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Artificial Intelligence (AI) Strategy

Course Summary

The Arificial Intelligence (AI) Strategy course provides the participants with a foundation for building a successful AI program within the enterprise. Participants will be introduced to key elements that the role performs, what a strategy should entail and how to implement an AI plan. The course concludes with an understanding of tasks and characteristics needed to lead a successful AI program.

Gain an understanding of key elements needed for building and leading an enterprise AI strategy.
Anyone interested in aspiring to an AI strategy role.
Data Scientist | Data Engineer | Business Leader
Skill level
Basic understanding of core AI technologies, data, and business process
3 days
Related technologies
AI/ML | Agile | Database Tools


Learning objectives
  • Identify the core requirements and tools needed for building an AI strategy.
  • Understand the importance of data when building an AI strategy.
  • Be able to construct key elements for implementing a successful strategy.
  • Develop a change agent mentality for building effective teams and leading an AI prgoram cross-functionally within the enterprise.

What you'll learn:

In this course, you'll learn:
  • Defining the Role of an AI Strategist
    • Introduction to AI Strategy
      • What is an AI Strategy?
      • Integrating AI Strategy with the Enterprise
    • Defining the Role
      • Key Responsibilities for an AI Strategist
      • Core Foundational Skills
    • AI Technologies
      • Core Concepts
      • Tools and Platforms
    • Business and Industry Applications
    • Data Strategy and Management
      • Importance
      • Types: structured, unstructured
    • Data Collection and Cleansing
    • Data Governance
      • Privacy/security
      • Regulatory compliance
      • Ethics in AI
  • Building a Successful AI Program
    •  Developing an AI strategy
      • Assessing organizational readiness
      • Setting AI goals and objectives
        • Aligning to business objectives
        • Defining measurable outcomes
      • AI Roadmap
        • Short/long term goals
        • Milestones/deliverab
      •  Resources
        • Budgeting
        • Talent – Hiring | Training | Building a Team
        • Risk/mitigation management
    • Implementing an AI Solution
      • Understanding Agile to manage AI projects
      • Prototyping and testing
      • Deployment and scaling
    • Monitoring an AI project
      •  Performance metrics and KPIs
      • Tracking performance
      • Continuous improvement
  • Leading an AI Program 
    • Being a Change Agent
    • Building and Leading Teams
    • Ethics and social impact
      • AI principles
        • Fairness, accountability, transparency
      • Mitigating Bias
      • Understanding potential societal impact
        • Job displacement
        • Job creation
    • Effective communication
      • Creating an AI culture
      • Working with the executive team
        • Communicating strategy and alignment to business
        • Building buy-in and stakeholder support
    •  Leading teams

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