Open-access preprint published on 2026-03-09 and mirrored with DOI-backed identifiers.
Research
Agile Artificial Intelligence Governance: A Practical Approach to Responsible Corporate Adoption
Focused on enterprise AI governance, LLM controls, adaptive monitoring and operational assurance.
Creative Commons Attribution 4.0 International for broad redistribution with credit.
Author profile linked through ORCID and cross-posted across Zenodo, ResearchHub and SSRN.
Abstract
This paper proposes an agile governance framework for artificial intelligence systems in corporate environments. The research explores operational governance layers, risk monitoring mechanisms, and adaptive controls designed for large language model deployments. The framework integrates technical safeguards, organizational policy structures, and continuous monitoring to enable responsible and secure AI adoption in enterprise settings.
Research focus
What this work covers
Defines how governance moves from policy statements into runtime controls, evidence and review loops.
Frames monitoring as an active layer for safety, misuse, privacy exposure and drift in production.
Combines technical controls with policy structures so governance can evolve with new AI capabilities.
Keywords
Research domains
Publication footprint
Records and identifiers
Citations
How to cite
Venegas, G. A. (2026). Agile Artificial Intelligence Governance: A Practical Approach to Responsible Corporate Adoption. Zenodo. https://doi.org/10.5281/zenodo.18918455
@misc{venegas2026agile,
title = {Agile Artificial Intelligence Governance: A Practical Approach to Responsible Corporate Adoption},
author = {Venegas, Gustavo Adolfo},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.18918455},
url = {https://doi.org/10.5281/zenodo.18918455}
}