The agricultural sector plays a vital role in Azerbaijan’s economic development and social welfare. Although the country has restructured its agricultural subsidy and insurance systems since 2020, their effectiveness remains limited. This paper proposes the adoption of automated insurance models and dynamic subsidy mechanisms, drawing on best practices from the United States and Australia. The primary objectives are to mitigate risks, enhance productivity, and improve the transparency of state support systems. Traditional insurance models, often influenced by subjective decision-making, contribute to delays in compensation payments and hinder the sector’s overall development. In contrast, automated systems based on objective, real-time data offer greater efficiency and reliability. Additionally, dynamically adjusting subsidies in response to changing environmental conditions-such as increased rainfall leading to higher pesticide costs-ensures a more responsive and equitable allocation of support. The integration of smart technologies, including sensors and artificial intelligence (AI), is instrumental in risk assessment and the fair distribution of subsidies. Real-time data collection enhances transparency and facilitates more objective policy decisions. These technological approaches can significantly contribute to increasing efficiency and promoting the sustainable development of the agricultural sector.