The intelligent economy—defined by data, algorithms, and computing power as key production factors and by the deep integration of intelligent technologies throughout the entire production process—is reshaping production modes, capital circulation, and governance mechanisms, and has become an important driving force for China’s high-quality development. Against the backdrop of advancing the “Artificial Intelligence Plus” initiative, accelerating the development of new-quality productive forces, and the Fourth Plenary Session of the 20th CPC Central Committee emphasizing the direction of intelligent, green, and integrated development, examining the internal logic of the intelligent economy and its mechanisms for promoting high-quality development holds significant theoretical and practical value. Drawing on Marxist political economy, this paper analyzes the structural impacts of the intelligent economy from the perspectives of production modes, capital circulation, and institutional regulation. In terms of production logic, the intelligent economy reconstructs production organization through data-driven processes, human-machine collaboration, cross-boundary integration, and co-creation and sharing. Real-time data recording reduces time frictions among production, warehousing, logistics, and sales, enabling a shift from preset planning to dynamic adjustment. Human-machine collaboration transforms labor from experiential activities into knowledge-based and system-oriented work. Cross-boundary integration, supported by unified data and algorithmic systems, reorganizes industrial chains and gives rise to networked and coordinated production structures. Co-creation and sharing enhance the socialization of production and accelerate the diffusion of knowledge and innovation. In terms of capital logic, intelligent technologies compress production and circulation time, accelerating capital turnover and increasing the frequency of surplus value realization, thereby shifting economic growth from factor-driven to efficiency-driven. Algorithms enhance capital’s ability to identify profit signals, making cross-sectoral flows more responsive and strengthening the mechanism of profit-rate equalization. Intelligent manufacturing, digital supply chains, and industrial internet systems improve labor productivity, optimize cost structures, and extend the service life of fixed capital, expanding profit margins and promoting new patterns of capital allocation within the industrial system, thus advancing industrial upgrading toward higher technological levels and greater value added. In terms of institutional logic, the intelligent economy is characterized by high investment intensity, long cycles, and strong interdependence, requiring patient capital and institutional regulation to support long-term innovation. Short-term profit-seeking capital tends to induce overinvestment and technological bubbles, whereas patient capital aligns capital recovery cycles with technological innovation cycles, ensuring stability. Meanwhile, the intelligent economy amplifies risks such as data monopolies, algorithmic bias, and systemic vulnerabilities, necessitating governance norms, risk classification, and long-term evaluation mechanisms to maintain coherence between innovation rhythms and the rhythm of social reproduction, thereby preventing financialization from undermining the real-economy foundation. Based on these analyses—and in alignment with the strategic arrangements, factor system reforms, and science-and-technology innovation directives set out in the Fourth Plenary Session of the 20th CPC Central Committee and the 15th Five-Year Plan Proposals—this paper recommends constructing a policy framework for the intelligent economy across four dimensions: strategic coordination, innovation system development, factor optimization, and institutional safeguards. Such a framework will facilitate the integration of the intelligent economy into the value-creation process and generate a synergistic force for advancing high-quality development.