About us
At Cooper University Health Care, our commitment to extraordinary care begins with our people. Our teams are empowered to innovate—continuously advancing clinical excellence while expanding access to leading‑edge facilities, equipment, technologies, and research protocols.
As an AI‑forward academic health system, Cooper is intentionally shaping the future of health care. We are embracing intelligent technologies that enhance clinical decision‑making, streamline workflows, and unlock new possibilities in patient care, education, and research. Our professionals don’t just adapt to change—they help lead it.
We demonstrate our commitment to our team members through competitive compensation, a comprehensive benefits program, supportive and collaborative work environments, and meaningful opportunities for career growth and professional development. At Cooper, you have the chance to build a career while helping redefine what’s possible in modern health care.
Discover why Cooper University Health Care is the employer of choice in South Jersey—and a place where innovation, purpose, and people come together.
Short Description
The Chief AI Officer (CAIO) is responsible for leading Cooper University Health Care’s enterprise-wide artificial intelligence strategy, governance, and innovation agenda. This executive role ensures that AI capabilities are responsibly designed, deployed, and scaled to drive clinical innovation, operational excellence, efficiency, and long -term strategic advancement. Wide artificial intelligence strategy, governance, and innovation agenda. This executive role ensures that AI capabilities are responsibly designed, deployed, and scaled to drive clinical innovation, operational excellence, efficiency, and long term strategic advancement.
While data remains a critical foundation for meaningful AI, the CAIO’s primary focus is on accelerating AI adoption, shaping enterprise AI governance, and guiding Cooper’s evolution into an AI -enabled healthcare system.
Overview
AI Strategy & Transformation Leadership
- Enterprise AI Strategy
- Develop and execute a comprehensive AI strategy aligned to Cooper’s clinical, operational, and strategic priorities. Define the roadmap for safe, ethical, and scalable AI adoption.
- AI Innovation & Solution Deployment
- Lead the exploration, evaluation, and implementation of AI solutions —including clinical decision support, automation, predictive modeling, and generative AI —to enhance care delivery and operational efficiency.
- AI Governance, Safety & Compliance
- Establish governance frameworks to ensure AI quality, transparency, safety, and compliance with HIPAA, CMS, FDA, and responsible AI standards.
- Cross -Functional AI Collaboration
- Partner with clinical, operational, and administrative leaders to identify high -impact AI opportunities that improve performance and advance the patient and caregiver experience.
Technology & Platform Leadership
- AI Platform & Tooling Oversight
- Evaluate, select, and implement enterprise AI platforms, LLM technologies, and automation tools supporting Cooper’s mission.
- AI-Ready Data Foundations
- Ensure the availability of high -quality, well -governed data sources required for safe, effective AI use—including data engineering, integration, and metadata visibility.
AI Workforce & Culture
- Team Development & Talent Leadership
- Build and lead a high -performing team of AI engineers, data scientists, machine -learning specialists, and applied innovation roles. Foster a culture of responsible AI, experimentation, and continuous learning.
- AI Literacy & Change Management
- Drive enterprise AI literacy, including training clinicians and staff on AI capabilities, limitations, and safe use.
Enterprise Data Governance Leadership
- Co-develop and operationalize Cooper’s enterprise data governance strategy, aligned with the CAIO’s AI and data readiness vision.
- Establish governance frameworks, policies, and standards that ensure quality, lineage, stewardship, privacy, and ethical use of data.
- Lead enterprise data stewardship programs and define roles, responsibilities, and accountability across the organization.
Data Quality & Integrity
- Implement and oversee enterprise processes for data quality monitoring, issue remediation, and continuous improvement.
- Ensure the accuracy, completeness, timeliness, and reliability of data used for analytics, AI models, and clinical decision support tools.
Performance & Value Realization
- Outcome Measurement
- Define and monitor KPIs for AI initiatives and communicate impact to executive leadership and the board, ensuring measurable value and alignment with organizational goals.
Partnerships & Thought Leadership
- External Innovation & Industry Collaboration
- Cultivate partnerships with tech companies, academic institutions, and AI vendors to accelerate Cooper’s AI maturity and innovation pipeline.
- Healthcare AI Thought Leadership
- Represent Cooper nationally as a leader in responsible AI adoption and healthcare transformation.
Regulatory Compliance & Risk Management
- Ensure compliance with HIPAA, CMS, OCR, FDA (for clinical AI), and emerging AI -related regulatory requirements.
- Work with Privacy, Security, Legal, and Compliance to manage data -related risks, including model input governance and data access transparency.
Foundational Responsibilities
Demonstrate Cooper Core Values, Service Standards, and Leadership Must -Haves. Utilize AIDET at all times.
AI-Focused Competencies
(With data and analytics reframed as supporting capabilities)
- AI Strategy & Policy Development
- Expertise in enterprise AI strategy, responsible AI frameworks, governance, and implementation.
- AI Literacy & Change Leadership
- Ability to translate complex AI concepts into operational and clinical value; lead organization -wide readiness efforts.
- Machine Learning & Advanced Analytics
- Understanding of predictive modeling, LLMs, natural language processing, graph technologies, and automation.
- AI-Ready Data Foundations
- Knowledge of data structures, architectures (e.g., data fabric, mesh), data integration, and metadata management as a prerequisite for operationalizing AI.
- Responsible AI & Compliance
- Understanding of model risk, bias detection, validation, privacy, security, and regulatory considerations.
- Optional (Preferred):
- Familiarity with analytics tools, enterprise information systems, and content management environments.
Management & Operational Responsibilities
- Develop and manage the CAIO office budget.
- Lead an enterprise AI Center of Excellence to continuously elevate organizational AI capabilities.
- Define team roles, recruit talent, and manage distributed AI and data professionals.
- Oversee AI platform architecture, with optional partnership with the CIO for shared technology operations and horizon scanning of emerging AI capabilities.
Experience Required
- 5-7 years prior experience in analytics or organizational performance improvement
- Knowledge and understanding of relevant legal and regulatory requirements
- Demonstrated Legal IT contract knowledge
- Strong communication and relationship management skills.
- Sound knowledge of business management and a working knowledge analytics and AI tools and processes
- Up-to-date knowledge of methodologies and trends in both business and IT
Education Requirements
Bachelor’s Degree required