THE ROLE OF AI-GENERATED CONTENT IN ENTERPRISE CONTENT MANAGEMENT (ECM) WORKFLOWS

Authors

  • Anoosha Cherukuri Sr Software Developer, State of Tennessee, USA. Author

DOI:

https://doi.org/10.34218/IJCET_16_03_015

Keywords:

ECM, Content Automation, NLG, Intelligent Document Processing, AI-generated Content, Governance, Metadata, Compliance, Workflow Automation, Knowledge Management

Abstract

The increasing presence of generative artificial intelligence (AI) in modern organizations is beginning to transform Enterprise Content Management (ECM) systems in profound ways. Historically, ECM platforms managed human-created documents—policies, contracts, internal memos—but today, tools like large language models (LLMs) are entering this ecosystem. AI is helping draft reports, summarize meetings, and populate knowledge bases. While the benefits of speed and scale are evident, organizations must also grapple with serious questions of content governance, compliance, and trust. This paper outlines the opportunities and challenges posed by AI-generated content in ECM and offers practical guidance for responsible implementation.

Key Findings AI-generated content enhances ECM efficiency by automating document creation and reducing manual workload. Natural Language Generation (NLG) improves consistency and scalability in enterprise communication. AI supports better metadata tagging and classification, aiding searchability and compliance. Integration of AI in ECM streamlines workflows and strengthens policy enforcement. Key challenges include content authenticity, explainability, and governance risks. Human-AI collaboration ensures quality control and preserves content integrity. Organizations report improved productivity and faster knowledge delivery. Standardization and ethical frameworks are essential for sustainable AI-ECM integration.

References

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Published

2025-05-23

How to Cite

Anoosha Cherukuri. (2025). THE ROLE OF AI-GENERATED CONTENT IN ENTERPRISE CONTENT MANAGEMENT (ECM) WORKFLOWS. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY, 16(3), 188-195. https://doi.org/10.34218/IJCET_16_03_015