Expanding the organizational design space: the emergence of AI robot bosses

Author:

Burton Richard M.,Obel BørgeORCID,Håkonsson Dorthe DøjbakORCID

Abstract

AbstractAI robot bosses are becoming increasingly prevalent in organizations, and they expand the traditional organizational design space. Organizations can benefit from utilizing both robots and humans as bosses, as they can substitute for each other and work together as complements across different organizational structures. This expanded design space includes different kinds of AI robots and humans as bosses, rather than limiting robots to just being helpers. By considering the different capabilities and relationships of humans and robots, we argue that the organizational design space is expanded to achieve greater effectiveness and efficiency. However, the effectiveness of a robot boss depends on the organizational situation. Robots excel at managing organizational rules and processing large data sets for certain environments. AI robots also excel at predicting future patterns based on large sets of data, while humans are better suited for uncertain situations requiring judgement and creativity. We develop four types of AI robot bosses based on: explainability or how easy it is to understand and explain the decisions made, and supervised learning or how the robots learn and are trained over time in usage. These four types are then matched with leadership styles and organization forms. Organizational charts, or hierarchy charts, visually depict an organization’s structure, showcasing reporting relationships and chains of command. Employees’ names, titles, and job positions are typically represented in boxes or circles connected by lines, indicating their affiliations. However, traditional organization charts lack icons or representations of Artificial intelligent or AI robot bosses. This discrepancy prompts the question not of their inclusion, but of why they are omitted.

Funder

Royal Danish Library, Aarhus University Library

Publisher

Springer Science and Business Media LLC

Subject

Strategy and Management

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3