Strategic AI Leadership: A Course for Modern Managers

Introduction

The integration of artificial intelligence into business operations is a critical challenge and a significant opportunity for today's leaders. This isn't a technical course for engineers, but a strategic training program designed specifically for managers who need to understand AI's potential, communicate effectively with technical teams, and lead successful AI-driven initiatives. By demystifying the technology and focusing on its practical application, this course provides you with the knowledge to make informed decisions and build a data-driven culture within your organization.

Through case studies, frameworks, and practical exercises, you will learn how to identify where AI can create the most value in your business, from streamlining workflows to discovering new market insights. This program will equip you with the skills to lead your team through the entire AI project lifecycle, manage risks, and ensure that your AI investments translate into a tangible competitive advantage. You will leave with a clear roadmap for leveraging AI to drive innovation and growth.

Duration 5 days

Target Audience This course is designed for managers, executives, team leaders, and business strategists from all industries who are responsible for identifying, evaluating, and implementing technology solutions. No prior technical or coding experience is required.

Objectives

  1. To understand the strategic implications and potential of AI for business.
  2. To identify practical business problems that can be solved with AI.
  3. To learn a structured framework for evaluating AI solutions and vendors.
  4. To communicate effectively with data scientists and AI engineers.
  5. To understand the key stages of the AI project lifecycle from a management perspective.
  6. To lead a team in the adoption and integration of AI tools.
  7. To recognize and address the ethical, privacy, and security challenges of AI.
  8. To build a compelling business case for AI investment and gain stakeholder buy-in.
  9. To analyze real-world case studies of successful and unsuccessful AI implementations.
  10. To develop an actionable AI strategy for your department or organization.

Course Modules

Module 1: The AI Manager's Mindset

  • Shifting from a traditional to an AI-driven business strategy.
  • Understanding AI's role in a competitive landscape.
  • Recognizing AI opportunities across different business functions.
  • The importance of data literacy for non-technical leaders.
  • Leading change and fostering a data-driven culture.

Module 2: AI Fundamentals for Leaders

  • A non-technical overview of core AI concepts.
  • Differentiating between Machine Learning, Deep Learning, and Generative AI.
  • Understanding key AI application areas like Computer Vision and Natural Language Processing.
  • The relationship between AI, data, and analytics.
  • Debunking common myths and misconceptions about AI.

Module 3: AI Opportunity Identification

  • How to identify high-impact, low-risk AI projects.
  • Using a problem-centric approach to AI adoption.
  • Defining clear project goals and key performance indicators (KPIs).
  • Mapping AI solutions to business needs.
  • Brainstorming sessions for AI use cases in your industry.

Module 4: The AI Project Lifecycle (Manager's View)

  • The stages of an AI project: from ideation to deployment.
  • Defining project scope and success metrics.
  • Managing resources, timelines, and budgets.
  • The role of a manager in each stage of the project.
  • An introduction to agile methodologies for AI projects.

Module 5: Data and Infrastructure for AI

  • The critical role of data in AI success.
  • Understanding data quality and data governance.
  • Working with data engineers and IT teams.
  • The basics of cloud computing for AI infrastructure.
  • Privacy and security considerations for data.

Module 6: Building an AI Business Case

  • Quantifying the value and ROI of an AI project.
  • Developing a compelling presentation for executives.
  • Presenting both quantitative and qualitative benefits.
  • Anticipating and addressing stakeholder concerns.
  • Gaining buy-in from leadership and end-users.

Module 7: The Human Element of AI

  • The future of work and human-AI collaboration.
  • Managing employee concerns and training for new roles.
  • Redesigning workflows to integrate AI tools.
  • The importance of change management.
  • Communication strategies for a smooth AI transition.

Module 8: Ethical AI and Risk Management

  • Recognizing and mitigating algorithmic bias.
  • The importance of transparency and fairness in AI systems.
  • Managing data privacy and regulatory compliance.
  • Creating a responsible AI framework for your team.
  • Risk assessment and management for AI projects.

Module 9: AI Vendor and Partner Management

  • The "build vs. buy" decision for AI solutions.
  • How to evaluate and select the right AI vendors.
  • Navigating contracts and service level agreements (SLAs).
  • Best practices for managing outsourced AI projects.
  • Building a strong partnership with a technical team.

Module 10: Case Studies in Applied AI

  • Analysis of successful AI implementations in various industries.
  • Learning from common pitfalls and challenges.
  • Case study discussions on strategy, technology, and management.
  • Identifying key takeaways from real-world examples.
  • Creating your own case study analysis.

Module 11: Generative AI for Managers

  • An overview of large language models and their business applications.
  • Using Generative AI to automate content creation and summarization.
  • Leveraging AI for code generation and internal tool development.
  • The strategic implications of conversational AI.
  • Understanding the future of Generative AI.

Module 12: Building an AI-Ready Team

  • Identifying the skills and roles needed for an AI project.
  • Strategies for recruiting and hiring AI talent.
  • Fostering continuous learning and skill development.
  • The importance of a collaborative, interdisciplinary team.
  • Empowering your team to experiment with AI.

Module 13: Your AI Action Plan

  • Developing a personalized roadmap for AI adoption.
  • Prioritizing short-term vs. long-term projects.
  • Identifying pilot programs and quick wins.
  • Monitoring progress and measuring success.
  • Presenting your final AI strategy to the group for feedback.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

Strategic Ai Leadership: A Course For Modern Managers in Namibia
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