24 CADERNOS DE ANÁLISE E PROSPETIVA CULTIVAR N.º 33 ABRIL 2025 – Dados na agricultura receive substantial investment by development partners because they connect to global supply chains, while data on local food crops that feed populations remains sparse and outdated. This creates a distorted picture of agricultural sectors, where sometimes policymakers have detailed information about crops that generate foreign exchange but limited visibility into those that ensure national food security. Fragmentation Across National and International Actors Even when the will to improve agricultural data systems exists, fragmentation across both national institutions and international partners undermines progress. Ministries, national statistics offices, and external funders often operate in silos, each guided by different mandates, timelines, and accountability frameworks. This results in overlapping surveys, duplicated investments, and parallel systems that fail to communicate. In many countries, development partners launch uncoordinated data initiatives that crowd the landscape with dashboards, registries, and pilots, often without a long-term sustainability plan or connection to national priorities. Governments are not passive recipients of this fragmentation. Institutional competition frequently leads to internal divisions over data ownership and authority, creating a fractured ecosystem where decision-makers lack a shared view of the agricultural landscape. The Platformization of Agriculture: Risks, Gaps, and the Role of Public Systems The agricultural sector is widely misunderstood. Many people still hold a romanticized view of farming, imagining pastoral landscapes, traditional practices, and a way of life rooted in community and land stewardship. For many producers, this remains true: farming is fundamentally a home and livelihood. For others, however, agriculture has evolved into a high-tech enterprise, managed through computers, sensors, and smartphones, integrated with global supply chains, and optimized through data analytics. Both are farmers, but the realities they navigate are vastly different. Today, Big Tech and agribusinesses are developing integrated digital platforms that bundle advisory services, inputs, finance, and market access. These systems blur traditional boundaries and increasingly serve as agriculture’s organizing structure. The intelligent use of data holds immense promise. It can reduce production costs, optimize resource use, predict harvests and price trends, and minimize losses. For many farmers, this can lead to greater profitability, competitiveness, and sustainability. Yet the platformization of agriculture brings serious risks. As these systems consolidate, they tend to entrench the market dominance of incumbents, increase dependency on closed ecosystems, and contribute to fragmented, siloed data landscapes. Critically, these privately managed data systems often bypass national statistical systems altogether. When governments cannot access or integrate platform-generated data, public institutions lose the ability to plan effectively, regulate markets, or deliver services that reflect the needs of all producers, from tech-enabled agribusinesses to smallholders cultivating only a few hectares of land. This separation of data ecosystems creates profound governance challenges. Without interoperable, publicly governed systems, agricultural policies are likely to be skewed toward those who are digitally visible, leaving large numbers of producers in low- and middle-income countries effectively invisible. The inability to reconcile platform data with national datasets weakens state oversight and makes it more difficult to ensure that land use regulations, labor protections, environmental safeguards, and food safety standards are applied consistently and fairly. At the same time, a critical insight is often overlooked: private-sector data cannot replace official agricultural statistics. Precision farming data from equipment manufacturers, satellite yield estimates from agribusinesses, and real-time market data from digital platforms offer speed and granularity, but they lack the representativeness, methodological consistency, and historical comparability of national agricultural censuses and surveys. Moreover, official statistics serve as the benchmark against which private-sector forecasts and models are validated. If national systems are weakened or underfunded, private-sector data may temporarily fill some gaps but will ultimately become less reliable and harder to regulate. These technological shifts are also occurring primarily in well-resourced, data-rich environments. Most LMICs still lack the foundational elements needed to participate in or shape this digital transformation. Many smallholder farmers have no access to mobile networks, let alone cloudbased platforms. In least developed countries, over a third of people remain offline or stuck on 2G connections. Even in relatively advanced agricultural economies such as Brazil, up to 70 percent of farmland lacks reliable connectivity. However, the digital divide is not only about infrastructure. It is also about capacity, voice, and control. Many farmers have little say in how data about them is collected, stored, or used. In some cases, digital tools can unintentionally deepen exclusion rather than reduce it. As AI becomes embedded in everything from weather forecasting to credit scoring, the risks of bias, opacity, and misuse increase. With-
RkJQdWJsaXNoZXIy MTgxOTE4Nw==