Improving Public-Sector Service Delivery through ServiceNow-Based ITSM Workflow Automation: An AI-Driven Approach to Reducing Manual Case Handling and Response Time in Government Benefit Systems
TL;DR
ServiceNow-based ITSM and AI-enabled workflow capabilities can improve operational efficiency, workflow development, and service delivery in public-sector benefits administration and future research should independently evaluate deployed ServiceNow systems across technical efficiency, workforce, fairness, governance, and citizen-trust outcomes.
Abstract
Aim: This study aimed to synthesize reported evidence on ServiceNow-based Information Technology Service Management (ITSM), including Now Assist and Flow Designer, in public-sector benefits administration, with particular emphasis on workflow efficiency, citizen trust and adoption, workforce outcomes, and governance and accountability. Methods: A structured integrative literature review with qualitative thematic synthesis was conducted using 45 sources, comprising peer-reviewed studies, government reports, professional surveys, industry research, platform documentation, and vendor case studies. The primary search period covered January 2015 to July 2026. The evidence was thematically classified into four categories: technical efficiency, citizen adoption and trust, workforce impact, and governance and accountability. Results: The reviewed evidence indicated improvements in workflow efficiency and service delivery in several reported contexts. Among directly summarized workflow examples, AI-assisted workflow design reduced development time by approximately 50.0%–51.9%, while workflow cycle time decreased from 25.1 to 23.4 days, representing an approximately 6.8% reduction. A separate ServiceNow vendor case study reported an 80-fold increase in Internal Revenue Service (IRS) throughput. In other study contexts, self-service adoption was reported at approximately 35%, while one model explained approximately 67% of the variance in adoption through trust-related factors. These estimates originated from different contexts and were therefore not treated as directly comparable or as pooled effects. Evidence on AI-governance maturity was inconsistent. Conclusion: ServiceNow-based ITSM and AI-enabled workflow capabilities can improve operational efficiency, workflow development, and service delivery in public-sector benefits administration. Recommendation: Future research should independently evaluate deployed ServiceNow systems across technical efficiency, workforce, fairness, governance, and citizen-trust outcomes.
