安永大中华区人工智能与数据咨询服务联席主管合伙人陈剑光：衡量AI Agent“好用”的关键指标，需兼顾技术效能与业务价值

Core Insights - The rapid development and deployment of AI Agents is being driven by major tech companies, with OpenAI and Ernst & Young launching their respective products [1] - The effectiveness of AI Agents is measured by both technical performance and business value, focusing on accuracy, response speed, efficiency improvement, cost optimization, and risk control [1][8] Industry Demand and Application - There is a significant variation in the demand for AI Agents across different industries, with common needs in personnel and administrative functions aimed at enhancing operational efficiency [2][3] - Specific industry applications include: - Financial sector: Risk control and compliance management, with agents for investment portfolio analysis and real-time trading monitoring [5][6] - Retail sector: Supply chain optimization, inventory management, and personalized marketing through consumer behavior analysis [5][6] - Manufacturing sector: Equipment maintenance, production process optimization, and quality control through predictive maintenance and quality inspection agents [6][7] Challenges in Implementation - Companies face two main challenges when deploying AI Agents: system integration barriers and insufficient vertical domain adaptation [4] - Integration issues arise from incompatible data formats and interface protocols, leading to operational inefficiencies [4][5] - The lack of specialized knowledge and high-quality structured data for training agents in specific industries presents a significant barrier [5] Measuring Effectiveness - The effectiveness of AI Agents should be evaluated through both technical efficiency metrics (accuracy, robustness, response time) and business value indicators (efficiency gains, cost savings, risk reduction, quality improvement) [8] - For companies new to AI Agents, starting with low-cost, easily implementable scenarios is recommended to gradually realize value [9] Strategic Recommendations for SMEs - Small and medium enterprises (SMEs) are advised to adopt a "small steps, quick wins" approach, beginning with lightweight scenarios that have clear demands and can quickly demonstrate value [9] - Utilizing external service APIs or SaaS products can help SMEs quickly expand AI Agent functionalities while minimizing initial costs [9] - The core value of AI Agents lies not in replacing human labor but in enhancing human capabilities and organizational efficiency through collaboration [9]