Title : Personalization at scale: Harnessing AI and automation to transform clinical onboarding across a large ambulatory health system
Abstract:
Background: Providing consistent clinical onboarding across more than 400 geographically dispersed ambulatory clinics presents a significant challenge for a small, centralized nursing professional development team. New clinical team members enter practice with varying experience, knowledge, learning needs, and confidence, while differences in specialty and practice environment further complicate a standardized approach. Traditional onboarding models often require a trade-off between scalability and personalization: standardized education can be deployed broadly but may not address individual learning needs, while individualized onboarding requires substantial educator time and resources.
Purpose: To develop and implement Constellation, a scalable ambulatory clinical onboarding model that leverages generative artificial intelligence (AI), structured assessment, targeted education, workflow automation, and centralized tracking to provide personalized learning and support across a large, geographically dispersed clinical network.
Approach: An iterative human-AI co-design process was used to develop the constellation program architecture, clinical onboarding assessment, computer-based learning modules, applied ambulatory case studies, individualized learning pathways, preceptor resources, structured educator check-ins, and supporting workflows. Assessment findings identify individual strengths and opportunities for development and activate targeted educational assignments. Rather than requiring all new hires to complete identical education, learners are assigned purpose-built modules and case studies aligned with identified knowledge gaps. Automated Microsoft 365 and Power Automate workflows monitor assessment completion, communicate individualized results and learning expectations, distribute learner-specific preceptor guidance, facilitate structured educator follow-up, and track onboarding milestones. Nursing professional development educators retain oversight of clinical and educational content and provide professional judgment, coaching, and intervention when indicated.
Implementation: Constellation created an integrated infrastructure connecting assessment, targeted education, applied learning, preceptor support, educator follow-up, automation, and centralized tracking across the onboarding journey. Early implementation across varied roles, specialties, clinical settings, and geographic areas demonstrates the feasibility of delivering individualized onboarding across a large ambulatory network without requiring direct educator intervention at every step. Ongoing implementation data will characterize program reach, learner needs, educational assignments, and progression through the onboarding pathway.
Implications for Practice: Constellation demonstrates how generative AI and workflow automation can function as capacity multipliers for nursing professional development teams. AI expanded the team's capacity to design a comprehensive onboarding ecosystem and targeted learning experiences, while automation enabled individualized processes to be executed consistently at scale. This model offers a practical approach for organizations seeking to preserve human judgment and connection while moving beyond the traditional choice between standardized education that scales and individualized education that consumes significant educator resources.
