Authors:
Manoj Parasa, Sasi Kiran Parasa

Addresses:
Department of Information Technology Services, Ernst and Young, Dallas, Texas, United States of America. Department of Information Technology Services, MongoDB, Austin, Texas, United States of America.

Abstract:

The rapid advancement of digital transformation in human capital management has redefined the expectations of employee self-service (ESS) systems, demanding intelligent, personalised, and autonomous support experiences. This research explores the integration of conversational artificial intelligence within SAP SuccessFactors to automate HR service delivery and enhance the responsiveness of ESS portals. Through a mixed-methods methodology combining system prototyping, quantitative performance analysis, and qualitative user feedback, the study demonstrates how chatbot-augmented ESS platforms can reduce administrative dependency, accelerate query resolution, and strengthen employee engagement. The implementation revealed a substantial reduction in response latency and a measurable rise in satisfaction levels, indicating that conversational AI can act as both a service enabler and an engagement amplifier within digital HR ecosystems. The findings contribute to the design of a scalable, ethically grounded framework for deploying AI-driven self-service in enterprise environments, providing a pathway for organisations to build adaptive, human-centric, and future-ready workforce support architectures.

Keywords: Conversational AI; Employee Self-Service (ESS); Human Capital Management; SAP SuccessFactors; Digital Transformation; Digital HR Ecosystems; System Prototyping; Grounded Framework.

Received on: 21/09/2024, Revised on: 11/12/2024, Accepted on: 08/03/2025, Published on: 09/09/2025

DOI: 10.69888/FTSML.2025.000444

FMDB Transactions on Sustainable Management Letters, 2025 Vol. 3 No. 3, Pages: 104-112

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