Core Viewpoint - The integration of AI in the financial sector is transforming traditional business models, with a focus on a "pay-for-performance" approach that aligns AI applications with actual business outcomes [7][8][9]. Group 1: AI in Financial Services - AI is becoming a crucial tool for enhancing core competitiveness and reshaping service systems in the financial industry [7]. - The "pay-for-performance" model allows clients to pay based on the actual results achieved through AI applications, rather than traditional project-based or subscription models [8][9]. - Ant Group's AI capabilities are shifting from a tool delivery model to a business outcome-oriented approach, emphasizing collaboration with financial institutions to achieve measurable results [9]. Group 2: Market Demand and Client Needs - There is a significant demand from small and medium-sized financial institutions for solutions that address business growth and asset quality improvement [9]. - Many financial institutions are eager to explore AI applications, with regional banks making up two-thirds of Ant Group's current partnerships [9]. - The primary needs of financial institutions include solving business growth challenges, ensuring business security, and enhancing user experience [10]. Group 3: Data and AI Integration - The construction of a trusted data space is increasingly intertwined with AI applications, providing essential data governance and support for AI model training [10][11]. - The integration of AI and trusted data spaces is accelerating, with both areas overlapping in infrastructure development, such as computing centers and data platforms [11]. - High-quality, standardized data is critical for AI development, and trusted data spaces are key to ensuring data governance and reliability [11].

Core Viewpoint - The advent of AI is transforming the SaaS industry, particularly in financial management, with a shift towards performance-based payment models [1][2] Company Overview - HeSi was founded in 2014 and specializes in financial digitalization, having raised over 1.5 billion yuan in funding from notable investors [1] - The company has over 7,000 paying enterprise clients and has been deeply involved in the financial SaaS sector for over a decade [1] AI Impact on SaaS - AI is revolutionizing product capabilities and altering business models, moving from subscription-based to performance-based payment structures [1][2] - AI solutions can enhance efficiency and reduce costs by automating tasks such as expense approvals and document submissions [2] Challenges in AI Implementation - Many enterprises struggle with AI deployment due to issues like lack of contextual learning, rigid workflows, and detachment from daily operations [3][4] - A report indicates that 95% of companies have not seen measurable financial returns from their AI investments [3] Strategies for Effective AI Integration - Companies should focus on tasks that AI excels at and introduce AI in scalable scenarios, particularly in areas like expense management [4] - Establishing a sustainable Agent platform and fostering an AI-friendly organization are crucial for successful AI integration [4][5] Evolution of Expense Management - The financial management function is evolving from mere record-keeping to resource allocation and risk management, with expense management becoming a key area for cost reduction and efficiency [6] - Traditional expense management has been characterized by inefficiencies, leading to a disconnect between finance and business operations [6] AI Solutions Offered - HeSi's AI solutions include various agents designed to streamline processes, significantly improving approval times and reducing error rates [7] - For instance, the implementation of AI in a restaurant chain led to a 75% improvement in approval efficiency and a 62.5% reduction in labor costs [7] Concerns About AI Replacing Jobs - There are concerns regarding AI replacing human jobs; however, the view is that AI will take over low-value tasks, allowing finance professionals to focus on higher-value work [8]

Group 1 - Ant Group's new "pay-for-performance" business model allows enterprise clients to pay based on the actual results achieved from AI applications, such as business growth or cost savings, rather than traditional project-based or subscription models [1][3] - The shift from technology payment to performance payment reflects the evolving role of AI as a business outcome accelerator, emphasizing the importance of measurable results for enterprise-level AI services [1][3] - Ant Group has already established partnerships with strategic clients based on key business outcomes and plans to promote this model across various industries [1][3] Group 2 - The "pay-for-performance" model addresses major challenges in scaling AI applications, such as high upfront costs, uncertain returns, and lack of implementation pathways, thereby lowering barriers and risks for enterprises [3] - Ant Group's comprehensive enterprise-level AI service framework enables businesses to access AI capabilities without significant infrastructure investments, particularly benefiting small and medium-sized enterprises [3] - The "ACE" methodology (Align-Construct-Evaluate) developed by Ant Group involves three steps: identifying valuable business goals with clients, constructing tailored solutions and implementation paths, and ensuring business outcomes through continuous joint operations [3]