The Digital Laboratory Assurance Framework DLAF A Conceptual Governance Model for AI Cybersecurity and Digital Laboratory Operations in ISO IEC 17025 Laboratories

Artificial intelligence (AI), cloud services and remote operations can affect the validity and confidentiality of laboratory results. This short communication proposes the Digital Laboratory Assurance Framework (DLAF), a conceptual model for translating digital risks into laboratory controls and evidence. ISO/IEC 17025:2017 provides the primary laboratory requirements; AI and information-security instruments provide supporting controls. Five functional layers cover technology and scope, risk assessment, requirements and controls mapping, laboratory controls, and continuous assurance. Governance operates across every layer and establishes responsibilities and acceptance criteria before risk evaluation. Clause mapping distinguishes existing requirements from proposed DLAF practices, including controls for external AI services, model changes and human review. Three conceptual use cases and a hypothetical tensile-testing protocol illustrate application without constituting implementation evidence. An assurance maturity model evaluates control effectiveness independently of technological sophistication. DLAF has not been empirically validated; its proposed benefits and usability require laboratory pilots and independent evaluation.