Abstract
Artificial intelligence (AI)-enabled systems are transforming public service delivery, representing a growing innovation in the public sector that promises greater efficiency and personalization. Although prior studies have identified factors influencing adoption, a limited understanding remains of how these factors shape users’ trust and adoption intention. To address this, building on quantitative findings that identified performance expectancy, security, cybersecurity law, recommendation quality, and trust as key constructs, this study employed three focus groups with thirteen participants in Saudi Arabia. Thematic analysis revealed that participants emphasized time-savings, efficiency, and continuous availability, while trust was shaped through confidence in the technology, the provider, and the reliability of the outputs. Regulatory assurance and security measures further reinforced confidence, and personalization and accuracy enhanced recommendation quality. These findings contribute a qualitative perspective that illustrates how perceptions translate into adoption, offering a richer understanding of users’ views toward AI-enabled public services.
Recommended Citation
Alqahtani, Ahmed; Yan, Jun; Vlahu-Gjorgievska, Elena; and Cao, Cong, "Toward Understanding Users’ Trust and Adoption of
AI-Enabled Public Services" (2025). ACIS 2025 Proceedings. 276.
https://aisel.aisnet.org/acis2025/276