. It was a mirror and a mandate. In that room, with Afzal on stage alongside Shail, Marc, and Dr. Grace, the contours of an intelligent food system were laid out: regional AI models rather than monoliths, traceability from farm to fork, human-centric interfaces, and strong governance of data and ethics.
My job now is to stay focused on that shared vision and turn it into code, infrastructure, and services that farmers, buyers, traders, and head chefs can all use without friction. If we succeed, the next time we return to Gulfood, “farm to fork” will no longer be a slogan we discuss on panels. It will be a transparent, measurable, and shared reality we show on the ground.
Walk the aisles at Gulfood, and you can almost sense the underlying challenges flowing through the global food system. I spoke with industry insiders, and many alluded to shipments arriving late or spoiled, prices swinging wildly, and buyers still making decisions with partial, sometimes unreliable information. Yet the technologies to change this story—AI, blockchain, IoT, and new data governance models—are already here. The real question, as our panel clarified, is how fast we can turn them into trusted, usable infrastructure from farm to fork.
Across the food chain, everyone is flying partly in the dark. That is the terrible truth. Farmers rarely know in real time what demand and prices will look like in the weeks ahead. Buyers and chefs often receive goods that do not meet expected quality or shelf-life standards, forcing last-minute menu changes or write-offs. Consumers trust labels and branding more than verifiable data because that data is not accessible in a simple, human-friendly way. This is not just a technology gap; it is a systems gap. Data exists, but it is fragmented, hoarded, and rarely converted into decisions that protect margins and people simultaneously.
How can AI and local intelligence rebuild trust from farm to fork?
Afzal’s intervention on the panel went straight to the heart of this problem: AI in food cannot be one giant, generic model sitting in the cloud. It must be local—built on regional realities of weather, soil, water, and demand. He spoke about the need for smaller, regional AI models and for public-private partnerships in which governments, universities, and platforms like T57 co-create these models with proper governance and regulation baked in. That is exactly the architecture we want to pursue at T57: localized intelligence, tuned to a farmer’s actual conditions and buyer needs, but connected into a global network so shocks in one market can be anticipated by actors in another.
Can traceability reach every kitchen and consumer?
Traceability is the clearest expression of this transformation. During the Q&A after the panel discussion, a question from the hospitality side asked whether traceability could trickle down to kitchens and venues. Afzal painted a picture that mirrors what we are building at T57: imagine a restaurant in Dubai scanning a product and instantly seeing the exact farm in Abu Dhabi where it was grown, the date and time of harvest, the name of the producer, the storage temperatures at every leg of the journey, and whether the product was ever thawed and refrozen. AI helps interpret and act on this information, but blockchain and IoT make the data tamper-proof and real-time. When a refrigerated container is unplugged for a few hours at sea, everyone in the chain should know—and be able to price that risk accordingly.
This same visibility is essential for food safety, compliance, and sustainability claims. Non-GMO, organic, low-carbon, fair trade—these labels cannot rely on trust alone in a world of complex, multi-country supply chains. By combining sensor data, satellite imagery, logistics telemetry, and transaction records, AI can flag anomalies, predict quality outcomes, and surface risks before they become crises. For us at T57, this is not just a feature; it is the core of a new food operating system where data moves as freely and reliably as the goods themselves.
What will it take to make an intelligent food system usable for everyone?
But none of these matters if only a handful of highly educated actors can use it. One of the most powerful moments in the session was when Afzal described a simple use case: a buyer sending a voice note on WhatsApp—“I need the cheapest, best‑quality, organic, non-GMO oranges this week”—and having AI do the heavy lifting behind the scenes. Most people working in farming, trading, logistics, and even many kitchens are not data scientists or AI prompt engineers, and they should not have to be. In my role as CTO, that is a design constraint: interfaces must feel like messaging, not like programming.
The other panelists sharpened the human and governance dimensions we technologists cannot ignore. Shail emphasized that AI will not deliver value without people, and urged organizations to start with high-stakes decisions rather than abstract pilots. That resonated deeply with how we are focusing on our roadmap at T57: we are wiring AI into concrete choices—what to ship, where to source, how to price—before anything else. Marc, drawing on his experience in controlled-environment agriculture, spoke about vertical farms. These farms produce millions of data points that enable real-time course corrections, making yields more predictable and resilient. They show us the decision support we want to bring to open-field farmers and traders, too.
Dr. Grace Thomson anchored the conversation in ethics, law, and national strategy. She spoke about the UAE’s Food Security Strategy 2051, recommendations on AI ethics from global bodies, and the hard questions enterprises must ask vendors about data provenance, consent, bias, and accountability. As I listened, I saw our own stack through that lens: T57 is not just connecting data and models; we are also embedding transparency, auditability, and clear lines of responsibility for what our systems do.
For T57, Gulfood 2026—and that specific panel—was more than a conference slot. It was a mirror and a mandate. In that room, with Afzal on stage alongside Shail, Marc, and Dr. Grace, the contours of an intelligent food system were laid out: regional AI models rather than monoliths, traceability from farm to fork, human-centric interfaces, and strong governance of data and ethics.
My job now is to stay focused on that shared vision and turn it into code, infrastructure, and services that farmers, buyers, traders, and head chefs can all use without friction. If we succeed, the next time we return to Gulfood, “farm to fork” will no longer be a slogan we discuss on panels. It will be a transparent, measurable, and shared reality we show on the ground.
