Leading with AI

Dates

Contact us for details

Length of Course

5 days

9 AM-1 PM (ET)

Prerequisites

An undergraduate degree is desirable

Delivery Method

Online

Cost

$1,825 CAD

Cost includes a non-refundable $25 registration fee

Instructor

Dmytro Chumachenko

Dmytro Chumachenko

Associate Professor, National Aerospace University "Kharkiv Aviation Institute"

AFG-2023-cropped-for-web-300x300

Ann Fitz-Gerald

Director, Balsillie School of International Affairs

Course Summary

Leading with AI is an executive-level course designed for leaders across various sectors, functions, and career stages. AI is transforming how organizations create value and stay competitive. It is reshaping workflows, talent needs, and the way decisions are made. This course helps you move from scattered experiments to an AI capability that supports real strategy. It keeps the technology discussion clear and actionable. You will learn how to identify high-impact use cases, test feasibility with a data-driven reality check, and develop a focused 6-12 month roadmap for AI adoption and execution. You will also learn how to set up responsible governance and prepare for real-world AI risks. You leave with a concise “AI Leadership Playbook” that is ready for leadership teams, boards, and partners.

Learning Outcomes

By the end of this course, participants will be able to:

  • Explain how AI changes competition, value creation, and operating models, and distinguish the leadership implications of GenAI, predictive AI, and analytics.
  • Translate organizational goals into a clear AI opportunity statement and decision frame for leadership teams.
  • Select and prioritize AI/GenAI initiatives using structured feasibility-value-risk criteria and data readiness checks.
  • Build a focused 6-12 month AI use-case portfolio that balances quick wins, strategic bets, and required enablers.
  • Make informed build/buy/partner decisions and define the cross-functional operating model needed to deliver AI at scale.
  • Define key AI roles and shape talent and culture for sustained adoption.
  • Design a responsible AI governance approach that covers privacy, safety, bias, explainability, and sector-specific obligations.
  • Lead and evaluate AI incident response at the executive level, including escalation paths, communications, and corrective actions.
  • Define KPI frameworks that measure AI value, adoption, risk, and trust, and communicate progress in board-ready language.
  • Deliver an AI Leadership Playbook and concise roadmap that aligns strategy, capabilities, governance, and measurable outcomes.

Session Breakdown

  • Session 1 - The Leadership Landscape of AI
  • Session 2 - Use-Case Strategy and Portfolio Prioritization
  • Session 3 - Operating Models, Talent, and Investment Decision
  • Session 4 - Responsible AI, Governance, and Risk
  • Session 5 - Leading Transformation and Measuring Value
Human and Robot Hands Shaking, AI Future

Instructor

Dmytro Chumachenko

Dmytro Chumachenko

Associate Professor, National Aerospace University "Kharkiv Aviation Institute"

AFG-2023-cropped-for-web-300x300

Ann Fitz-Gerald

Director, Balsillie School of International Affairs

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