HUMAN–AI COLLABORATION READINESS AMONG ALLIED HEALTHCARE PROFESSIONALS IN SAUDI ARABIA: A NARRATIVE REVIEW

Abstract

Background: Artificial intelligence (AI) is increasingly embedded in diagnostic, decision-support, and administrative workflows across healthcare systems. Allied healthcare professionals (AHPs) — including nurses, pharmacists, radiographers, laboratory technologists, physical and respiratory therapists — form the largest segment of the clinical workforce, yet their readiness for human–AI collaboration remains comparatively under-studied relative to physicians. Saudi Arabia's Vision 2030 digital-health agenda makes this an especially timely question for the Kingdom's health system.

Objective: This narrative review synthesizes recent evidence on AI readiness, trust, and adoption among allied healthcare professionals, with particular attention to the Saudi Arabian context, and proposes an integrative multi-level readiness framework.

Methods: A structured narrative literature search was conducted in PubMed for studies published largely between 2021 and 2026 addressing AI knowledge, attitudes, trust, and adoption among allied health and related clinical professionals. Twenty-three studies meeting relevance criteria were screened, extracted, and thematically synthesized; direct quotations were avoided in favor of original synthesis.

Results: Six recurring themes emerged: (1) a persistent knowledge–enthusiasm or awareness–practice gap; (2) a “trust-optimism paradox” in which positive general attitudes coexist with low trust in specific AI recommendations; (3) discipline-specific variation in perceived task fit across allied professions; (4) organizational and governance barriers to workflow integration; (5) uneven curricular and continuing-education preparation; and (6) a broader national digital-health readiness culture in Saudi Arabia that is more advanced at the policy level than at the point-of-care allied-workforce level.

Conclusions: Readiness for human–AI collaboration among Saudi allied healthcare professionals is best understood as a multi-level construct spanning individual, professional/task, organizational, and system layers. Calibrated — rather than blind — trust, built through transparent, explainable, and role-specific AI training, appears central to safe and sustained adoption. Targeted, profession-specific AI literacy programs aligned with Vision 2030 governance structures are recommended.