Core Viewpoint - The compensation system is deeply linked to talent recruitment and retention, employee motivation and development, organizational stability, and cost control, making it a crucial tool for executing corporate strategy. The management of compensation is undergoing profound changes in the era of artificial intelligence (AI) [2][24]. Group 1: AI in Compensation Management - By 2025, AI applications in compensation management will focus on three main areas: compensation communication and transparency, external compensation benchmarking, and job and skill architecture. Currently, 22% of organizations apply AI in the first two areas, while 21% use it for job skill architecture [2][24]. - Despite the low current application rates (9%-22%), a significant majority of organizations (66%) are considering AI for predictive analytics, fairness and consistency (15% already using, 62% considering), and performance-related compensation (14% already using, 57% considering) [2][24]. - The future of AI-driven compensation management is expected to evolve beyond backend management to become an intelligent hub connecting human resource management, organizational strategy, and business development [2]. Group 2: Data and Analysis in Compensation - In the information age, compensation systems primarily rely on employee databases and payroll, which are foundational to Human Resource Information Systems (HRIS). Early systems had limited data processing capabilities, focusing on basic variables like job title and total compensation [4]. - The emergence of the internet and mobile technology has increased the volume of compensation-related data and allowed for integration with other management modules, enhancing transparency and responsiveness in compensation management [4][5]. - AI enables the evolution of traditional compensation analysis into a "data + intelligence" model, allowing for dynamic, real-time data integration and predictive capabilities regarding employee turnover and compensation effectiveness [5][6]. Group 3: Challenges in AI Implementation - Key challenges in applying AI to organizational compensation management include data privacy and security (69% of respondents), internal data and system integration (54%), and cost/resource limitations (42%) [6]. - The quality of data is critical, as incomplete or biased data can lead to inaccurate algorithm outputs, potentially exacerbating compensation inequities [6]. Group 4: Differentiated Compensation Structures - A well-structured compensation system is essential for linking employee motivation, talent management, and organizational operations. It helps define job responsibilities and aligns pay with job value and individual contributions [8][9]. - Differentiated compensation structures serve as both a talent strategy tool and an implicit screening mechanism, aiding organizations in identifying and retaining the most suitable talent [8][9]. - AI presents new opportunities for enhancing differentiated compensation by accurately assessing job value and dynamically updating compensation standards in line with external market conditions [10][11]. Group 5: Fairness in Compensation - Achieving a balance between incentive effectiveness and fairness perception is crucial for organizations, as fairness impacts both internal job matching and external market competitiveness [13][14]. - Many organizations are increasingly using algorithmic tools for compensation benchmarking, but there is a risk of overemphasizing external fairness at the expense of internal equity [14][15]. - The lack of high-quality performance or skill assessment systems in many organizations complicates the accurate measurement of job value, affecting internal compensation fairness [16]. Group 6: Communication in Compensation Management - Effective compensation communication enhances employee satisfaction and motivation, yet it is often seen as a weak link in compensation management [19][20]. - Digital tools can improve the transparency of compensation structures and assist managers in effectively communicating compensation policies to employees [19][20]. - Organizations must foster a culture of fairness and transparency to enhance the effectiveness of compensation communication [21][22]. Group 7: Future of Compensation Management - Compensation management will continue to evolve while remaining aligned with business strategy, organizational culture, and compliance requirements. Organizations need to clarify compensation standards through job evaluations and market benchmarking [23][24]. - The demand for high-level compensation experts with strategic vision and data analysis skills will increase, as they will be essential for developing compensation plans that align with corporate strategy and culture [24].