Length: 2 Days
The Vision 2030 AI Leadership Program (V3ALP) by Tonex is a comprehensive certification course designed to equip leaders with the necessary skills and knowledge to spearhead AI initiatives aligned with Saudi Vision 2030. Participants will delve into topics such as digital transformation, economic diversification, and innovation leadership, gaining practical insights to drive impactful change in their organizations and communities.
Learning Objectives:
- Understand the principles and objectives of Saudi Vision 2030.
- Gain proficiency in leveraging AI technologies for digital transformation.
- Develop strategies for fostering economic diversification through AI initiatives.
- Cultivate leadership skills essential for driving innovation in AI-driven environments.
- Acquire knowledge of best practices and case studies relevant to AI implementation.
- Develop a comprehensive action plan for executing AI initiatives aligned with Vision 2030 goals.
Audience:
- Executives and senior leaders from government agencies.
- Business leaders and entrepreneurs seeking to integrate AI into their operations.
- Technology professionals involved in AI strategy and implementation.
- Policy makers and decision makers shaping the future of industries.
Course Outline:
Module 1: Introduction to Saudi Vision 2030
- Overview of Saudi Vision 2030
- Objectives and Key Initiatives
- Importance of AI in Vision 2030
- Role of Leadership in Driving Vision 2030
- Global Context and Relevance
- Future Outlook and Challenges
Module 2: Digital Transformation
- Foundations of Digital Transformation
- AI Applications in Business Processes
- Data-driven Decision Making
- AI-driven Customer Experience
- Automation and Efficiency
- Ethical and Regulatory Considerations
Module 3: Economic Diversification
- Understanding Economic Diversification
- Identifying Diversification Opportunities
- AI in Emerging Industries
- Fostering Entrepreneurship and Innovation
- Public-Private Partnerships for Economic Growth
- Sustainable Development Goals and Economic Diversification
Module 4: Innovation Leadership
- Leadership in the Age of AI
- Cultivating a Culture of Innovation
- Design Thinking and Human-Centered AI
- Risk Management in AI Innovation
- Leading Cross-functional AI Teams
- Adaptive Leadership in Dynamic Environments
Module 5: Best Practices and Case Studies
- Successful AI Implementation Strategies
- Industry-specific Case Studies
- Lessons Learned from AI Failures
- Ethical and Responsible AI Practices
- Scaling AI Initiatives
- Future Trends in AI Adoption
Module 6: Action Planning
- Assessing Organizational Readiness for AI
- Setting SMART Goals for AI Initiatives
- Stakeholder Engagement and Alignment
- Resource Allocation and Budgeting
- Monitoring and Evaluation Frameworks
- Iterative Improvement and Adaptation
Exam Domains:
- AI Fundamentals
- Ethics and Responsible AI
- AI Strategy and Leadership
- AI Implementation and Deployment
- AI Governance and Regulation
- AI Innovation and Emerging Technologies
- AI Business Cases and ROI Evaluation
Question Types:
- Multiple Choice Questions (MCQs): Assessing understanding of concepts and principles.
- Scenario-based Questions: Presenting real-world situations to evaluate problem-solving skills and decision-making abilities.
- Case Studies: Analyzing cases to demonstrate strategic thinking and application of AI principles.
- Essay Questions: Allowing candidates to elaborate on AI strategies, ethical considerations, and implementation approaches.
Passing Criteria:
- Minimum Score: Candidates must achieve a minimum passing score in each domain to pass the exam.
- Overall Performance: The overall performance is evaluated based on the aggregate score across all domains.
- Completion of All Sections: Completion of all exam sections is mandatory.
- Evaluation of Written Responses: Essay questions and case studies are evaluated based on the depth of analysis, clarity of argument, and adherence to ethical and strategic principles.