THE CONSTRUCTION OF PERFORMANCE MEASUREMENT SYSTEM FOR CENTRAL SOES' "AI+" INITIATIVES: A BALANCED SCORECARD PERSPECTIVE
Keywords:
Balanced Scorecard, "AI+" initiative, Artificial intelligence, Performance evaluationAbstract
In 2024, the State-owned Assets Supervision and Administration Commission (SASAC) of the State Council launched the "AI+" special action for central SOEs (state-owned enterprises), aiming to help them achieve better development and play a greater role in artificial intelligence. How to evaluate the performance of these initiatives scientifically has become an urgent issue for both theory and practice. Conventional performance evaluation systems, which rely primarily on financial indicators, may fail to capture the long-term value, intangible contributions, and national strategic significance of AI technologies. Drawing on Balanced Scorecard (BSC) theory and incorporating the three missions of central SOEs, namely sci-tech innovation, industrial control and security support, this study constructs a multidimensional performance evaluation indicator system for the "AI+" initiatives of central SOEs. "AI+"-specific indicators covering data assets, model efficacy, value creation, and other aspects are designed across the Financial, Customer, Internal Process, and Learning and Growth perspectives. The indicator system is then applied to a case study of CRRC Corporation Limited (CRRC), using publicly available data from its 2025 annual report and sustainability report, and an "AI+" strategy map is developed. The findings suggest that an adaptively modified BSC can effectively overcome the limitations of conventional financial indicators in evaluating AI outcomes, providing a scientific basis for SASAC's assessment and supervision and for the optimization of management in central SOEs.References
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