Submitted:
28 October 2026
Posted:
28 October 2026
You are already at the latest version
Abstract
As AI-enabled workplace monitoring expands, organizations may increasingly have the technical capacity to classify prosocial conduct, assign scores, and link those scores to managerial incentives. This paper treats the governance implications as an AI-enabled management control and accounting governance question, not an engineering scoring study; reward crowding-out is borrowed evidence, not a new finding here. It makes two contributions. First, it explains how accounting measurement, target setting, budgeting, disclosure, and compensation design turn a fleeting motivational reaction into a durable arrangement reproduced across reporting periods. Second, it analyzes the asymmetry between auditable behavioral indicators and moral costs that resist measurement, and why those costs stay out of ordinary records. A four-arm governance design—management control, financial reporting, internal audit, compensation—extends these contributions in practice. Three layers and four falsifiable propositions follow, offered for later testing, not validated causal claims.
Keywords:
management control
; accounting governance
; internal audit
; compensation governance
; algorithmic management
; moral-cost information asymmetry
; workplace spirituality
; AI-enabled control
; testable propositions
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.