Effective AI Oversight for Directors Certificate Program

Instructor:
Dr. Inderpal Bhandari | Board Member – Walgreens Boots Alliance and the AES Corporation; CMU CDAIO Program Faculty Member; Distinguished Executive-in-Residence – CMU Heinz College

Artificial intelligence is rapidly transforming every sector — from financial services and healthcare to manufacturing and government — bringing new opportunities for innovation, efficiency, and growth. Yet alongside these benefits come heightened risks related to privacy, bias, accountability, and unintended consequences. As AI becomes embedded in core business operations and decision-making, boards must play a critical role in ensuring that its use is responsible, ethical, and aligned with the organization's values and risk appetite. This opening module introduces the Effective AI Oversight for Directors Certificate Program, setting the foundation for the strategic and governance-oriented content that follows. The module outlines the structure and learning outcomes of the program’s core topics — from AI strategy alignment and data governance to ethical considerations, risk management, and performance monitoring.

Instructor:
Dr. David Steier | Distinguished Service Professor – CMU Heinz College; CMU CDAIO Program Faculty Member

As data becomes an increasingly strategic asset, effective Enterprise Data Management (EDM) is foundational to digital transformation, AI enablement, and long-term business resilience. This module introduces board members to the evolving nature of data — its types, value, and role in powering intelligent decision-making and innovation. Through real-world examples of successful data and digital transformation initiatives, participants will gain insight into how leading organizations are structuring their data strategies. The module also outlines the key components of an effective EDM program, including governance, architecture, and lifecycle management, with a special emphasis on data quality — a critical enabler for reliable AI outcomes. Designed for senior leaders and non-technical stakeholders, the session offers a high-level yet actionable understanding of the principles, challenges, and strategic levers of enterprise data management.

Instructor:
Krishna Cheriath | CDO – ThermoFisher Scientific; CMU CDAIO Program Faculty Member

As digital transformation reshapes industries, data and artificial intelligence (AI) have become essential drivers of competitive advantage, operational efficiency, and innovation. However, without alignment between AI capabilities, data governance, and overall business strategy, organizations risk fragmentation, ethical missteps, and missed opportunities. This module equips board members with the strategic insight needed to oversee, question, and support the effective integration of data and AI into the organization’s digital transformation journey. Designed for non-technical leaders, the content emphasizes governance, value creation, risk management, and ethical oversight. Participants will gain a high-level understanding of how to align data and AI strategy with long-term organizational goals, ensure responsible AI deployment, and guide their executive teams in building digital resilience.

Instructor:
Craig Brabec | former CDAO – Best Buy; CMU CDAIO Program Faculty Member

In an era where data is a critical asset, the ability to make informed, evidence-based decisions is a defining factor of competitive success. This module helps board members understand how data and business intelligence (BI) analytics can empower better decision-making at both the operational and strategic levels. Designed for non-technical executives, the session demystifies the role of data analytics in identifying trends, measuring performance, forecasting risk, and uncovering growth opportunities. The focus is on what board members need to know to ask the right questions, assess data quality, and hold management accountable for leveraging insights that drive business value. Participants will explore frameworks for interpreting analytics, aligning metrics with strategic goals, and integrating business intelligence into governance and oversight practices.

Instructor:
Dr. David Steier | Distinguished Service Professor – CMU Heinz College; CMU CDAIO Program Faculty Member

This module equips organizational stakeholders with a clear, practical understanding of artificial intelligence (AI) and its near-term impact across business functions. Beginning with an accessible overview of AI technologies — including the transformative advances in generative AI and large language models (LLMs) — participants will gain clarity on AI’s current capabilities and limitations. The session highlights how AI is reshaping work through automation, augmentation, and autonomous task execution, supported by real-world use cases spanning diverse functional areas. It also addresses critical considerations for managing AI initiatives within the enterprise, including talent acquisition, team structuring, and retention. Finally, participants will learn foundational principles for developing a robust enterprise AI strategy that aligns technology adoption with organizational goals and ethical considerations. This module provides board members and senior leaders with the knowledge needed to guide their organizations through the AI journey confidently and responsibly.

Instructor:
Chris Stephens | Field CTO — Groq; CMU CDAIO Program Faculty Member

As organizations compete in a data-driven economy, success increasingly depends on having the right digital and AI infrastructure to support scalable innovation, real-time insights, and operational agility. This module equips board members and senior stakeholders with a strategic understanding of the foundational technologies that underpin data and AI capabilities. Participants will explore the evolution of data platforms and architectures, including data warehouses, lakes, and hubs, and gain insight into how modern infrastructure choices—such as cloud adoption, automation, and platform orchestration—enable enterprise-wide collaboration and data value realization. The session also addresses how to align technology decisions with business goals, governance requirements, and the broader data strategy. This non-technical module provides board members with the contextual knowledge they need to provide effective oversight, support strategic investment decisions, and challenge executive assumptions about infrastructure readiness and capability.

Instructor:
JoAnn Stonier | Fellow of Data and AI — Mastercard; CMU CDAIO Program Faculty Member

In today’s rapidly evolving business landscape, data-driven transformation is essential for accelerating decision-making, enhancing customer value, and sustaining competitive advantage. Central to this transformation is the leadership role responsible for aligning data and AI initiatives with organizational goals. This module provides insights into the critical responsibilities of Data and AI leaders, focusing on how they establish their function, develop effective strategies, and foster a culture that embraces data-driven decision-making across the enterprise. Participants will explore best practices for structuring and resourcing this function, including talent acquisition, skill development, and budget planning. The session also examines the complex dynamics of organizational change management and how culture acts as both a driver and a barrier to successful data and AI adoption. By understanding these key dimensions, board members and senior stakeholders will be better positioned to support and oversee the development of data and AI leadership that drives sustainable business impact.

Instructor:
Dr. Anand Rao | Distinguished Service Professor – CMU Heinz College; CMU CDAIO Program Faculty Member; former Partner and Global Head of AI – PwC

As AI technologies become integral to business operations, the imperative to govern their use responsibly has never been greater. This module provides board members and senior leaders with a deep understanding of the complex landscape of AI risks and the frameworks required to ensure ethical, transparent, and trustworthy AI deployment. Participants will explore foundational principles of responsible AI—including fairness, bias mitigation, transparency, privacy, security, robustness, and reliability—and learn how to translate these ethical imperatives into practical governance measures. Special attention is given to the unique challenges posed by generative AI and large language models (LLMs), as well as emerging regulatory and industry expectations. This session empowers directors to oversee AI governance effectively, ensuring that their organizations not only comply with evolving standards but also build stakeholder trust and sustain long-term value through responsible innovation.

Instructor:
Omar Khawaja | VP and Field CISO of Databricks; CMU CDAIO and CISO Program Faculty Member

In today’s fast-paced technological environment, Artificial Intelligence is transforming industries, streamlining operations, and enhancing strategic decision-making. As organizations increasingly depend on AI, ensuring the security and robustness of these systems is paramount. This module equips board members with the essential knowledge and oversight tools needed to safeguard AI initiatives. Participants will learn how to assess the resilience and reliability of AI systems, understand emerging security risks unique to AI, and oversee the implementation of rigorous testing and validation practices. By fostering a security-first mindset, this session empowers directors to guide their organizations in building trustworthy AI capabilities that protect against vulnerabilities, safeguard sensitive data, and maintain stakeholder confidence in an increasingly complex risk landscape.

Instructor:
Dr. Inderpal Bhandari | Board Member – Walgreens Boots Alliance and the AES Corporation; CMU CDAIO Program Faculty Member; Distinguished Executive-in-Residence – CMU Heinz College

This module begins by reviewing the critical duties and oversight responsibilities of the board in guiding data and AI transformation efforts within the organization. It highlights the dual nature of disruptive data-centric technologies — presenting both significant opportunities for value creation and complex risks that require vigilant governance. Participants will explore the importance of establishing a clear organizational risk appetite—both strategic and operational—to set the tone at the top and align oversight activities accordingly. The module further presents best practices for coordinating board-level governance to ensure that data and AI initiatives are effectively managed, appropriately resourced, and deliver measurable business value. Through this session, board members will gain the insight needed to balance innovation with risk, support prudent investment decisions, and oversee the realization of their organization’s data asset potential.