AI Progam Manager, IT Dept

UCSF•San Francisco, CA

12d•$160,000 - $225,000•Hybrid

About The Position

The AI Program Manager serves as an organization-wide expert and strategic advisor leading UCSF’s enterprise AI program across clinical care, research, education, and administrative operations. The incumbent partners with Enterprise AI product, technical, and leadership stakeholders to translate institutional priorities and complex business needs into adoption plans, enablement programs, stakeholder engagement strategies, feedback loops, and sustainable operating practices. The role evaluates organizational readiness, workflows, stakeholder needs, and performance data to identify opportunities that improve institutional effectiveness, workforce experience, quality, and mission outcomes. The incumbent coordinates adoption, enablement, communications, stakeholder engagement, value tracking, and operational readiness for a high-impact portfolio of AI initiatives, from intake through implementation, adoption, value realization, and transition to operations. The role supports prioritization and resource planning by preparing analysis, maintaining visibility into progress and risks, facilitating multidisciplinary coordination, and escalating complex or politically sensitive issues for leadership decision-making. The AI Program Manager leads awareness and adoption of approved AI tools by communicating available capabilities, appropriate use cases, limitations, support resources, and product roadmaps. Working with senior leaders and clinical, research, academic, operational, technology, and risk stakeholders, the incumbent advances responsible AI adoption, informs vendor and product decisions, leads organizational change, and represents UCSF in relevant University and industry forums. The role works in close partnership with Enterprise AI product leadership, which retains accountability for product strategy, platform roadmap, prioritization recommendations, and product/vendor decision-making. UCSF Enterprise Information and Analytics (EIA) advances the institution’s data and analytics capabilities in support of patient care, research, education, and administrative operations. Enterprise AI builds on this foundation by delivering secure, scalable, and responsible artificial intelligence capabilities to the UCSF community. The program integrates AI strategy, governance, platforms, portfolio management, adoption, training, communications, and stakeholder engagement, and supports enterprise services such as UCSF ChatGPT Enterprise and the Versa API.

Requirements

Bachelor’s degree in a related area and/or equivalent experience or training.
Minimum of 10 years of progressively responsible experience in organizational consulting, strategic planning, or organizational change, including leading complex cross-functional initiatives.
Expert knowledge of enterprise program management, organizational effectiveness, strategic planning, and change management, with demonstrated ability to lead complex transformation initiatives from strategy through implementation, adoption, and operational transition.
Knowledge of generative AI capabilities, limitations, and adoption patterns, including associated privacy, security, safety, ethical, accessibility, and responsible-use considerations.
Demonstrated ability to design and operate portfolio intake, evaluation, prioritization, governance, business-case, and value-realization processes.
Advanced analytical and problem-solving skills, including ability to evaluate complex organizational needs, workflows, risks, dependencies, resource requirements, and expected benefits.
Demonstrated ability to lead multidisciplinary teams and influence senior leaders and technical, clinical, research, academic, administrative, operational, and governance stakeholders without direct authority.
Demonstrated ability to design and scale adoption and enablement programs and communicate complex AI capabilities, risks, use cases, and roadmaps through training, demonstrations, communities of practice, and other engagement methods.
Strong technical fluency across enterprise applications, systems integration, data and analytics platforms, information security, cloud services, or enterprise architecture, with ability to translate between technical teams and organizational stakeholders.
Demonstrated ability to establish performance measures and use quantitative and qualitative data to evaluate adoption, user experience, risk, program health, and institutional value.
Ability to exercise independent judgment, establish priorities, and resolve highly complex or politically sensitive issues involving ambiguity, competing interests, and multiple constituencies.

Nice To Haves

Advanced degree in a related area.
Project Management Professional (PMP) or Program Management Professional (PgMP) certification.
Specialized certifications in AI/ML project lifecycle delivery, such as PMI-CPMAI or CAIPM.
Knowledge of product and vendor management practices, including capability assessment, requirements development, roadmap evaluation, deployment readiness, and vendor performance management.
Experience leading enterprise technology programs in healthcare, academic medicine, research, higher education, or another regulated environment, including familiarity with applicable data governance, privacy, security, and compliance requirements.
Experience with enterprise generative AI platforms, large language model services, AI-enabled workflows, or related emerging technologies.

Responsibilities

Lead development and execution of UCSF’s enterprise AI adoption, enablement, governance, community engagement, and communications strategies in alignment with enterprise AI product strategy, roadmap, governance model, and operating framework.
Assess institutional priorities, organizational readiness, emerging capabilities, and regulatory requirements to recommend strategies aligned with UCSF’s clinical care, research, education, and administrative missions.
Direct a portfolio of complex, high-impact AI initiatives from intake and business-case development through prioritization, governance, implementation, adoption, and transition to sustainable operations.
Establish program plans, dependencies, resource requirements, decision points, and escalation processes across concurrent initiatives.
Facilitate cross-functional collaboration among senior leaders, faculty, clinicians, operational units, technology teams, and privacy, security, legal, compliance, accessibility, and risk stakeholders.
Align participants, resolve complex organizational issues and competing priorities, and address implementation barriers through consultation and influence.
Develop and execute the enterprise awareness, communications, and adoption strategy for approved AI tools and services.
Maintain and promote information about available tools, capabilities, appropriate use cases, planned enhancements, roadmaps, training, and support resources through targeted communications, demonstrations, learning forums, and user communities.
Establish transparent processes for identifying, evaluating, and prioritizing AI opportunities.
Analyze business needs, workflows, stakeholder impacts, risks, expected benefits, and organizational readiness to recommend investments and scalable solutions.
Define and monitor measures for program performance, adoption, user experience, institutional value, risk, and mission outcomes.
Use quantitative and qualitative findings and stakeholder feedback to improve services, guide resource allocation, and inform portfolio and roadmap decisions.
Advise product owners and technology leaders on AI platform capabilities, service design, vendor performance, and product roadmaps.
Engage technology providers and internal partners to communicate UCSF requirements, evaluate emerging capabilities, and address gaps between institutional needs and available services.
Serve as an enterprise AI subject-matter expert, represent UCSF in relevant external partnerships and professional forums, and guide project teams and less-experienced professionals in AI program management, organizational change, and stakeholder engagement practices.