引入智能体需要这些基础，企业准备好了么

Core Insights - The application of artificial intelligence (AI) in recruitment, interviews, and human resource management is rapidly increasing, with studies showing that AI outperforms humans in interview settings, significantly enhancing candidates' chances of being hired, onboarding, and retention [1][2] - Companies face the challenge of integrating AI deeply into organizational management processes rather than merely using it as a tool [1] Group 1: AI in Human Resources - eRoad is one of the early adopters of AI technology in the human resources sector, providing solutions to over 800 medium and large enterprises across more than 20 countries and 310 cities in China [2] - In 2023, eRoad transitioned from early AI applications based on natural language processing (NLP) to utilizing large language models (LLM) for developing its intelligent product offerings [2] - The launch of the iBuilder platform in 2024, which includes 39 intelligent agents covering various HR functions, marks a significant advancement in eRoad's AI capabilities [2][3] Group 2: Addressing Recruitment Challenges - eRoad's AI solutions address key recruitment challenges, such as determining appropriate salary levels and ensuring candidate suitability, which have become increasingly complex in a fluctuating economic environment [3][4] - The company aims to provide objective talent assessments to assist second-generation family business leaders in making informed personnel decisions, overcoming biases in traditional evaluations [3][4] Group 3: AI's Role in Talent Assessment - AI constructs objective talent profiles by analyzing historical data, which helps eliminate subjective biases in candidate evaluations [4][5] - The technology enhances job matching accuracy by considering both job descriptions and performance behaviors of past successful employees, rather than relying solely on job titles [5][6] - AI links job matching with compensation strategies, analyzing market data and internal performance metrics to determine appropriate salary ranges for specific talent profiles [6] Group 4: Intelligent Agents in Decision-Making - Intelligent agents are increasingly used in business decision-making, categorized into those handling standard tasks and those managing non-standard tasks [7][8] - These agents can significantly improve efficiency and reduce costs in standard operations, while also enhancing human decision-making capabilities in more complex scenarios [7][8] Group 5: Foundations for Trust in AI - Successful AI integration in enterprises relies on three foundational pillars: validated management theories, high-quality data integration, and empowering AI interactions [11][12] - Predictability, traceability, and auditability are essential for establishing trust in AI systems, ensuring that decisions are based on clear standards and can withstand scrutiny [15][16] Group 6: Stages of Trust Development - The development of trust in AI occurs in three stages: full delegation for deterministic tasks, advisory roles for complex decisions, and collaborative exploration for strategic innovations [17][18] - This progression highlights the importance of AI as a strategic partner in business operations, moving beyond mere automation to become a reliable decision-making ally [18]