Work

AI-Mediated Apprenticeship: Rethinking Follower Development in Servant Leadership Under GenAI Delegation

Year: 2026

Type: article

Abstract: Generative AI can now perform routine and first-pass knowledge work that has also helped less-experienced employees develop. This creates a leadership problem for servant leadership, which treats follower growth as a constitutive priority. This article introduces developmental work access (DWA): the breadth and continuity of meaningful participation in development-bearing work across the part of a follower’s portfolio that a focal leader can materially allocate. It distinguishes general AI use from efficiency-first managerial AI delegation (EFAID). In EFAID, speed, cost, throughput, or reduced managerial burden guide delegation, while follower development is absent from the material allocation decision. Four propositions link servant leadership, EFAID, DWA, leader-designed AI-mediated apprenticeship (AMA), and role-relevant capability development. AMA comprises verified review, specification authorship, and reflective human–AI comparison. It is a design-side moderator; DWA records realised participation. This article also specifies how to measure eligible work, participation, breadth, continuity, portfolio compensation, and construct denominators. The model neither assumes that AI causes deskilling nor that AMA works in every setting. It identifies when manager-authorised delegation may restrict developmental participation and how leaders may reconstruct it while protecting genuine human execution.

Source: Administrative Sciences

DOI: 10.3390/admsci16100505

Author: Ozgur Ertem

Institution: Amsterdam University of Applied Sciences

Language: English

Topic: Corporate Management and Leadership

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Decent work and economic growth

Open Access status: gold

Estimated APC paid: $1,689