未来研究
战略规划
知识管理
过程管理
利益相关者
过程(计算)
计算机科学
政府(语言学)
生成语法
自动化
管理科学
战略情报
战略联盟
公共部门
方案规划
人工智能
工程类
期货合约
情景分析
灵活性(工程)
生成模型
业务
有可能
作者
Marc E. B. Picavet,Peter Maroni,Alexander T. Sandhu,Kevin C. Desouza
摘要
ABSTRACT Generating strategic foresight for public organizations is a resource‐intensive and non‐trivial effort. Strategic foresight is especially important for governments, which are increasingly confronted by complex and unpredictable challenges and wicked problems. With advances in machine learning, information systems can be integrated more creatively into the strategic foresight process. We report on an innovative pilot project conducted by an Australian state government that leveraged generative artificial intelligence (AI), specifically large language models, for strategic foresight using a design science approach. The project demonstrated AI's potential to enhance scenario generation for strategic foresight, improve data processing efficiency, and support human decision‐making. However, the study also found that it is essential to balance AI automation with human expertise for validation and oversight. These findings highlight the importance of iterative design to develop robust AI tools for strategic foresight which, alongside stakeholder engagement and process transparency, build trust and ensure practical relevance.
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