Vice President, Chief Data and Artificial Intelligence Officer

Sanford Health•Sioux Falls, SD

About The Position

The Chief Data and Artificial Intelligence Officer (CDAIO) is responsible for defining and executing the enterprise data, analytics, robotic process automation, and AI strategy for the health system. This role ensures that data and AI are trusted, secure, ethical, and effectively leveraged to improve clinical outcomes, operational efficiency, patient experience, research, and financial performance. The CDAIO operates at the intersection of clinical, operational, financial, and technology domains, translating complex capabilities into measurable business and care transformation outcomes while maintaining compliance with healthcare regulations and ethical AI standards. The CDAIO leads the development and execution of an enterprise-wide strategy aligned with the organization's mission and goals, serving as the executive champion for data-driven decision-making and AI-enabled transformation. This role partners with executive leadership, clinical leaders, and the board to identify high-impact use cases for analytics, machine learning, and generative AI. The CDAIO builds and leads high-performing teams across data engineering, analytics, data science, governance, and business intelligence, fostering a culture of innovation, accountability, and continuous improvement while driving alignment across the organization. A core responsibility of the role is establishing strong data and analytics governance. This includes overseeing data quality, stewardship, standards, interoperability, and metadata management, while ensuring compliance with HIPAA, HITECH, CMS, FDA, and other applicable regulations. The CDAIO promotes a "single source of truth" through consistent data definitions and leads the responsible integration of AI into clinical workflows to improve efficiency, reduce documentation burden, and enhance patient and provider experience. The CDAIO oversees the full lifecycle of AI, machine learning, and advanced analytics solutions across clinical care, population health, revenue cycle, supply chain, and workforce operations. Acting as the organization's central AI authority, this leader ensures solutions are ethical, transparent, and explainable, with strong oversight for bias mitigation, model performance, and clinical safety. The role also governs third-party AI tools and vendor partnerships and drives the integration of AI into care pathways, including predictive analytics, triage automation, and documentation support. In parallel, the CDAIO leads workflow redesign efforts to reduce inefficiencies, lower cognitive burden, and expand capacity, while partnering with clinical and operational leaders to modernize care delivery models. In addition, the CDAIO develops and executes strategies for data monetization and commercialization. This includes responsibly leveraging de-identified data assets, launching AI-enabled products such as predictive models and clinical algorithms, and forming strategic partnerships with life sciences organizations, startups, and academic institutions. The role establishes data-as-a-service and AI-as-a-service capabilities and defines an intellectual property strategy to extend organizational impact. From a clinical and operational perspective, the CDAIO works closely with physicians, nurses, and operational leaders to embed analytics and AI into workflows and decision support, driving measurable improvements in quality, safety, access, cost, and patient experience. The role also supports research, clinical trials, and innovation through advanced data platforms and expands the organization's reach to broader communities and markets. In partnership with the CIO and CDO, the CDAIO defines and maintains a modern, scalable data and AI architecture. This includes cloud-native platforms, real-time data streaming, master data management, interoperability frameworks such as FHIR and APIs, and the transition to a data lakehouse environment. The CDAIO ensures strong data security, privacy, and system resilience, working closely with the CISO to mitigate risks such as model poisoning, secure training data pipelines, monitor adversarial threats, and implement safe AI deployment practices. The role also advances research and innovation by integrating diverse data sources, including genomics, imaging, and clinical trials, into enterprise analytics. The CDAIO leads initiatives in areas such as federated learning, precision medicine, and predictive population health, while building partnerships that accelerate scientific and clinical advancement. As a leader of people and culture, the CDAIO builds and mentors high-performing teams and fosters enterprise-wide data and AI literacy. This includes developing training programs for leaders and clinicians, establishing an AI center of excellence, defining emerging roles, embedding AI champions across departments, and leading change management efforts to drive adoption and reduce resistance.

Requirements

Master’s degree in Business Administration, Health Administration, Information Technology, or a related field.
10+ years of progressive leadership experience in data, analytics, or AI, including significant experience in healthcare or life sciences.
A strong understanding of healthcare data domains, regulatory requirements, and data privacy and security is essential, along with a demonstrated track record of leading enterprise-scale transformations.

Nice To Haves

A clinical background or close experience working with clinicians, as well as exposure to academic medicine, population health, value-based care, digital health innovation, and evolving AI regulations.

Responsibilities

Defining and executing the enterprise data, analytics, robotic process automation, and AI strategy for the health system.
Ensuring that data and AI are trusted, secure, ethical, and effectively leveraged.
Improving clinical outcomes, operational efficiency, patient experience, research, and financial performance.
Translating complex capabilities into measurable business and care transformation outcomes.
Maintaining compliance with healthcare regulations and ethical AI standards.
Leading the development and execution of an enterprise-wide strategy aligned with the organization's mission and goals.
Serving as the executive champion for data-driven decision-making and AI-enabled transformation.
Partnering with executive leadership, clinical leaders, and the board to identify high-impact use cases for analytics, machine learning, and generative AI.
Building and leading high-performing teams across data engineering, analytics, data science, governance, and business intelligence.
Fostering a culture of innovation, accountability, and continuous improvement while driving alignment across the organization.
Establishing strong data and analytics governance.
Overseeing data quality, stewardship, standards, interoperability, and metadata management.
Ensuring compliance with HIPAA, HITECH, CMS, FDA, and other applicable regulations.
Promoting a "single source of truth" through consistent data definitions.
Leading the responsible integration of AI into clinical workflows.
Overseeing the full lifecycle of AI, machine learning, and advanced analytics solutions.
Ensuring solutions are ethical, transparent, and explainable, with strong oversight for bias mitigation, model performance, and clinical safety.
Governing third-party AI tools and vendor partnerships.
Driving the integration of AI into care pathways, including predictive analytics, triage automation, and documentation support.
Leading workflow redesign efforts to reduce inefficiencies, lower cognitive burden, and expand capacity.
Partnering with clinical and operational leaders to modernize care delivery models.
Developing and executing strategies for data monetization and commercialization.
Responsibly leveraging de-identified data assets.
Launching AI-enabled products such as predictive models and clinical algorithms.
Forming strategic partnerships with life sciences organizations, startups, and academic institutions.
Establishing data-as-a-service and AI-as-a-service capabilities.
Defining an intellectual property strategy to extend organizational impact.
Working closely with physicians, nurses, and operational leaders to embed analytics and AI into workflows and decision support.
Driving measurable improvements in quality, safety, access, cost, and patient experience.
Supporting research, clinical trials, and innovation through advanced data platforms.
Expanding the organization's reach to broader communities and markets.
Defining and maintaining a modern, scalable data and AI architecture.
Ensuring strong data security, privacy, and system resilience.
Mitigating risks such as model poisoning, secure training data pipelines, monitor adversarial threats, and implement safe AI deployment practices.
Advancing research and innovation by integrating diverse data sources, including genomics, imaging, and clinical trials, into enterprise analytics.
Leading initiatives in areas such as federated learning, precision medicine, and predictive population health.
Building partnerships that accelerate scientific and clinical advancement.
Building and mentoring high-performing teams.
Fostering enterprise-wide data and AI literacy.
Developing training programs for leaders and clinicians.
Establishing an AI center of excellence.
Defining emerging roles.
Embedding AI champions across departments.
Leading change management efforts to drive adoption and reduce resistance.