PIF-PAF: Proficiency Infusion Framework for Professional AI Fluency: A Training Architecture for AI Capability Development in Higher Education Administration with Application to Prior Learning Assessment

Abstract

Generative AI integration in higher education administration requires more than awareness training; it demands systematic capability development aligned with institutional maturity and role-specific requirements. This concept paper introduces the Proficiency Infusion Framework for Professional AI Fluency (PIF-PAF), a training architecture that infuses PAF capabilities into specific professional domains through use-case-driven development aligned with organizational maturity levels. PIF-PAF addresses a critical gap: while the Professional AI Fluency (PAF) framework specifies what AI competence looks like and the EMERALD capability maturity model specifies where institutions are headed, neither provides the operational training pathway connecting the current state to the target capability. Drawing on established infusion pedagogies from technology integration, ethics education, and critical thinking instruction, PIF-PAF embeds proficiency development within domain-specific professional practice rather than treating AI as a standalone technical training. The framework intersects three dimensions—PAF capability pillars, EMERALD maturity levels, and proficiency stages—producing a matrix of use cases that specify exactly what to train, for whom, and to what standard. This paper demonstrates PIF-PAF through an application to Prior Learning Assessment (PLA), a domain in which administrative professionals must simultaneously master AI tools, advise students on appropriate AI use, and navigate governance complexities. The PAF-PLA instantiation maps eight capability pillars to ten operational use cases spanning account governance, file management, document analysis, professional communication, custom GPT development, knowledge base curation, advanced research, and self-leadership. Each case specifies Level 2 (foundational) and Level 3 (intermediate) expectations, producing a training roadmap for a small team of PLA professionals culminating in demonstrated competency through portfolio evidence. The framework's transferability is illustrated through potential extensions to faculty development and other administrative functions. PIF-PAF contributes a replicable methodology for institutions designing AI training programs that connect individual proficiency development to organizational capability maturation.

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