Artificial Intelligence in the Agro-Industrial Complex: Issues of Legal Regulation and Prospects for Use

Svetskiy Arseniy Vladimirovich ORCID: 0000-0002-0678-4841 Junior Researcher of the Environmental, Land and Agrarian Law Department, Institute of State and Law of the Russian Academy of Sciences 10 Znamenka str., Moscow, 119019, Russia arseniy1107@gmail.com Other publications by this author

In the modern world, the agro–industrial complex (hereinafter referred to as the agroindustrial complex) of any state faces a number of problems, including population growth and the associated need for increased productivity, environmental problems, climate change, as well as a shortage of natural resources, soil contamination with pesticides, and others. Under these conditions, artificial intelligence (AI) is becoming a key tool for solving these problems. According to statistics and forecasts posted on the United Nations website, the world's population will reach 8.5 billion people in 2030 and increase further to 9.7 billion in 2050 (URL: https://www.un.org/en/global-issues/population (date of request: 03/07/2025)). In this regard, certain actions are being taken in various industries, both at the national and international levels, to ensure the livelihood of the growing world population. The need to increase the efficiency of agriculture and food production is one of the main tasks. AI technologies are already being used in this industry to optimize production. This is due to the fact that traditional farming methods are not able to meet the growing needs. Artificial intelligence is emerging as part of the solution and a pioneer in the technological evolution of the agricultural industry. AI solutions in agriculture are already widespread and cover areas such as real-time monitoring, harvesting, processing, crop cultivation, marketing, weed detection, yield forecasting, and crop quality control.

Thus, the relevance of the research is due to: the need for legal regulation of AI in agriculture to minimize risks and increase the effectiveness of technology implementation; insufficient number of comprehensive studies devoted to the analysis of Russian and international experience in regulating AI in agriculture, due to the novelty of AI technology itself, as well as its pace of development; formation of an understanding of the current situation in the field of legal regulation in agriculture. different stages of using AI in agriculture. The purpose of this study is to analyze modern legal, ethical and technological aspects of the introduction of artificial intelligence in the agro-industrial complex, as well as to develop proposals for improving regulation in this area.

According to scientists, the AI market in agriculture is currently most developed in three promising areas: machine learning, computer vision, predictive analytics. It is expected that, in terms of technology segmentation, the computer vision category will occupy the largest market share in the global agricultural AI market ^[3].

Artificial intelligence (AI) is already being used in many areas of agriculture, including tractors and comparable robots ^[1]. In these systems, AI is often used to detect collisions using computer vision and, in particular, to protect people moving in the working area of the machine. Despite the progressive development of the use of AI technologies in agriculture, the main areas of its use are still unclear, although there is a significant need for legal certainty on the part of manufacturers of AI systems due to the high rate of development of this technology.

Agriculture is faced with the need to constantly choose between different scenarios depending on a range of external conditions and a rather large uncertainty of prospects. For example, the weather changes from season to season, prices for agricultural materials fluctuate, the soil degrades, crops become unviable, weeds destroy crops, pests damage crops, and climatic changes occur from season to season. Since the stable state of agricultural crops directly depends on the chemical elements contained in the soil, it needs constant monitoring. Currently, agricultural producers have begun to actively use specialized unmanned aerial vehicles that use computer vision to take aerial photographs, while capturing a huge amount of data. Through these manipulations, the condition of crops in vast territories is monitored. In addition, there are systems that analyze a number of data to predict the harvest.

By analyzing various data sources such as temperature, weather, soil analysis, humidity, and historical yield indicators, artificial intelligence systems can predict which crops should be planted in a given year and when the optimal time for sowing and harvesting in a particular area will come, thereby increasing yields and efficiency of cultivation. The use of AI also makes it possible to reduce the amount of water, fertilizers, and pesticides used. Through the use of artificial intelligence technologies, it is possible to reduce the impact on natural ecosystems and improve the safety of workers, which, in turn, should lead to lower food prices and ensure an increase in food production in line with population growth ^[5]. Today, there are a number of databases that are used by AI systems in agriculture, such as:
FGIS "Agriculture", containing data on land resources, yields and subsidies; NASA POWER and AgERA5 contains climate data, as well as satellite data for agrometeorology; Sentinel Hub, containing satellite images for monitoring fields; FarmBeats contains data for managing agricultural machinery, etc. The Ministry of Agriculture has a database for monitoring the state of and the development of agriculture in the Russian Federation; there is a database of agricultural lands ^[10].

Many databases are created by foreign companies, which in turn complicates the process of interacting with the hosted data. This highlights the importance of creating such databases and regulating them at the national level. However, certain standards are needed in data collection for such systems, as well as regulation of information collection by the AI system itself, without ignoring the issue of data protection and database fault tolerance.

Since one of the main tasks of agriculture today is to provide nutrition to a rapidly growing population, agricultural production should also grow. One of the factors directly affecting this process is plant diseases, which lead to a decrease in the quantity and quality of crop production. Losses of agriculture due to diseases of agricultural crops can become critical. Weeds also represent one of the main threats to all agricultural activities. To combat this problem, there are several ready-made solutions using AI technology. One example of the use of AI in agriculture is the use by farmers of agricultural drones spraying pesticides, a special type of agricultural machinery that is unmanned aerial vehicles with special systems for applying chemicals to soil or plants.

However, the introduction of artificial intelligence in agriculture is accompanied by a number of legal, ethical and technical difficulties that require detailed study and regulation. The introduction of artificial intelligence technologies into the agricultural sector provides a number of advantages and opens up new opportunities, but, in turn, new risks and threats arise. As a rule, they are associated with an ethical, social and legal problem in the regulation of AI. The growing integration of AI into agriculture requires access to diverse datasets for training artificial intelligence systems.

The fundamental problem of digitalization in agriculture is that many AI systems never leave the academic test environment ^[6]. Accordingly, it is necessary for the legislator to fix certain rules for developers of AI systems when training such systems. In order to minimize risks, it seems necessary to introduce some kind of test level for the implementation of AI systems in agricultural production, which will show the possibilities in practice and eliminate further risks in the event of a system failure.

The following should be attributed to the ethical problems of regulating AI technology: systems require a significant amount of data for stable operation. However, the collection and use of this information should be regulated by strict rules in order to protect the rights of farmers and other participants in the process. Transparency should be ensured in how data on fields, crops, and current conditions in agricultural production are collected, stored, and used. This should include protecting personal information, preventing unauthorized access, and ensuring the legitimate use of such data.

Because the agro-industrial complex contains critical infrastructure facilities: elevators, irrigation systems, logistics chains, and agricultural laboratories. The introduction of information technologies in this area requires special legal regulation to minimize risks, prevent cyber attacks, and failures in the system algorithm. One of the key problems of government regulation in agriculture related to the introduction of AI and the use of data is the lack of a unified system for standardization and management of agricultural data. The disparity of information resources, namely, meteorological data, indicators of soil analysis, yield statistics, as well as the lack of clear legal mechanisms for their integration into AI algorithms make it difficult to create effective forecasting models. In addition, data protection issues remain unresolved, especially in the face of cyber threats to critical infrastructure.

In the modern agro-industrial complex, the problem of decentralization of information resources is of high importance. Agrochemical soil analysis data, meteorological indicators, phytosanitary monitoring, yield statistics, and financial and economic parameters of agricultural enterprises are accumulated in heterogeneous information systems belonging to various entities, from private agricultural holdings to state meteorological services. Such a dispersion of data can lead to legal conflicts related to the issue of ownership of information, the reliability of sources, as well as the protection of personal data in accordance with the Federal Law "On Personal Data" dated 27.07.2006 N 152-FZ.

The formation of unified digital platforms integrating disparate data arrays based on common exchange standards, such as the ISO 19115-1:2014 standard for geospatial information, is a strategic direction for the digitalization of agriculture. Such systems make it possible to provide artificial intelligence algorithms with relevant and verified data, which is critically important for improving the accuracy of predictive analytics. A legally significant aspect is the development of mechanisms for legitimate access to data, including licensing agreements and regulation of information exchange within the framework of public-private partnerships.

The introduction of such platforms will not only provide technological advantages – automation of precision farming, dynamic monitoring of crops using remote sensing of the Earth and yield forecasting based on machine learning – but will also create the basis for effective interagency cooperation. The integration of data into a single information space will allow government authorities to form an evidence base for making regulatory decisions, scientific institutions to conduct research on relevant data, and agricultural producers to optimize production processes in real time.

One of the problems in regulating artificial intelligence is the issue of liability in the event of an AI error. If technological systems based on artificial intelligence fail or make errors in the algorithm, the question arises as to who should be responsible for the consequences. For example, if AI–controlled agricultural machinery does not recognize weeds and destroys crops by mistake, the question arises as to who should compensate for the damage: the software developer (hereinafter referred to as the software), the equipment manufacturer, the device owner, or third parties. This problem also requires clear regulation in order to define the boundaries of responsibility in order to avoid disputes. When implementing legal provisions that regulate innovative technologies, including AI technology, it is necessary to take into account the levels of social, economic and other risks, that is, with an assessment of the possible consequences of the introduction of AI systems, to introduce control standards for them.

As for the problem related to the data that is used to train systems using AI, the following should also be noted. Manufacturers often face problems due to a perceived shortage of data sets that will fully meet the training needs of the system, will be relevant to different user requests of the systems and adapted to different situations. This highlights the need for centralized platforms offering high-quality data. As you know, the higher the quality of the data provided to the AI system for training, the better such a system will perform the specified functions.

Although the rules in the field of AI are still being formed, some of them have already been formed, but they are advisory in nature and regulate the ethical aspect in the application of such systems. Such documents at the international level should include documents submitted by the International Organization for Standardization.

The main standard in the field of artificial intelligence is the ISO/IEC 22989:2022 standard, dedicated to the concept and terminology of artificial intelligence. The terminology used in this document is used with reference in other standards. The definition of artificial intelligence is given here as a discipline for the research and development of mechanisms and applications of AI systems. We also note the ISO/IEC 42001:2023 standard, which establishes requirements for AI management systems used by organizations that develop and implement AI systems. This standard refers to the above, which is the basis for it, using the terminology fixed in it. In addition, various international organizations are also working in this area. For example, there is a guideline on data protection when using AI, adopted by the Council of Europe on January 25, 2019 ^[3].

In addition to the international level of regulation, it is worth noting the positive dynamics in the development of legal regulation of the use of AI at the national level. Existing laws regulate the collection, creation, labeling, and processing of AI training data in various legal systems. In the Russian Federation, Decree No. 490 of the President of the Russian Federation dated October 10, 2019 "On the development of artificial Intelligence in the Russian Federation", which lists the goals and objectives of the development of artificial intelligence in our country. However, in addition to regulating AI at the general level, which does not affect various aspects and spheres of life, there are various government programs in the relevant areas of the country's development. Regarding the agro-industrial complex, it should be noted the state federal scientific and technical program for the development of agriculture for 2017-2025, which consists in the introduction of various digital platforms aimed at effective administration, improvement of statistical analytics, creation of advanced production and implementation mechanisms for the functioning of the agro–industrial complex ^[7]. The goal of the project is the digital transformation of agriculture through the introduction of digital technologies and platform solutions to ensure a technological breakthrough in agriculture and achieve productivity growth. The project provides for the digitalization of not only business entities, but also the agro-industrial complex management system itself ^[8]. In Russia today, AI is mainly used in the following agricultural sectors: "smart" crop production, "smart" animal husbandry, precision agriculture, as well as intelligent production and logistics management systems (URL: https://ai.gov.ru/knowledgebase/vnedrenie-ii/2023_peredovye_intellektualynye_resheniya_v_selyskom_hozyaystve_csr_severo-zapad / (date of access: 03/14/2025)).

Despite the existing problems in the legal regulation of AI technologies, work is underway in this area. For example, the Russian Federation has approved a Code of Ethics in the field of artificial intelligence, which is advisory in nature. The text of this document contains guidelines and rules in relations related to the ethical aspects of creation, including design, construction, piloting, as well as the introduction and use of AI technologies. In addition, key draft laws have been adopted to promote the development of technologies and solutions in the field of AI. Among them are legislative initiatives aimed at using cloud infrastructure to create AI models – Federal Law No. 266–FZ of July 14, 2022 "On Amendments to the Federal Law "On Personal Data", Certain Legislative Acts of the Russian Federation and the invalidation of Part Fourteen of Article 30 of the Federal Law "On Banks and Banking activities". This law clarifies the rules for processing personal data, introduces operator responsibility for the actions of foreign persons charged with data processing, and operators are also required to notify the authorized body of their intention to carry out cross-border data transfer. Changes have been added to the register of operators, and this law has been expanded: the provisions of the law now apply to the processing of personal data of Russian citizens by foreign legal entities or individuals based on contracts or agreements with Russian citizens.

In addition to this document, there are also changes in the mechanism of public-private partnership in the field of information technology. Federal Law No. 604-FZ of December 29, 2022 "On Amendments to Certain Legislative Acts of the Russian Federation" is aimed at simplifying and clarifying procedures for concluding concession agreements, especially in the context of information technology facilities, including AI.

There is also regulation of the use of unmanned aerial vehicles: Decree of the Government of the Russian Federation dated March 24, 2022 No. 462 "On the establishment of an experimental legal regime in the field of digital innovation and Approval of the Program of an experimental legal regime in the field of digital innovation for the Operation of unmanned aircraft systems in the Kamchatka Territory, Khanty-Mansiysk Autonomous Okrug – Yugra, Chukotka Autonomous Okrug and Yamalo-Nenets Autonomous District".-Nenets Autonomous District" and Decree of the Government of the Russian Federation dated March 24, 2022 No. 458 "On the establishment of an experimental legal regime in the field of digital innovations and approval of the Program of an experimental legal regime in the field of digital innovations for the operation of unmanned aircraft systems in the Tomsk Region." In parallel, active work is underway on standardization in the field of AI: as of 2023, about 40 GOST standards related to the use of artificial intelligence have been adopted (URL: https://ict.moscow/news/2022-ai-regulation / (date of access: 03/14/2025)). Due to the novelty of AI technology, which is rapidly changing and expanding its fields of application, legal norms are needed that will stimulate the development of technologies experimentally and without unnecessary risks, without slowing down scientific progress, while protecting the rights of all participants in the process. In the Russian Federation, back in 2020, the concept of an experimental legal regime (hereinafter referred to as the EPR) in the field of digital innovation appeared in the legal system.
EPR implies the application over a certain period of time of special regulation in the areas of development, testing and implementation of digital innovations ^[9]. It is worth noting the existence of similar legal regimes in a number of countries where the introduction of artificial intelligence is at a high level. To date, 14 EPR systems have been installed in Russia in the field of AI, including in the field of agriculture – Decree of the Government of the Russian Federation dated 09/16/2023 No. 1510 "On the establishment of an experimental legal regime in the field of digital innovation and approval of the Program of an experimental legal regime in the field of digital innovation for the operation of agricultural unmanned aircraft systems" (URL: https://ai.gov.ru/ai/regulatory/ (date of access: 03/18/2025)). The objectives of establishing this regime are: to form new types, forms and methods of economic activity after the deadline for establishing the regime; to ensure the development of technologies; to create conditions for the development and implementation of new technologies; to improve products.

In conclusion, it can be noted that the current legal situation is characterized by the presence of many rules and standards related to the development, implementation and use of AI systems, both at the national and international levels. An analysis of the content of international acts aimed at regulating the field of artificial intelligence has shown that all of them are documents containing mainly general approaches, while they do not affect specific areas of application of such systems. For example, in 2017, the Resolution of the European Parliament with the recommendations of the Commission on Civil Law "Rules of Robotics" (2015/2103(INL)) reflected the general direction of the principles of the development of robotics and artificial intelligence for civil purposes. Later, in 2021, the UNESCO Recommendations on the Ethical Aspects of Artificial Intelligence were adopted, which contain recommendations on the ethical aspects of using AI. This document calls for responsible use of AI and emphasizes the importance of respect for human rights and fundamental freedoms. The creation of new legal mechanisms is largely due to the rapid development and active implementation of innovative technologies in agricultural production. If ten years ago the main object of legal regulation in the agro-industrial complex was land, today the situation has changed. This is due to the fact that modern technologies have significantly expanded the possibilities of using high-tech solutions in agriculture, which requires a more comprehensive approach to legal regulation. Also, the introduction of legal regimes regulating the use of innovative technologies should be taken into account. This experience is important for states, as it makes it possible to regulate innovations under controlled conditions without violating existing norms.

Currently, information in the agro-industrial complex (AIC) is fragmented: data on soils, weather, yields, plant diseases and economic indicators are stored in disparate systems, which makes it difficult to analyze them. The creation of universal platforms with centralized databases for AI will allow combining information from different sources, providing algorithms with reliable and up-to-date analytics. This will increase the accuracy of forecasts, optimize resource management, and accelerate the adoption of smart technologies such as precision farming, automated crop monitoring, and yield forecasting. In addition, a single platform will simplify the interaction between farmers, government agencies and scientific institutions, contributing to the development of digital agriculture.

Artificial intelligence has a huge potential for the transformation of the agro-industrial complex. However, to realize this potential, it is necessary to solve a number of legal, ethical and technical problems. The development of effective legal regulation, international cooperation and support for innovation will be key factors for the successful implementation of AI in agriculture.