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In our Supply Chain Trends and Digitalization Study 2026 focused on the Food sector, we identified a transition: companies have stopped simply “recording data” to focus on combating perishability through prediction driven by new technologies.
We live in an accelerating technological era. While the 52% of the companies have already based their operations on Big Data and analytics, the objective now is to scale towards a applied intelligence that protects profitability and minimizes waste.
By 2026, the Advanced Data Analytics is the dominant technological trend, selected by the 76% of the respondents.
In the food sector, where product expiration is unforgiving, companies are migrating from past analysis to future analysis.
La generative artificial intelligence is the second technological priority that professionals in the food sector want to implement in the management of their supply chain. But, even though it's at the “top of mind” of emerging trends, real adoption isn't as tangible:
This suggests that 2026 will be the year of “deployment or discard”: organizations will stop playing with generic chatbots to search for specific use cases that impact, such as the generation of demand scenarios or the automation of reports.
Digital transformation in this sector is not a software problem, it's a structural problem. El 60% of the respondents identify the Organizational Silos as the main barrier to transformation, overcoming even the lack of budget (40%).
The data shows that most of the Supply Chain, Commercial and Finance areas are only “Partially aligned” (they share information, but not decisions). The winning trend will be the implementation of processes of Integrated Planning (IBP/S&OP) that force collaboration, since technology alone cannot fix a broken organization chart
Unlike other sectors, in the Food sample, financial efficiency has a higher priority. “Decrease working capital” and “Improve demand accuracy” consistently rank above other objectives. With the “Inventory Break” (56%) and the “Oversupply” (44%) as the most painful operational challenges, the strategy for 2026 focuses on refining inventory: having just enough, no more (loss/cost) and no less (lost sale).
Currently, the food sector is experiencing an accelerated but uneven migration. Although most companies have left behind manual management to digitize their records, the value today is not only to have data, but to use it to optimize operations, reduce losses and increase productivity.
It is unquestionably the technology with the highest traction, implemented by 52% of leading companies. In an industry where inventory “expires”, analytics has ceased to be a reporting tool and has become a prediction engine. It is no longer a question of knowing how much was sold last week, but rather of questioning consumption patterns to adjust production and distribution to the day, minimizing the risk of expiry dates and returns.
Unlike other sectors where AI is a plan for the future, in the food industry it is already positioned as the second most implemented technology (40%). Its practical application is obsessively focused on Demand forecast accuracy. Since the cost of error is measured in tons of waste, companies are adopting machine learning algorithms to refine their orders, although the big leap still lies in relying on these systems for autonomous decision-making without human intervention.
With an adoption of 32%, SCMs are increasingly being adopted because they allow for the integration of demand planning, inventories, purchasing and logistics. Its adoption makes the difference between a company that suffers stock failures due to misalignment and one that synchronizes its supply with real demand.
Strangely enough, despite the critical importance of traceability and the cold chain, technologies such as the Internet of Things (IoT) and Robotics have a lower penetration (20% and 12% respectively). Although connected sensors provide real-time visibility into temperature and product quality, infrastructure costs remain a high barrier. Many food companies still prioritize digitizing their decisions (software) rather than automating their physical assets (hardware).
The analysis of the data confirms a direct correlation: the quality of the planning is proportional to the level of digitalization of the company. Investment in technology is validated by operating results.
Although Generative Artificial Intelligence is at the top of the agenda, its deployment in plants and distribution centers in the food sector does not seem to be as fast. There is a difference between the desire for new technologies and operational reality: most companies want to use it, but few have been able to effectively integrate it into their daily lives.
For a significant segment of the industry (28%), this technology remains a difficult abstract concept to land. Even though curiosity is high, many leaders admit not knowing how to transform that technological power into practical solutions for the supply chain. The main obstacle is no longer access to the tool, but rather identifying clear use cases that justify investment in a sector with such tight margins.
Only 12% of the companies surveyed have managed to go beyond the experimentation stage to operate with Generative AI in a real environment. This exclusive group is no longer exploring possibilities; it has integrated these models into its workflows to streamline decision-making and process complex information, turning what for many is a novelty, into a functional competitive advantage.
In a market where inventory loses value every minute, organizations that manage freshness with predictive algorithms coexist with others that rely on manual processes, revealing an ecosystem that is advancing at two very marked speeds.
The obstacles to digitalization in the food sector change dramatically depending on the scale of the organization. Each stage of growth presents a particular friction that requires different solutions.
For this segment, the Lack of budget is in first place. These companies usually have the agility needed to adopt new technologies, but the priority lies in maintaining operational liquidity. Your path to digitalization depends on find accessible tools that make it possible to professionalize management without compromising cash flow.
These organizations are going through a phase where operational complexity often exceeds planning. By pointing out the “Lack of clear vision” And the “Organizational silos” as their biggest problems, show a structure that has grown faster than their strategy. Departments begin to operate in isolation, making it difficult to define a unified digital north.
At this level, the restriction ceases to be capital and becomes the structure itself. His biggest pain is the “Organizational silos”. Bureaucracy and lack of fluid communication between areas prevent agility. The real challenge is managing change: aligning Finance, Commercial and Supply Chain so that they work as a single cog.
In an industry where margins are tight and the product perishes, performance indicators act as the financial compass for the operation. Based on data analysis, supply chain management in 2026 prioritizes three fundamental metrics to balance product availability with capital efficiency.
The supply chain in the food sector lives in a constant tension between guaranteeing the product on the shelf and avoiding waste. The study identifies the friction points that directly impact the profitability of companies.
It is positioned as the number one challenge, pointed out by the 56% of the leaders. In the food industry, a shortage rarely means a delayed purchase; it means that the consumer chooses the competition immediately. Ensuring availability is the top priority to protect market share and customer loyalty.
Located in second place (52%), the difficulty in predicting demand creates instability throughout the operation. The lack of precision about how much and when to supply prevents efficient planning. In an industry governed by expiration dates, an incorrect forecast directly translates into decline or lost sales.
Excess inventory (44%) and product obsolescence (40%) appear as critical interconnected challenges. Accumulating more merchandise than necessary immobilizes working capital and dramatically increases the risk of loss due to maturity. This “silent cost” directly attacks the company's profit margin.
The reliance on manual processes takes a heavy toll. The workload in data processing (44%) reflects slow operation. Teams spend a large part of their time cleaning information instead of analyzing strategies, leading to decision errors in a market that requires speed.
The time when planning relied on instinct, manual data and lifelong processes is changing. Now, the urgency of accurate data is a priority on the agenda to protect profitability and product freshness.
While 60% of companies struggle against the inertia of manual processes and the lack of communication between areas, a select group of leaders (12%) are already capitalizing on the use of advanced analytics to anticipate the market. The technological difference has a direct impact on finances; whoever forecasts better, wastes less and sells more.
In 2026, investment in technology must be understood as a strategy for the development of competitive advantages. The objective transcends product availability; it is about achieving it with the least fixed capital and the least possible waste. In a market that punishes expiration, the ability of data to have greater accuracy and possibilities is the new standard.
Attempting to apply Artificial Intelligence to disordered processes is as ineffective as managing perishable products using data from last week. Based on the insights from this study, these are the recommended actions depending on your organization's stage of maturity:
Your priority is focused on preparing the cultural and operational structure to receive the technology. Skipping these fundamental steps often results in investments that don't lead anywhere.
You already have the foundations. The objective now changes: move from using information to audit the past to using it to shape the immediate future.
The food sector is changing at a rapid pace. To lead, you need data, not assumptions. Access our exclusive trend analysis and discover where your organization is on the logistics innovation map.
