From Structured Documentation to Intelligent Self-Service: Leveraging AEM Guides and Large Language Models

Authors

  • Rakesh Konda Texas Tech University, USA Author

DOI:

https://doi.org/10.32628/CSEIT25112360

Keywords:

DITA Framework, AEM Guides, Large Language Models, Structured Documentation, Intelligent Self-Service

Abstract

This article explores the transformative potential of integrating structured documentation systems, specifically Adobe Experience Manager (AEM) Guides, with Large Language Models (LLMs) in the context of technical documentation and customer support. It delves into the foundations of the DITA framework and AEM Guides, highlighting their role in creating modular, reusable content. The article then examines the capabilities and current applications of LLMs in customer support, addressing both their strengths and limitations. The core of the article focuses on the synergy between AEM Guides and LLMs, detailing the technical implementation, data preparation considerations, and the resulting benefits such as improved response accuracy, enhanced scalability, cost reduction, and personalized user experiences. Challenges including data privacy, content quality maintenance, and balancing automation with human expertise are critically discussed. The article concludes by exploring future directions in AI-enhanced documentation and self-service systems, including potential advancements in AI technologies and emerging trends like predictive support and emotional intelligence in AI systems. This comprehensive article analysis provides insights into how the integration of structured documentation with advanced AI can revolutionize customer support and technical communication strategies in the digital age.

Downloads

Download data is not yet available.

References

Gartner, "Gartner Predicts 80% of Customer Service Organizations Will Abandon Native Mobile Apps in Favor of Messaging by 2025" January 12, 2021. [Online] Available: https://www.gartner.com/en/newsroom/press-releases/2021-01-12-gartner-predicts-80--of-customer-service-organization

Patrick Bosek ,Joe Gelb , et al., The Content Wrangler, "2020 DITA Satisfaction Report" 2017. https://www.precisioncontent.com/wp-content/uploads/2016/10/2020-DITA-satisfaction-report.pdf

Alex Shipps | MIT CSAIL, August 14, 2024. MIT News, "LLMs develop their own understanding of reality as their language abilities improve" 2023. https://news.mit.edu/2024/llms-develop-own-understanding-of-reality-as-language-abilities-improve-0814

Ignacio Romero, et al., (February 2021). Impact of the Application of Artificial Intelligence Technologies in a Content Management System of a Media. 10.1007/978-3-030-67148-8_11. http://dx.doi.org/10.1007/978-3-030-67148-8_11

Avinash Chandra Das, et al. McKinsey & Company ( January 29, 2021), "The next frontier of customer engagement: AI-enabled customer service” https://www.mckinsey.com/capabilities/operations/our-insights/the-next-frontier-of-customer-engagement-ai-enabled-customer-service

Mariam Yusuff. (2023). Ensuring Compliance with GDPR, CCPA, and Other Data Protection Regulations: Challenges and Best Practices. https://www.researchgate.net/publication/387224965_Ensuring_Compliance_with_GDPR_CCPA_and_Other_Data_Protection_Regulations_Challenges_and_Best_Practices

Harvard Business Review, "How AI Is Changing the ROI of Customer Service" 2022. https://hbr.org/sponsored/2025/01/how-ai-is-changing-the-roi-of-customer-service

Gloria Omale, Gartner, "Top Customer Service and Support Predictions for 2021 and Beyond," 2022. https://www.gartner.com/smarterwithgartner/top-customer-service-and-support-predictions-for-2021-and-beyond

Downloads

Published

03-03-2025

Issue

Section

Research Articles