Artificial Intelligence-Driven Chatbots and Intelligent Agents for Monitoring, Evaluation, and Organisational Learning: A Review of Techniques and Trends
Abstract
Artificial Intelligence (AI)-driven chatbots and intelligent agents are increasingly deployed to support monitoring, evaluation, and organisational learning. Advances in large language models, retrieval-augmented generation, and multi-agent architectures have expanded conversational AI. Despite growing adoption, existing research remains fragmented across technical, educational, and organisational domains, limiting holistic understanding of their design, impact, and governance. This gap creates challenges for organisations seeking evidence-based guidance for implementation. The purpose of this study is to examine and synthesise existing literature on the design, adoption, and impact of AI-based chatbots and intelligent agents within the contexts of monitoring, evaluation, and internal organisational operations. This study presents a systematic literature review and bibliometric analysis of peer-reviewed studies (2021-2025). The review analyses publication trends, core techniques, and application areas of AI-driven chatbots and intelligent agents. Findings reveal rapid growth and increasing focus on organisational learning and evaluation use cases. The study contributes a consolidated synthesis of techniques, benefits, and challenges, identifies research gaps, and offers directions for future research and evidence-based adoption of conversational AI in organisational environments.
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