Executive Director, DTS, AI & Automation

About the role

The Executive Director, DTS, AI & Automation is responsible for leading the vision, strategy, and execution of enterprise-wide AI initiatives, ensuring alignment with organizational goals while collaborating with senior leadership across clinical, operational, and finance domains.

Responsibilities

• Develops and executes the enterprise-wide AI vision, strategy, and initiative roadmap, ensuring alignment with organizational goals, security, and business outcomes.
• Serves as the organizational authority and champion for AI, inspire a culture of collaboration, innovation, and support.
• Builds, leads, and mentors a high-performing AI Innovation team providing strategic direction, professional development, performance management, accountability, and continuous learning.
• Develops and maintains strategic resource planning models, budget forecasts, and staffing strategies for the organization's AI and automation initiatives.
• Creates and maintains documentation standards for enterprise AI and automation assets, ensuring knowledge transfer and operational sustainability.
• Evaluate and prioritize AI opportunities across the organization, assessing strategic value, resource requirements, and ROI potential to build a comprehensive portfolio factoring business goal alignment, scalability, and innovation.
• Foster cross-functional collaboration to identify high-impact use cases for AI and automation, driving innovation and measurable business outcomes.
• Partners with business and clinical stakeholders to define, document, and transform critical workflows that deliver significant operational improvements to align with AI strategies, business needs, and ensure seamless integration.
• Directs and oversees the development of business cases, technical feasibility studies, and cost-benefit analyses for major AI initiatives, securing funding and resource allocation.
• Evaluates emerging AI technologies and vendor solutions, making strategic recommendations for enterprise adoption and integration.
• Affiliate technical and operational teams with build vs. buy decisions, implementations, and ongoing monitoring.
• Ensure seamless integration of AI into enterprise systems through oversight of change management, training, and post live performance monitoring.
• Reviews and approves high-level design specifications for enterprise AI and automation solutions, ensuring architectural alignment, security, scalability, and high-performance solutions.
• Lead training and change management initiatives to build organizational readiness for AI adoption.
• Monitor program performance against strategic KPIs, providing executive-level reporting on AI and automation outcomes and business value realization.
• Adjusting AI and automation strategies as needed to maximize value and minimize risk.
• Align with existing governance and ethical guidelines for AI adoption ensuring responsible use, transparency, and alignment with organizational policies/values.

Qualifications

• Education: Bachelor degree in health management, statistics, mathematics, finance, business, science, or other relevant program or equivalent experience. Preferred advanced degree in Computer Science, Data Science, Engineering, or related field.
• Experience: With a Bachelor's degree, 8 to 10 years of progressive, DTS healthcare related work experience; with at least five (5) years of AI experience demonstrating business and operations expertise in a leadership role.

Special skills

• Experience leading enterprise-wide AI and automation initiatives with advanced knowledge of conversational or agentic AI solutions, RPA platforms (UiPath, Blue Prism, Automation Anywhere), and their integration with DevOps methodologies is required.
• Demonstrated expertise in leading AI Centers of Excellence, governing cross-functional teams, evaluating vendor product fit, and implementing bot deployment.
• Deep understanding of healthcare workflows in both outpatient and inpatient settings, coupled with experience in API management strategies, microservices architectures, and infrastructure-as-code approaches.
• Strong technical portfolio management capabilities including version control for AI and automation assets, architectural governance frameworks, and scalability planning across enterprise environments.
• Knowledge of monitoring/alerting systems for automated processes, incident response procedures, and SLA management for critical workflows.
• Ability to evaluate emerging technologies and develop comprehensive technical roadmaps that balance innovation with operational stability while ensuring alignment with organizational objectives.