Artificial intelligence applications for leaders and decision makers #254023

Upon completion of this course, participants will be able to:

• Understand AI Fundamentals: Comprehend key AI concepts, capabilities, and limitations in business contexts

• Identify AI Opportunities: Recognize potential AI applications across various business functions and industries

• Evaluate AI Solutions: Assess AI technologies and vendors for strategic fit and implementation feasibility

• Lead AI Implementation: Develop strategies for successful AI adoption and organizational change management

• Manage AI Risks: Address ethical considerations, bias mitigation, and regulatory compliance issues

• Measure AI ROI: Establish metrics and evaluation frameworks for AI project success

• Build AI Strategy: Create a roadmap for AI integration aligned with organizational goals

This course is designed for senior professionals and decision-makers across various functions:

• C-Suite Executives (CEOs, COOs, CFOs, CTOs, CIOs, CDOs)

• Business Unit Leaders and Department Heads

• Senior Project Managers and Program Directors

• Strategy and Innovation Officers

• Product Development Leaders

• Operations and Supply Chain Executives

• Marketing and Sales Directors

• Financial Services Executives

• Healthcare Administration Leaders

• Government Officials and Policy Makers

• Entrepreneurs and Business Owners

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: AI Foundations for Strategic Decision-Making

• AM: The AI Landscape for Business Leaders

  • Understanding AI, Machine Learning, and Deep Learning

  • Current state of AI capabilities and limitations

  • AI’s impact on various industries and business models

  • Case studies of successful AI implementations

• PM: Identifying AI Opportunities in Your Organization

  • Framework for assessing AI readiness

  • Identifying high-impact AI use cases

  • Prioritizing AI initiatives based on strategic value

  • Workshop: AI opportunity mapping for participant organizations

Day 2: Evaluating and Selecting AI Solutions

• AM: AI Technology Assessment

  • Understanding different AI approaches and technologies

  • Evaluating AI vendors and solutions

  • Build vs. buy vs. partner decisions

  • Technical feasibility assessment

• PM: Business Case Development for AI Projects

  • Calculating ROI for AI initiatives

  • Risk assessment and mitigation strategies

  • Resource planning and budgeting

  • Workshop: Developing a business case for AI implementation

Day 3: Leading AI Implementation and Adoption

• AM: AI Project Management

  • Unique aspects of AI project lifecycle

  • Managing cross-functional AI teams

  • Agile approaches for AI development

  • Measuring progress and success metrics

• PM: Organizational Change Management

  • Building AI literacy across the organization

  • Addressing resistance to AI adoption

  • Upskilling and reskilling strategies

  • Creating an AI-ready culture

Day 4: Ethical AI and Risk Management

• AM: Responsible AI Governance

  • Ethical considerations in AI deployment

  • Bias detection and mitigation strategies

  • Transparency and explainability requirements

  • Regulatory compliance and legal implications

• PM: AI Risk Management Framework

  • Security considerations for AI systems

  • Data privacy and protection

  • Continuity planning for AI systems

  • Monitoring and maintenance strategies

Day 5: Strategic AI Leadership and Implementation

• AM: Developing Your AI Strategy

  • Creating an AI vision and roadmap

  • Aligning AI initiatives with business objectives

  • Resource allocation and investment planning

  • Partner ecosystem development

• PM: Capstone Project and Action Planning

  • Group exercise: Develop comprehensive AI strategy for sample organization

  • Creating personal implementation plans

  • Establishing metrics for success

  • Building peer networks for ongoing support

  • Final Q&A and course wrap-up