AI Enablement Manager

Franciscan Alliance, Inc.

1d•Remote

About The Position

The AI Enablement Manager leads the coordination, execution, and oversight of the organization's AI initiatives to ensure safe, compliant, and value‑driven adoption of artificial intelligence across clinical, research, operational, and enterprise domains. This role operationalizes AI governance framework, manages the AI initiative portfolio, and ensures alignment with regulatory requirements, organizational priorities, and risk‑management standards. This function drives the structured intake, review, monitoring, reporting, and lifecycle‑management processes to support responsible and scalable AI deployment. Serving as a central connector across Franciscan Alliance, this role partners with clinical, technical, legal, compliance, security, and operational teams to ensure AI solutions are evaluated, implemented, and monitored consistently and transparently. In addition, the AI Enablement Manager champions AI literacy, promotes responsible‑use practices, and supports change‑management efforts to help Franciscan Alliance adopt AI safely and effectively. This role plays a critical part in maturing the organization's AI operating model, enabling innovation while safeguarding patient safety, data integrity, and organizational trust, while supporting the AI governance council and steering committees in fulfillment of charter responsibilities.

Requirements

Bachelor's Degree Business, Computer Science, Engineering, Information Systems, Public Health, or related field
8 years Program management in data governance, analytics, information services, or related field.
5 years Setting up and scaling program, governance or oversight processes across a maturing data and/or AI portfolio.
2 years Measuring and reporting AI performance, safety, value, and risk across the AI lifecycle.

Nice To Haves

Master's Degree Business, Computer Science, Engineering, Information Systems, Public Health, or related field
2 years Managing AI, analytics, or model-based systems in healthcare or other regulated industries.
1 year Utilizing healthcare AI governance frameworks and regulatory standards (e.g., NIST, ISO, FDA, HIPAA).

Responsibilities

Coordinate cross-functional review and assessment of AI driven solutions across clinical, operational, technical, compliance, privacy, legal, and security teams.
AI Governance Lead execution of the enterprise AI governance framework and oversee end-to-end AI lifecycle management.
AI Regulations Monitor evolving AI regulations and industry best practices; translate requirements into program and control enhancements.
Supporting Council Manage the centralized AI governance program supporting AI governance council, Clinical/Business AI steering committees, and overall executive oversight.
Cases Ensure AI initiatives include documented use cases, architecture reviews, risk assessments, data lineage, bias evaluation, and control frameworks.
Stakeholders Facilitate enterprise-wide stakeholder collaboration and governance alignment, working with committee co-chairs and senior leaders across IS and operations.
Inventory Maintain the enterprise AI inventory with full traceability, documentation standards, model metadata, and audit readiness.
Governance Define technical governance controls including model validation standards, monitoring requirements, performance thresholds, and change management protocols.
Working Sessions Lead working sessions with business and technical teams to clarify requirements and ensure alignment.
Implementation Oversee implementation of model monitoring, drift detection, incident response processes, and remediation tracking.
Reporting Provide executive reporting on AI risk posture, safety, adoption, performance, and enterprise impact.
Guidance Provide clear technical and governance guidance on lifecycle expectations, documentation standards, and risk controls.
Policies Create and update AI policies, standards, and acceptable‑use guidelines.
Programs Lead enablement programs, training, and communication to help teams understand AI policies, risks, and best practices.