Purpose

The current gap between the required and available artificial intelligence (AI) professionals poses significant challenges for organisations and academia. Organisations are challenged to identify and secure the appropriate AI competencies. Simultaneously, academia is challenged to design, offer and quickly scale academic programmes in line with industry needs and train new generations of AI professionals. Therefore, identifying and structuring AI competencies is necessary to effectively overcome the AI competence shortage.

Design/methodology/approach

A probabilistic topic model was applied to explore the AI competence categories empirically. The authors analysed 1159 AI-related online job ads published on LinkedIn.

Findings

The authors identified five predominant competence categories: (1) Data Science, (2) AI Software Development, (3) AI Product Development and Management, (4) AI Client Servicing, and (5) AI Research. These five competence categories were summarised under the developed AI competence framework.

Originality/value

The AI competence framework contributes to clarifying and structuring the diverse AI landscape. These findings have the potential to aid various stakeholders involved in the process of training, recruiting and selecting AI professionals. They may guide organisations in constructing a complementary portfolio of AI competencies by helping users match the right competence requirements with an organisation's needs and business objectives. Similarly, they can support academia in designing academic programmes aligned with industry needs. Furthermore, while focusing on AI, this study contributes to the research stream of information technology (IT) competencies.

中文翻译：

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使用概率主题建模为人工智能专业人员开发能力框架

目的

目前所需和可用的人工智能 (AI) 专业人员之间的差距给组织和学术界带来了重大挑战。组织面临着识别和确保适当的人工智能能力的挑战。同时，学术界面临着根据行业需求设计、提供和快速扩展学术课程以及培训新一代 AI 专业人员的挑战。因此，识别和构建人工智能能力是有效克服人工智能能力短缺的必要条件。

设计/方法/途径

应用概率主题模型从经验上探索 AI 能力类别。作者分析了 LinkedIn 上发布的 1159 个与 AI 相关的在线招聘广告。

发现

作者确定了五个主要的能力类别：(1) 数据科学，(2) AI 软件开发，(3) AI 产品开发和管理，(4) AI 客户服务，以及 (5) AI 研究。在开发的人工智能能力框架下总结了这五个能力类别。

原创性/价值

AI 能力框架有助于阐明和构建多样化的 AI 景观。这些发现有可能帮助参与培训、招聘和选择 AI 专业人员的各种利益相关者。它们可以通过帮助用户将正确的能力要求与组织的需求和业务目标相匹配，来指导组织构建互补的 AI 能力组合。同样，他们可以支持学术界设计符合行业需求的学术项目。此外，在关注 AI 的同时，本研究有助于信息技术 (IT) 能力的研究流。