This study aimed to show the impact of intelligent automation on the satisfaction of service recipients in the Jordanian Social Security General Organization. It was conducted in the Capital Governorate - Amman, and the time limit is 2024. The study population consisted of social security employees and service recipients, as the questionnaires were distributed to two categories: The first includes social security employees. In contrast, the second category consists of social security service recipients. The Information Systems Department has 29 employees, the Information Technology Department has 30 employees, and the Operations Department has 11 employees. In total, there are 70 employees across these departments. Their administration is centralized at the General Administration of the Social Security Corporation in Amman, excluding the branches. To achieve the objectives of the study, the quantitative approach (analytical description) is used through several statistical methods. In the second category, which pertains to the recipients of social security services, a total of 1,574,291 individuals are participants in the Jordanian social security system. To conduct the study, a random sample of 403 participants and an additional 40 employees were selected. A quantitative approach (analytical description) involving several statistical methods was employed to achieve the study's objectives. The study produced several key findings, particularly highlighting a statistically significant level of intelligent automation, which encompasses its various dimensions: robotic process automation, business process management, and data-driven decision-making. Additionally, there was a statistically significant level of service recipient satisfaction, measured through its combined dimensions of perceived value, reliability/credibility, and responsiveness. These results provide valuable insights into the relationship between intelligent automation and recipient satisfaction. The study emphasized the importance of addressing the issues beneficiaries face with services. It recommended that the organization respond promptly to inquiries and requests from beneficiaries. Additionally, it suggested that beneficiaries' feedback be considered when developing services. The study called for training on using data in decision-making and conducting periodic assessments to measure beneficiaries' satisfaction with the services provided by the General Organization for Social Security. Furthermore, it is proposed to broaden the scope of future research to encompass more service areas. The study aims to expand its scope to include communications, artificial intelligence, and enterprise resource planning. It will also involve conducting periodic user surveys, enhancing technical support channels, and generalizing the experiences of intelligent automation in social security in Jordan to other state institutions. Keywords: Intelligent automation, robotic process automation, business process management, data-driven decision making, beneficiary satisfaction, perceived value, reliability, credibility, responsiveness, social security corporation.