Generative AI Workflow Risk

This white paper examines how generative AI use in workplace workflows can lead to destructive system actions, defective professional work, and unauthorized disclosure of restricted information. Its central assessment is that approving an AI tool or assigning a human reviewer does not establish control of the complete workflow. Drawing on Replit, Mata v. Avianca, and Deloitte, with Samsung included as a qualified reported incident, the paper traces how task definition, permissions, information handling, and human–AI interaction turn actions and outputs into business consequences. It distinguishes documented incidents from experimental research, technical evidence, and proposed safeguards. The analysis provides recommendations for validating objectives, restricting access and transmission, testing human review, and evaluating final outcomes. It identifies conditions supporting workflow expansion, restriction, or suspension. Written for security, governance, risk, operations, and professional-services leaders, the paper includes Chicago-style endnotes and a bibliography.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-16
DOI
https://doi.org/10.5281/zenodo.23421606
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Generative AI Workflow Risk

Jessica S. Marosi
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Generative AI Workflow Risk

Jessica S. Marosi
article en

Abstract

This white paper examines how generative AI use in workplace workflows can lead to destructive system actions, defective professional work, and unauthorized disclosure of restricted information. Its central assessment is that approving an AI tool or assigning a human reviewer does not establish control of the complete workflow. Drawing on Replit, Mata v. Avianca, and Deloitte, with Samsung included as a qualified reported incident, the paper traces how task definition, permissions, information handling, and human–AI interaction turn actions and outputs into business consequences. It distinguishes documented incidents from experimental research, technical evidence, and proposed safeguards. The analysis provides recommendations for validating objectives, restricting access and transmission, testing human review, and evaluating final outcomes. It identifies conditions supporting workflow expansion, restriction, or suspension. Written for security, governance, risk, operations, and professional-services leaders, the paper includes Chicago-style endnotes and a bibliography.

Zenodo (CERN European Organization for Nuclear Research)
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Ethics and Social Impacts of AI
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