Artificial intelligence (AI) is redefining the conditions for performance, decision-making, and organizational transformation. For executives, the challenge is no longer simply to keep up with its evolution, but to make it a driver of progress in service of their priorities and ambitions.
This AI certification takes a strategic perspective focused on leadership, governance, and value creation. It highlights the key role of senior management in clarifying priorities, targeting the most promising initiatives, defining a clear vision, and creating the conditions needed for successful AI integration within the organization.
Designed specifically for decision-makers, this certification will help you better understand the opportunities and limitations of AI, make informed investment choices, and guide your organization through a transformation that is both strategic and responsible. It also covers essential dimensions such as team readiness, cybersecurity, ethics, law, and digital responsibility, enabling you to anchor AI in a sustainable, controlled, and impactful trajectory.
The successful completion of this program entitles you to a digital certificate. These credentials are trusted, secure, verifiable, and sustainable.
GOALS
This program will enable you to:
- Understand the capabilities, limitations, and success factors of AI in a digital transformation context
- Identify AI value-creation opportunities in operations, offerings, and stakeholder relationships
- Prioritize AI investments and initiatives according to business objectives and organizational maturity
- Develop an AI strategy supported by clear governance, defined roles, and appropriate steering mechanisms
- Prepare teams, skills, and management practices for AI adoption
- Protect the organization by framing AI use in terms of cybersecurity, ethics, law, and digital responsibility
IS THIS FOR YOU?
This training is primarily aimed at executives, managers, senior leaders, and high-potential professionals who are expected to guide their organization’s digital transformation and make decisions on AI investments.
It is particularly relevant for those who need to:
- Identify where AI can create value
- Prioritize a portfolio of initiatives
- Guide strategy and governance
- Prepare teams for change
- Ensure responsible integration of AI within the organization
The program assumes participants have management experience, but no technical prerequisites are required.
SPECIAL FEATURES
- A certification that bridges the gap between understanding AI advancements and the ability to turn them into decisions, priorities, and concrete actions
- A practical roadmap to guide AI integration within your organization
- Privileged access to HEC Montréal’s Institute for Digital Transformation and AI
Successful completion of this program grants a digital certification—a secure, verifiable, authentic, and durable proof of competence.
DAY 1 — WHAT DIFFERENCE DOES AI MAKE?
This first day aims to establish a common language and understand why AI is now a major driver of transformation.
Module 1: AI at the heart of digital transformation
This module explains AI’s role as a technological capability supporting digital transformation and value creation. It lays the foundation for the program’s overarching framework.
- Digital transformation: concepts, drivers, and trajectories
- Digital capabilities and the distinctive role of AI
- Value creation and organizational transformation
- Analytical frameworks for digital transformation
Module 2: AI capabilities
This module aims to establish a shared understanding of AI, the central role of data, and the differences between approaches such as predictive, generative, and agentic AI. It highlights that not all forms of AI serve the same needs or uses.
- Fundamental concepts and AI terminology
- Data, availability, quality, and infrastructure
- Predictive, generative, and agentic capabilities
- Models, platforms, and technological environments
- Strengths, limitations, and use cases of different approaches
DAY 2 — WHERE CAN AI CREATE VALUE?
This day focuses on better targeting investments.
Module 3: AI for transforming internal operations
This module explores AI’s potential to improve internal processes, support employees, and enhance organizational performance.
- Case studies illustrating predictive, generative, and agentic AI capabilities in various organizational contexts
- Process automation and optimization
- Decision support and advanced analytics
- Employee productivity and augmentation
- Applications across functions: finance, HR, operations, IT, etc.
Module 4: AI for transforming offerings, markets, and stakeholder relationships
This module explores AI’s potential to transform customer and partner interactions, enrich products and services, and support organizational growth. Case studies illustrating predictive, generative, and agentic AI capabilities in various business contexts.
- Customer experience and personalization
- Marketing, sales, and pricing
- Supplier and partner relationships
- Innovation in products, services, and interaction models
DAY 3 — HOW TO BUILD AN IMPLEMENT AN AI STRATEGY?
This day equips participants to make the right investment decisions and support AI strategy execution.
Module 5: Building and steering an AI strategy
This module presents the key elements to consider when designing, prioritizing, and implementing an AI strategy.
- Strategic alignment and value creation
- Selection, prioritization, and initiative portfolios
- Build, buy, or partner decisions
- Organizational maturity and execution capability
- Experimentation, scaling, and roadmap
Module 6: Governing AI
This module explains the foundations, challenges, and levers of effective AI governance.
- Governance of AI initiatives and projects
- Governance of data, models, and platforms
- Governance of uses and decisions
- Roles, responsibilities, and governance mechanisms (Legal, ethical, and cybersecurity dimensions are covered in Modules 8 to 10)
DAY 4 — HOW TO PREPARE THE ORGANIZATION FOR AI AND SECURE ITS DEPLOYMENT?
This day focuses on organizational readiness, management practices, and risk control.
Module 7: Preparing teams for AI
This module highlights the human and organizational conditions needed for successful AI projects.
- Evolution of roles and skills
- Transformation leadership
- Human–AI collaboration
- Culture, engagement, and adoption
Module 8: AI and cybersecurity
This module addresses cyber risks associated with AI deployment and use.
- Vulnerabilities and new attack surfaces
- Cyber resilience and business continuity
- Protection of information assets
- Frameworks and cyber risk governance
DAY 5 — HOW TO PROTECT YOUR ORGANIZATION IN THE AGE OF AI?
This day focuses on responsible AI use, including ethical, legal, and digital responsibility considerations.
Module 9: Ethical and legal issues in AI
This module provides a better understanding of ethical and legal issues surrounding AI.
- Ethics, accountability, and transparency
- Legal and regulatory frameworks
- Rights protection and risk management
- Guidelines and best practices
Module 10: AI and digital responsibility
This module addresses the conditions for responsible AI integration in digital services.
- Materiality and environmental impacts of AI
- Environmental assessment of AI systems
- Ecodesign and digital sobriety
- Responsible governance of AI solutions
DAY 6 — HOW TO TAKE ACTION?
This final day consolidates learning, applies it, and opens reflection on future technological and organizational trends.
Module 11: Integrative workshop
This module is entirely dedicated to the final assessment. Individually or in teams, participants work on a real or fictional case and present their action plan.
Module 12: Cross perspectives on the future of AI
This module offers conferences and discussions to explore future developments.
- Leadership in the age of AI agents: how autonomous systems will transform decision-making, organizational structures, and leadership work
- The next waves of AI: evolution of models, multimodal AI, robotics, technological sovereignty, and geopolitical impacts
TRAINING APPROACH
- Case studies
- Workshops (applied data analysis, etc.)
- Lectures
- Discussions between participants and experts
PROGRAM EDUCATIONAL DIRECTOR AND INSTRUCTOR:
Ph. D.
Associate Professor, Department of Information Technologies, and Director of the Sustainable Transition Office, HEC Montréal
INSTRUCTORS:
MSc (Information Technologies), PhD (Information Technologies)
Assistant Professor, Department of Information Technologies, HEC Montréal
MBA, SAP Certified Associate
Senior Faculty Lecturer, Department of Information Technologies, HEC Montréal
MSc (Management - Business Intelligence)
Head of AI Practice, Numea, and Lecturer, HEC Montréal
MSc (Management), PhD (Management)
Associate Professor, Department of Management, HEC Montréal
MSc (Information Technology), PhD (Administration)
Professor, Department of Information Technologies, Director, Institute for Digital Transformation and AI
Presentation
Program
Instructors
GOALS
This program will enable you to:
- Understand the capabilities, limitations, and success factors of AI in a digital transformation context
- Identify AI value-creation opportunities in operations, offerings, and stakeholder relationships
- Prioritize AI investments and initiatives according to business objectives and organizational maturity
- Develop an AI strategy supported by clear governance, defined roles, and appropriate steering mechanisms
- Prepare teams, skills, and management practices for AI adoption
- Protect the organization by framing AI use in terms of cybersecurity, ethics, law, and digital responsibility
IS THIS FOR YOU?
This training is primarily aimed at executives, managers, senior leaders, and high-potential professionals who are expected to guide their organization’s digital transformation and make decisions on AI investments.
It is particularly relevant for those who need to:
- Identify where AI can create value
- Prioritize a portfolio of initiatives
- Guide strategy and governance
- Prepare teams for change
- Ensure responsible integration of AI within the organization
The program assumes participants have management experience, but no technical prerequisites are required.
SPECIAL FEATURES
- A certification that bridges the gap between understanding AI advancements and the ability to turn them into decisions, priorities, and concrete actions
- A practical roadmap to guide AI integration within your organization
- Privileged access to HEC Montréal’s Institute for Digital Transformation and AI
Successful completion of this program grants a digital certification—a secure, verifiable, authentic, and durable proof of competence.
DAY 1 — WHAT DIFFERENCE DOES AI MAKE?
This first day aims to establish a common language and understand why AI is now a major driver of transformation.
Module 1: AI at the heart of digital transformation
This module explains AI’s role as a technological capability supporting digital transformation and value creation. It lays the foundation for the program’s overarching framework.
- Digital transformation: concepts, drivers, and trajectories
- Digital capabilities and the distinctive role of AI
- Value creation and organizational transformation
- Analytical frameworks for digital transformation
Module 2: AI capabilities
This module aims to establish a shared understanding of AI, the central role of data, and the differences between approaches such as predictive, generative, and agentic AI. It highlights that not all forms of AI serve the same needs or uses.
- Fundamental concepts and AI terminology
- Data, availability, quality, and infrastructure
- Predictive, generative, and agentic capabilities
- Models, platforms, and technological environments
- Strengths, limitations, and use cases of different approaches
DAY 2 — WHERE CAN AI CREATE VALUE?
This day focuses on better targeting investments.
Module 3: AI for transforming internal operations
This module explores AI’s potential to improve internal processes, support employees, and enhance organizational performance.
- Case studies illustrating predictive, generative, and agentic AI capabilities in various organizational contexts
- Process automation and optimization
- Decision support and advanced analytics
- Employee productivity and augmentation
- Applications across functions: finance, HR, operations, IT, etc.
Module 4: AI for transforming offerings, markets, and stakeholder relationships
This module explores AI’s potential to transform customer and partner interactions, enrich products and services, and support organizational growth. Case studies illustrating predictive, generative, and agentic AI capabilities in various business contexts.
- Customer experience and personalization
- Marketing, sales, and pricing
- Supplier and partner relationships
- Innovation in products, services, and interaction models
DAY 3 — HOW TO BUILD AN IMPLEMENT AN AI STRATEGY?
This day equips participants to make the right investment decisions and support AI strategy execution.
Module 5: Building and steering an AI strategy
This module presents the key elements to consider when designing, prioritizing, and implementing an AI strategy.
- Strategic alignment and value creation
- Selection, prioritization, and initiative portfolios
- Build, buy, or partner decisions
- Organizational maturity and execution capability
- Experimentation, scaling, and roadmap
Module 6: Governing AI
This module explains the foundations, challenges, and levers of effective AI governance.
- Governance of AI initiatives and projects
- Governance of data, models, and platforms
- Governance of uses and decisions
- Roles, responsibilities, and governance mechanisms (Legal, ethical, and cybersecurity dimensions are covered in Modules 8 to 10)
DAY 4 — HOW TO PREPARE THE ORGANIZATION FOR AI AND SECURE ITS DEPLOYMENT?
This day focuses on organizational readiness, management practices, and risk control.
Module 7: Preparing teams for AI
This module highlights the human and organizational conditions needed for successful AI projects.
- Evolution of roles and skills
- Transformation leadership
- Human–AI collaboration
- Culture, engagement, and adoption
Module 8: AI and cybersecurity
This module addresses cyber risks associated with AI deployment and use.
- Vulnerabilities and new attack surfaces
- Cyber resilience and business continuity
- Protection of information assets
- Frameworks and cyber risk governance
DAY 5 — HOW TO PROTECT YOUR ORGANIZATION IN THE AGE OF AI?
This day focuses on responsible AI use, including ethical, legal, and digital responsibility considerations.
Module 9: Ethical and legal issues in AI
This module provides a better understanding of ethical and legal issues surrounding AI.
- Ethics, accountability, and transparency
- Legal and regulatory frameworks
- Rights protection and risk management
- Guidelines and best practices
Module 10: AI and digital responsibility
This module addresses the conditions for responsible AI integration in digital services.
- Materiality and environmental impacts of AI
- Environmental assessment of AI systems
- Ecodesign and digital sobriety
- Responsible governance of AI solutions
DAY 6 — HOW TO TAKE ACTION?
This final day consolidates learning, applies it, and opens reflection on future technological and organizational trends.
Module 11: Integrative workshop
This module is entirely dedicated to the final assessment. Individually or in teams, participants work on a real or fictional case and present their action plan.
Module 12: Cross perspectives on the future of AI
This module offers conferences and discussions to explore future developments.
- Leadership in the age of AI agents: how autonomous systems will transform decision-making, organizational structures, and leadership work
- The next waves of AI: evolution of models, multimodal AI, robotics, technological sovereignty, and geopolitical impacts
TRAINING APPROACH
- Case studies
- Workshops (applied data analysis, etc.)
- Lectures
- Discussions between participants and experts
PROGRAM EDUCATIONAL DIRECTOR AND INSTRUCTOR:
Ph. D.
Associate Professor, Department of Information Technologies, and Director of the Sustainable Transition Office, HEC Montréal
INSTRUCTORS:
MSc (Information Technologies), PhD (Information Technologies)
Assistant Professor, Department of Information Technologies, HEC Montréal
MBA, SAP Certified Associate
Senior Faculty Lecturer, Department of Information Technologies, HEC Montréal
MSc (Management - Business Intelligence)
Head of AI Practice, Numea, and Lecturer, HEC Montréal
MSc (Management), PhD (Management)
Associate Professor, Department of Management, HEC Montréal
MSc (Information Technology), PhD (Administration)
Professor, Department of Information Technologies, Director, Institute for Digital Transformation and AI