发表机构
City St George’s, University of London（伦敦城市圣乔治大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出中小型成熟企业应摒弃AI炒作，以低影响、模块化动态跨职能的知识图谱技术为核心重构数据基础，这是其迈向数据成熟度的最具颠覆性举措。
AI 中文摘要
中小型成熟企业要充分利用AI领域的最新技术进展，最具颠覆性的举措是摒弃炒作，专注于建立或重构良好的知识基础层。向高管团队传达这一信息颇具难度，因此该举措需有证据支撑，且实施过程需尽可能减少对现有流程的影响。在本愿景声明中，我们探讨需如何重新思考向决策者传递何种证据，并提出一种低影响的数据策略，该策略可适配公司内现有且不断变化的数据流与流程。我们坚信，只要以模块化、动态化及跨职能的方式设计知识图谱技术，其将日益成为AI驱动型企业数据策略中不可或缺的组成部分。
英文摘要
The most disruptive step that enterprises of small-medium size and maturity can take to make the most of the latest technological advances in AI is to step back from the hype and focus on establishing or reviving a good knowledge foundation layer. It is a hard message to present to the executive team; therefore, it needs to be backed by evidence, and its implementation needs to be of minimal impact on the existing processes. In this vision statement, we discuss how we need to rethink what evidence speaks to the decision-makers and propose a low-impact data strategy that adapts to the existing and ever-changing data flows and processes across the company. We firmly believe that knowledge graph techniques will increasingly become non-negotiable in the data strategy of an AI-powered enterprise, provided that we approach their design in a modular, dynamic and cross-functional way.
Comments6 pages
