Artificial Intelligence for leadership & decision makers #254015

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

• Articulate AI’s Strategic Value: Define key AI concepts in business terms and articulate a compelling vision for how AI can create value and drive competitive advantage in their industry.

• Evaluate AI Opportunities and Use Cases: Identify and prioritize high-impact AI opportunities that align with core business objectives across functions like operations, marketing, and customer service.

• Lead AI Transformation: Develop a roadmap for building AI literacy, fostering a data-driven culture, and managing organizational change associated with AI adoption.

• Manage Risk and Ethics: Understand and mitigate the key risks of AI implementation, including ethical dilemmas, algorithmic bias, data privacy, and potential reputational damage.

• Make Informed Investment Decisions: Understand the components of AI project cost, evaluate build-vs.-buy decisions, and ask the right questions to assess the viability and ROI of AI initiatives.

• Govern AI Effectively: Establish principles and oversight structures for the responsible and effective use of AI within the organization.

This course is designed for senior decision-makers who set strategy and allocate resources:

• C-Suite Executives: CEOs, CFOs, COOs, CMOs, CIOs, CTOs, and CDOs responsible for setting corporate strategy and driving innovation.

• Heads of Business Units & Division Presidents: Leaders accountable for the P&L and operational performance of a major business segment.

• VPs and Directors: Senior leaders in key functions such as Marketing, Operations, Finance, HR, and Supply Chain.

• Strategy & Innovation Officers: Professionals leading corporate development, digital transformation, and innovation initiatives.

• Entrepreneurs & Business Owners: Founders and owners of companies looking to leverage AI for growth and scalability.

• Senior Project & Program Managers: Leaders tasked with overseeing the execution of major strategic initiatives, including AI adoption.

• 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: Demystifying AI for Strategic Advantage

• AM: The AI Imperative: Beyond the Hype

  • Why AI is a Strategic Business Issue, Not Just a IT Project.

  • Key Concepts Demystified: AI, ML, Deep Learning, Generative AI explained in business terms.

  • The State of Play: How AI is transforming major industries (a cross-industry perspective).

• PM: Identifying AI Opportunities in Your Business

  • Frameworks for spotting AI use cases: Automating processes, enhancing products, improving decision-making.

  • Workshop: “AI Opportunity Sprint” – Brainstorming and prioritizing potential AI applications for your organization.

Day 2: Building an AI-Ready Organization

• AM: The Leadership Playbook for AI Adoption

  • Assessing Your AI Maturity: Where is your organization today?

  • Building AI Literacy and a Data-Driven Culture from the top down.

  • Talent Strategy: Do you hire, reskill, or partner? Understanding key AI roles.

• PM: The Economics of AI: Investment and ROI

  • Understanding the True Cost of AI Projects (data, talent, infrastructure, maintenance).

  • Building a Business Case for AI: Measuring and forecasting value and ROI.

  • Build vs. Buy vs. Partner: Making the right strategic sourcing decision.

Day 3: From Strategy to Execution

• AM: Leading AI Projects to Success

  • The AI Project Lifecycle: What leaders need to know from ideation to deployment.

  • Avoiding Common Pitfalls: Why many AI projects fail and how to prevent it.

  • Case Study: Deep dive into a successful (or failed) corporate AI implementation.

• PM: Data Strategy: The Fuel for AI

  • Why Data is Your Most Important Asset. Assessing data quality and accessibility.

  • Data Governance and Architecture: Questions every leader should ask.

  • Workshop: Evaluating your organization’s data readiness for AI.

Day 4: Managing Risk, Ethics, and Governance

• AM: The Responsible Leader’s Guide to AI Ethics

  • Identifying and Mitigating Algorithmic Bias: A threat to brand and fairness.

  • Privacy, Security, and Regulatory Compliance (GDPR, EU AI Act).

  • Transparency and Explainability: How to trust your AI’s decisions.

• PM: Establishing AI Governance

  • Creating an AI Ethics Board and Principles for your organization.

  • Implementing oversight and accountability frameworks.

  • Group Discussion: Developing a draft AI policy for a real-world scenario.

Day 5: The Future of AI and Your Leadership Legacy

• AM: The Future Landscape: Trends Leaders Must Watch

  • The impact of Generative AI on business and creativity.

  • The Geopolitics of AI: Staying ahead in a competitive global landscape.

  • Fireside Chat: A guest speaker (or case-based discussion) on the future of an AI-driven world.

• PM: Capstone: Your AI Leadership Action Plan

  • Final Exercise: Each participant develops a personalized 90-day AI Strategy and Action Plan for their organization or business unit.

  • Presentation and peer feedback session.

  • Course Wrap-Up: Committing to ongoing learning and leading with confidence.