AI Strategy for Executives

of organizations use AI in at least one business function.

McKinsey, 2024

higher productivity growth in companies most exposed to AI.

PwC, 2026

is the pace of change in the skills required for roles most exposed to AI.

PwC, 2026

of leaders consider AI a strategic priority, yet fewer than 25% feel confident evaluating business cases or managing its risks.

Deloitte, 2024

Understand the strategic relevance of AI and its implications for leadership.

Develop the executive vision and sponsorship required to drive AI transformation.

Distinguish hype from real business value and understand what AI can and cannot do today.

Christina Stathopoulos

Understand the current capabilities, limitations, and strategic implications of generative AI and AI agents.

Assess how these technologies can enhance productivity, decision-making, innovation, and business performance.

Daniel Pereira

Explore a real-world case step by step, from framing an AI opportunity to assessment, implementation, and value creation.

Gain practical exposure to analytical AI through the experience of professionals working directly on the implementation of these solutions.

Daniel Pereira

Identify AI opportunities with the greatest potential to create lasting value.

Prioritize initiatives based on strategic alignment, feasibility, expected impact, and other business drivers.

Map AI applications across industries and analyze their strategic implications.

Christina Stathopoulos

Understand the data and technology capabilities that support successful AI adoption.

Recognize data as a strategic asset and a foundation for scalable, high-impact AI initiatives.

Christina Stathopoulos

Navigate the ethical, regulatory, governance, and risk considerations associated with AI implementation.

Build frameworks that support responsible, trustworthy, and compliant AI adoption.

Christina Stathopoulos

Understand the roles required in an AI-ready organization.

Foster a culture built around data, experimentation, transparency, and continuous learning.

Lead the organizational change required to integrate AI as a sustainable business capability.

Christina Stathopoulos

Debates, structured discussions, and peer exchange challenge assumptions and deepen understanding of AI in a business context.

Work in groups to develop and present strategic recommendations for a real-world case, with feedback from participants and faculty.

Christina Stathopoulos

Leaders who need to define and communicate a credible AI strategy, respond to board expectations, and support investment decisions.

Executives looking to connect technology capabilities with business priorities and create a common language between technical teams and management.

Leaders facing resistance to change, unclear ownership of AI, and the need to assess their teams’ readiness.

Decision-makers who need to distinguish real opportunities from hype and prioritize AI initiatives with the potential to create measurable value.

Professionals responsible for evaluating build, buy, or partner options and estimating returns before committing resources.

Leaders integrating AI into their business models and looking to separate sustainable competitive advantage from passing trends.

of organizations use AI in at least one business function.

McKinsey, 2024

higher productivity growth in companies most exposed to AI.

PwC, 2026

is the pace of change in the skills required for roles most exposed to AI.

PwC, 2026

of leaders consider AI a strategic priority, yet fewer than 25% feel confident evaluating business cases or managing its risks.

Deloitte, 2024

Understand what AI can do today, where its limitations lie, and in which contexts it can generate real value.

Assess how emerging AI capabilities can contribute to productivity, innovation, and decision quality.

Strengthen your ability to collaborate with technical teams without delegating strategic AI decisions.

Identify opportunities and prioritize initiatives based on strategic alignment, feasibility, and expected impact.

Integrate ethics, privacy, regulation, and risk into AI decision-making.

Understand the roles, processes, data, and culture required to turn isolated initiatives into a sustainable organizational capability.