Purpose

To report on a study that focused on the records and information management (RIM) profession’s competencies with respect to the development of AI.

Design/methodology/approach

Designed as deductive, the study distilled artificial intelligence (AI) insusceptibility indicators, creative intelligence and social intelligence, from the Oxford study and applied them to the current RIM core competencies developed by ARMA International. Manual coding and semantic analysis served as the primary inquiring methods, and both statistical and qualitative results are presented.

Findings

The RIM profession as a whole is currently AI-resistant, yet it is not AI-proof. To be AI-proof, the existent competencies model needs to be redesigned as the AI-resistant parts are mingled with AI-prone ones, and the prescriptions of some RIM theories and principles are not ready for AI judgements or adjustments. It requires also strategizing collaborations among all stakeholders so that we can be one step ahead of future unfavorable organizational decisions. If our professional nature renders us AI-resistant for now, then it is our professional unity that will ensure us AI-proof in the future.

Originality/value

To the best of the authors’ knowledge, this paper is first of its kind within the international RIM community. It provides detailed assessment data on AI insusceptibility and targeted suggestions regarding the RIM community as a whole.

中文翻译：

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与人工智能竞争——记录和信息管理行业能否经受住挑战？

目的

报告一项研究，重点关注记录和信息管理 (RIM) 专业在人工智能发展方面的能力。

设计/方法/方法

该研究采用演绎设计，从牛津大学的研究中提炼出人工智能 (AI) 敏感性指标、创造性智能和社会智能，并将其应用于 ARMA International 开发的当前 RIM 核心竞争力。人工编码和语义分析是主要的查询方法，并给出了统计和定性结果。

发现

RIM 行业作为一个整体目前是抗 AI 的，但它不是抗 AI 的。要抗AI，需要重新设计现有的胜任力模型，因为抗AI的部分与易AI的部分混杂在一起，一些RIM理论和原理的处方还没有为AI判断或调整做好准备。它还需要制定所有利益相关者之间的合作战略，以便我们能够在未来不利的组织决策之前领先一步。如果说我们的专业本性让我们暂时能够抵抗人工智能，那么我们的专业团结将确保我们未来能够抵抗人工智能。

原创性/价值

据作者所知，这篇论文在国际 RIM 社区中尚属首创。它提供了关于人工智能不敏感的详细评估数据和关于整个 RIM 社区的有针对性的建议。