Abstract: Generative artificial intelligence (AI) is rapidly transforming corporate digital communications, enabling faster creation of emails, intranet posts, and social‑media content. However, the deployment of large language models (LLMs) on public clouds introduces data‑sensitivity, regulatory, and brand‑consistency risks. In this paper we present Secure Agentic Content‑Governance (SAC‑G), a multi‑agent framework that integrates locally hosted LLMs (Llama 3.1 and Qwen 2.5), a policy‑driven rule engine, and end‑to‑end encryption to provide a fully auditable, privacy‑preserving workflow for enterprise content production.
A three‑month pilot (June – August 2026) in the Corporate Content and Channels Department produced 480 digital‑communication artifacts. The SAC‑G pipeline achieved an average fluency score of 4.3 / 5, a brand‑voice consistency of 94 %, zero policy‑violation incidents, and a 38 % reduction in drafting time. The framework also maintained complete audit trails, enforced role‑based access, and prevented any data leakage during security audits. These results demonstrate that a governance‑centric, locally hosted generative‑AI architecture can deliver high‑quality, compliant digital communications at scale, offering a viable alternative to cloud‑based generative services for regulated enterprises.
Keywords: Generative AI, Governance, Security, Enterprise AI, Local LLM, Policy Engine, Digital Communications, Agentic AI, Audit Trail, Data Protection.
Title: A Governance and Security Framework for Enterprise Adoption of Generative AI Digital Communications
Author: Asif Ali Khan
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 14, Issue 3, July 2026 - September 2026
Page No: 115-119
Research Publish Journals
Website: www.researchpublish.com
Published Date: 29-September-2026
