Explain AI and machine-learning capabilities in clear business language and challenge unrealistic claims.
Lead AI withclarity, evidence, and accountability.
AI and Data Management for Executives is a simulation-first diploma for executives who must turn AI possibility into responsible organizational value.
Created and taught by Georges Bachaalany. Delivered through the Lebanese American University Academy of Continuing Education and shaped through four completed cohorts.
- Taught
- 60h
- Capstone
- 40h
- Total
- 100h
- Cohorts completed
- 4
Five 12-hour executive modules + one 40-hour applied capstone = one integrated 100-hour learning journey.
Not AI awareness. AI leadership.
Participants build the judgment to ask better questions, challenge weak assumptions, mobilize the organization, and govern what happens after a model reaches the real world.
Identify, prioritize, and govern AI opportunities that align with organizational strategy and operating realities.
Lead responsible AI adoption across data, people, process, technology, risk, and change management.
Design and defend an evidence-based AI initiative through a 40-hour executive capstone practicum.
Five cores. Twenty executive sessions. One connected story.
Fundamentals of AI and Machine Learning
Build the executive vocabulary and judgment required to evaluate AI, machine learning, deep learning, generative AI, and agentic systems.
Organizational Management with AI
Lead the organizational shift created by AI across people, processes, decision rights, culture, operating models, and human accountability.
Formulate, Implement and Assess AI Solutions
Translate business problems into testable AI solutions through data readiness, feature thinking, prototyping, validation, automation, and executive evaluation.
Ethics, Privacy and Legal AI
Convert ethical principles, privacy duties, security requirements, and the EU AI Act into practical governance decisions.
Blending AI, Data and Business Strategy
Connect AI ambition to enterprise strategy, data advantage, use-case portfolios, operating capabilities, investment logic, and measurable outcomes.
The capstone is the integration engine.
Apply the diploma to a real or realistic organizational challenge and defend an evidence-based AI strategy roadmap.
A final portfolio and executive defense demonstrating readiness to lead an AI initiative.
Opportunity framing and concept outline
Problem, stakeholders, baseline, strategic relevance, value hypothesis, and scope.
Data, feasibility, and responsible AI assessment
Data readiness, solution options, risks, legal classification, controls, and accountability.
Solution design, prototype, and validation
Workflow, prototype, evaluation evidence, failure analysis, user feedback, and iteration.
Operating model, adoption, and value roadmap
Ownership, capabilities, change, investment, sequencing, metrics, and scale criteria.
Executive defense and final portfolio
Evidence synthesis, executive narrative, decision request, limitations, and next steps.
Built for the room executives actually work in.
Executive-first
Technical depth is translated into decisions, operating implications, and strategic trade-offs.
Simulation-first
Participants practice under pressure using cases, labs, games, and realistic organizational dilemmas.
Evidence-led
Every module ends with a practical artifact that can survive scrutiny outside the classroom.
Responsibility built in
Ethics, privacy, security, law, and human accountability shape the solution from the start.
Georges Bachaalany
Four cohorts completed. A new cohort begins with a stronger, centralized learning experience.
Leave able to lead the next AI decision.
The diploma centralizes the learning path, simulations, executive toolkits, assignments, feedback, and capstone evidence in one LMS journey—without losing the energy of the live classroom.