Multi-Cloud and Cloud-Native Strategies for Digital Human Capital Management in Saudi Arabia: Building Scalable and Future-Ready HR Technology Platforms
Digital human capital management increasingly depends on interconnected recruitment, payroll, learning, workforce planning and employee-service applications. Yet distributing these functions across cloud providers does not automatically produce integration, resilience or trustworthy personnel decisions. This integrative review examines how multi-cloud and cloud-native strategies can support scalable human resource technology platforms in Saudi Arabia while preserving information accountability and employee confidence. Thirty peer-reviewed publications issued during 2020–2025 are examined across software architecture, electronic human resource management, cyber security and Saudi digital transformation. The synthesis distinguishes application portability from data portability, technical availability from operational continuity, and analytic capability from legitimate data use. It proposes a layered reference architecture combining domain-oriented services, controlled integration, sovereign data stewardship, interoperable identity and observable operations. A staged implementation pathway is developed for organisations modernising heterogeneous enterprise systems, together with indicators for evaluating capability, fairness, resilience and economic sustainability. The evidence suggests that selective workload placement and disciplined platform engineering are more defensible than indiscriminate replication across providers. The principal contribution is an HR-specific governance framework that links technical architectural choices to human capital outcomes and Saudi institutional requirements. The framework remains conceptual and requires empirical evaluation before performance or compliance benefits can be asserted.
Authors
- Faraz Jameel Siddiqui
Publication Details
- Journal
- Iconic Research and Engineering Journals
- Published
- 2026-10-13
- DOI
- https://doi.org/10.64388/irev10i4-1723995
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00