Under the background of the national strategy of the integration of artificial intelligence and real economy, financial digital-intelligent transformation has become imminent for traditional manufacturing enterprises. By conducting a case study of Sichuan Changhong, this paper investigates how the "Artificial Intelligence+" (AI+) strategy shapes the mechanisms and pathways underlying financial digital intelligence transformation in manufacturing companies. Empirical evidence from the case reveals that enterprise-wide digital and intelligent transformation is fundamentally propelled by financial digital intelligence. The evolution of "AI + finance" unfolds progressively, shifting from operational process automation to intelligent decision-making, which can only be achieved through integrated alignment among technology, organizational structure, and corporate strategy. Changhong has embedded AI into the core scenario of expense reimbursement, and achieved cost reduction and efficiency increase through intelligent order creation, approval and data analysis. The financial function has shifted from accounting to strategic, and the period expense ratio has decreased, and ROE and other profit indicators have steadily improved. This study explores the feasible path of "AI + finance" for traditional large enterprises, provides practical reference for the transformation of similar enterprises, and enriches the case studies in related fields.

Under the background of the development of digital intelligence economy and the country's promotion of digital intelligence upgrading of traditional industries, the logistics industry is facing the efficiency bottleneck of the traditional model, and it is urgent to respond to changes in market demand and industry competition through digital intelligence transformation. This article takes Shun Feng Express (SF) as a case, and uses the case study method to explore its digital intelligence transformation path and its impact on enterprise performance. The study found that SF Express has solved the pain points of the industry such as decision-making lag through the transformation of integration, digital intelligence, informatization and intelligent globalization, and achieved a double improvement in financial and customer-level performance: revenue and net profit grew steadily, new business expansion achieved remarkable results, customer satisfaction continued to lead, and the cooperation penetration rate of head enterprises was high. The core of its transformation lies in the upgrading of technical roles, in-depth coordination of software and hardware, and the development model of technology reinvigorating enterprises. This research enriches the theoretical cases of the digital and intelligent transformation of the logistics industry, provides practical reference for the transformation of logistics enterprises, and also provides reference ideas for the digital and intelligent upgrading of traditional industries.