AI改造最难啃的行业，万亿基建求解“效率”与“可信”

Core Insights - The global infrastructure industry is at a transformative crossroads, with projected construction spending reaching $10 trillion by 2025, yet productivity has seen little improvement over decades. AI is viewed as a key opportunity to bridge the supply-demand gap in infrastructure [1][4] - AI is increasingly integrated into various stages of infrastructure projects, enhancing efficiency and decision-making, but its adoption faces significant challenges due to the industry's complexity and high stakes [1][8] Group 1: AI Integration and Impact - Approximately half of the respondents in a global survey have piloted or implemented AI in infrastructure, with one-third predicting AI will be applied to over half of their design and engineering projects within three years [4] - AI has demonstrated substantial efficiency improvements, with examples including a Chinese engineering company achieving over 60% operational efficiency in substations and a Turkish project reducing development time from five years to one year while cutting costs by over 75% [4][9] - Bentley's AI strategy emphasizes "trustworthy AI," focusing on specialized intelligence rooted in infrastructure scenarios, utilizing real project data and geographic information [7][8] Group 2: Challenges in AI Adoption - Data silos present a significant challenge, as infrastructure projects involve multiple phases and data formats, necessitating a unified data foundation to facilitate seamless data flow [8][9] - The rigorous engineering logic must be embedded in AI to ensure compliance with safety and construction standards, as any deviation could lead to unsafe outcomes [8][9] - The complexity of adapting AI to various geographical and climatic conditions poses a third challenge, requiring tailored solutions for different project environments [9][10] Group 3: Future Directions - Bentley's "Infrastructure AI Co-Creation Program" aims to involve users in the design of AI workflows, enhancing software optimization through user feedback [10] - The vision for AI in the infrastructure sector is not to replace engineers but to empower them, fostering a collaborative human-machine process [11]