Adjunct Instructor, MHA Program, Medical Sciences

This course explores how artificial intelligence is reshaping healthcare and redefining leadership during rapid digital transformation. Students examine emerging AI technologies and their clinical, operational, strategic, ethical, workforce, and governance implications. Through case studies, discussions, simulations, and strategic planning activities, students develop the competencies needed to lead responsible, human-centered, and sustainable AI-enabled innovation in healthcare organizations.

Primary Course Topics

• The AI moment in healthcare and implications for leadership and career development
• Foundational AI and machine learning concepts, AI culture, and organizational readiness
• Healthcare AI use cases, strategic value, stakeholder trust, and ethical implementation
• Workforce transformation, reskilling, AI literacy, and the future of healthcare jobs
• Interoperability, data oversight, equity, sustainability, and responsible governance
• A capstone project focused on using AI to improve healthcare

Key Responsibilities of Adjunct Faculty

1. Develop, organize, and upload course content in Blackboard Ultra before the beginning of the six-week session, in alignment with the approved syllabus and program expectations.

2. Deliver an engaging online learning experience using recorded lectures, applied activities, case studies, discussion boards, and other appropriate instructional methods.

3. Interact consistently with students throughout the session, provide timely and substantive feedback, and evaluate all required student work.

4. Assess achievement of course learning outcomes and use effective assessment strategies to support student learning and continuous course improvement.

5. Guide students in analyzing AI applications across clinical, operational, and administrative settings, including ethical, legal, regulatory, equity, workforce, and governance considerations.

6. Mentor students as they develop an actionable strategic roadmap and leadership plan for responsible AI adoption in healthcare.

7. Maintain expectations for graduate-level scholarship, professional communication, academic integrity, appropriate citation, and transparent disclosure of generative AI use.

8. Submit final grades promptly at the conclusion of the session and complete other required academic and administrative responsibilities.

Instructional Expectations

• Course resources must be provided by the instructor, available online, or accessible through the university library system.
• Readings, recordings, discussions, activities, and assignments should align with course and program learning outcomes.
• Instruction should recognize differing learning needs, encourage problem-solving, and support acquisition of practical leadership competencies.
• The course should include meaningful opportunities for students to apply AI concepts to real-world healthcare leadership challenges.
• Student workload should be appropriate for a three-credit graduate course delivered in an accelerated six-week format.

Preferred Qualifications and Experience

• Doctorate or master’s degree in healthcare administration, health sciences, business, informatics, data science, artificial intelligence, or a closely related field.
• Demonstrated knowledge of artificial intelligence and its applications in healthcare delivery, operations, strategy, or administration.
• Healthcare industry and leadership experience, with the ability to connect emerging technologies to organizational decision-making and change management.
• Experience teaching graduate or professional learners; online teaching experience and familiarity with learning management systems are strongly preferred.
• Knowledge of responsible AI, ethics, privacy, data governance, equity, regulatory considerations, workforce readiness, and stakeholder engagement.
• Strong written, verbal, facilitation, and student-mentoring skills.

Course Learning Outcomes

The adjunct instructor will facilitate student achievement of the approved course learning outcomes, including the ability to:

• Explain foundational AI and machine learning concepts and their relevance to healthcare delivery, operations, and strategy.
• Critically assess AI applications to identify strategic value and leadership opportunities.
• Analyze ethical, legal, regulatory, trust, and equity challenges associated with healthcare AI.
• Evaluate organizational AI maturity and readiness for responsible, scalable implementation.
• Apply leadership and change-management frameworks to AI-driven innovation and transformation.
• Develop a strategic roadmap and leadership plan for implementing, evaluating, and sustaining healthcare AI initiatives.

Additional Information

The course is delivered fully online and asynchronously through Blackboard Ultra. Candidates may teach remotely. The selected instructor will collaborate with MHA program leadership to ensure consistency with the approved syllabus, program competencies, academic policies, and expectations for graduate education.