Most organizations have already deployed AI tools. However, there aren’t enough leaders who know how to use these tools strategically.

The Raymond A. Mason School of Business at William & Mary built its MBA in AI for Business Leaders specialization to solve this issue.

This Online MBA program is designed for working professionals who are ready to lead digital transformation and AI initiatives at the highest levels of their organizations. Whether you’re managing a team, running a business unit or advising the C-suite, this specialization gives you the strategic fluency to turn AI from a buzzword into a business advantage.

The curriculum focuses on AI for business leaders, not coders or data scientists. You’ll be equipped with the AI decision-making skills today’s most competitive organizations demand.

The AI for Business Leaders specialization is an optional pathway for students in William & Mary’s nationally recognized Online MBA program.

• AACSB-accredited degree
• 49 credits total
  
  • 8 specialization credits
• Asynchronous online courses
• 1 weekend residency
• No GMAT or GRE required

Graduates of William & Mary Mason’s Online MBA with an AI for Business Leader specialization leave the program ready to lead, not just participate, in the AI transformation of their industries. Here is what you will be positioned to do:

• Identify AI opportunities across business functions, from marketing and operations to finance and human resources, and build the business case for strategic investment
• Lead AI implementation ethically and responsibly, applying governance frameworks that account for bias, transparency and accountability in AI-driven decisions
• Build a data-driven, AI-ready organization by designing the structures, cultures and workflows that allow teams to act on AI-generated insights with confidence
• Manage AI risk and governance at the enterprise level, including regulatory compliance, model interpretability and stakeholder trust
• Drive competitive advantage through AI strategy, translating emerging AI capabilities into market-facing initiatives that differentiate your organization from the competition
• Communicate AI insights to non-technical stakeholders, such as boards, clients and cross-functional teams, with clarity, credibility and strategic purpose

Faculty
AI Specialization | Business Analytics

Professor Rachel Chung has earned national recognition for her work in AI business education—specifically for her ability to make artificial intelligence accessible and actionable for non-technical business professionals. At a time when many AI courses assume a background in data science or programming, Professor Chung builds bridges. Her teaching philosophy centers on the idea that business leaders don’t need to build AI systems; they need to understand them well enough to lead the people and organizations that do.

Her published contributions on AI fundamentals have made her a go-to resource for students and practitioners seeking a clear, jargon-free entry point into AI literacy. Through her courses, students develop the confidence to engage with AI tools, evaluate AI-generated outputs critically and ask the strategic questions that matter most in high-stakes business environments.

Areas of Expertise: AI literacy for business leaders, AI fundamentals, digital transformation, business strategy

Hays T. Watkins Distinguished Professor of Business
AI Specialization | Business Analytics

Professor Monica Tremblay is one of the most respected voices in the field of ethical AI and organizational transformation. Her work sits at the intersection of technology, human judgment and organizational culture, uniquely positioning her to prepare business leaders for the complexities that accompany AI adoption.

Her ongoing research, including collaborative work on enhancing predictive models in high-stakes sectors like the juvenile justice system, reflects her conviction that AI must be grounded in human expertise and ethical judgment. “AI is not a separate discipline,” she noted. “It’s a tool that enhances everything we teach at the business school.”

Professor Tremblay is also a leading advocate for expanding AI accessibility in the classroom. Her machine learning courses are specifically designed to eliminate the technical barriers that have historically excluded non-technical students from data-driven education, enabling all students, regardless of background, to engage meaningfully with AI concepts and contribute to data-driven problem-solving.

Areas of Expertise: Ethical AI, responsible AI deployment, machine learning, business analytics, organizational culture, AI transparency and trustworthiness, data-driven decision-making

CONTEXT: In today’s AI-saturated job market, professional differentiation requires more than a polished résumé. It requires strategic use of the tools shaping how talent is discovered and evaluated.

METHOD: In Professor Dawn Edmiston’s marketing course, students use generative AI tools, including Microsoft Copilot and Perplexity Pro, to enhance their professional presence on LinkedIn. Students craft compelling value statements, brainstorm thought leadership content and analyze industry trends to sharpen their positioning. Importantly, the exercise does not end at output generation. Students are challenged to critically evaluate the ethical implications of AI-assisted content creation and to balance efficiency with authenticity.

OUTCOME: Students leave with both a stronger LinkedIn presence and a nuanced understanding of how AI shapes professional communication and where human judgment must take the lead. This exercise reflects a broader principle: AI fluency and critical thinking are inseparable.

CONTEXT: Persuasive communication and negotiation are among the highest-value skills for any business leader, and they are also among the most difficult to practice in a traditional classroom setting.

METHOD: Professor David Long integrates ChatGPT’s voice interaction tool to create real-time business simulations that challenge students to think on their feet. In one notable exercise built around a Boeing change management case study, students used AI-powered dialogue to explore leadership decisions, cultural challenges and communication strategies under pressure. Students could customize AI responses to simulate different executive stakeholder profiles, sharpening their ability to adapt messaging, manage difficult conversations and refine negotiation tactics in dynamic environments.

OUTCOME: As Professor Long explains, “By integrating AI simulations and interactive role-playing into our coursework, we’re helping students refine their ability to think on their feet, adapt their communication strategies and navigate complex negotiations—skills that are critical in today’s fast-paced business environment.” Students emerge from these exercises with practical, transferable skills for real-world professional interactions.

CONTEXT: Strategic analysis requires students to synthesize complex information, structure coherent arguments and communicate recommendations with precision—skills that AI can support but not replace.

METHOD: Professor Phil Wagner’s Vision 2026 case study integrates generative AI as a learning accelerator, not a shortcut. Students collaborate on real-world business cases aligned with William & Mary’s Vision 2026 pillars—water, democracy, data and jobs—and use AI tools to explore concepts, stress-test arguments and receive iterative feedback on their thinking before finalizing their presentations. The process is deliberate: AI cannot generate graded content, but it serves as a powerful sparring partner for refining analysis and communication.

OUTCOME: Students deliver polished, research-driven presentations that demonstrate both strategic depth and AI literacy. The exercise models how AI can serve as a force multiplier for human analysis, amplifying rigor without replacing the judgment and creativity that define strong business leadership.

CONTEXT: As AI tools become embedded in business operations, students need hands-on experience applying them in contextualized, professionally relevant settings.

METHOD: Professor Jamie Diaz integrates AI classroom applications that give students direct experience with AI-enabled workflows across business functions. Students engage with AI tools in ways that mirror how organizations are deploying them, exploring applications in decision support, content generation, data interpretation and process optimization. The focus is on developing students’ ability to evaluate AI outputs critically and integrate them meaningfully into their work.

OUTCOME: Students develop practical AI fluency that is grounded in a business context, preparing them to step into organizations and immediately contribute to AI-enabled teams and projects. Professor Diaz’s classroom reflects the Mason School of Business’s broader commitment: AI education is experiential, not just theoretical.