Chief Data and AI Officer (CDAIO) Certificate Program

Virtual Orientation: 12:00 - 5:00 p.m. EDT
September 2-4, 2026

Virtual Modules: 4:00 - 9:00 p.m. EDT/EST
(Note: all virtual class dates are Mondays)
September 14, 21 (2026)
October 5, 12, 19 (2026)
November 9, 16 (2026)

Mid-Session: 9:00 - 5:00 p.m. EST (Pittsburgh, PA; virtual option available)
December 8-10, 2026

Virtual Modules: 4:00 - 9:00 p.m. EST
(Note: all virtual class dates are Mondays)
December 14, 2026
January 11, 18, 25 (2027)
February 8, 15, 22 (2027)

Practicum: 9:00 a.m. - 5:00 p.m. EDT (Pittsburgh, PA; virtual option available)
March 23-24, 2027

Virtual Orientation: 12:00 - 5:00 p.m. EST
January 6-8, 2026

Virtual Modules: 4:00 - 9:00 p.m. EST/EDT
(Note: all virtual class dates are Mondays)
January 26, 2026
February 9, 16, 23 (2026)
March 9, 16, 23 (2026)

Mid-Session: 9:00 - 5:00 p.m. EDT (Pittsburgh, PA; virtual option available)
April 7-9, 2026

Virtual Modules: 4:00 - 9:00 p.m. EDT
(Note: all virtual class dates are Mondays)
April 20, 2026
May 4, 11, 18 (2026)
June 1, 15, 22 (2026)

Practicum: 9:00 a.m. - 5:00 p.m. EDT (Pittsburgh, PA; virtual option available)
July 28-29, 2026

The program mid-session and practicum will be held in person at our main campus in Pittsburgh:

Heinz College of Information Systems and Public Policy
Carnegie Mellon University
4800 Forbes Avenue
Pittsburgh, PA 15213

A virtual option will be offered for the program mid-session and practicum; students will not be required to travel to complete the program.

Earning your executive education certificate is just the beginning of a lifelong relationship with CMU; we're here to help you advance your career throughout your professional life. The Heinz College Executive Advantage program is meant for people who always want to be ahead of the curve—those who want to lead the conversation, not just be a part of it.

Executive Advantage was designed with you—C-suite executives and lifelong learners—in mind. In addition to the valuable skills you gain through our executive certificate programs, you now have access to workshops, leadership summits, and conferences.

Instructor:
Dr. David Steier | Distinguished Service Professor, Carnegie Mellon University's Heinz College

This module will set the stage for the program by describing the evolving nature of data and its value to the enterprise and discussing use cases of organizations that have undergone successful data and digital transformations. The module will then outline the core components of an enterprise data management program. This module will also review the necessary components of the data lifecycle management process.Finally, the module will end with a discussion on data quality management.

Instructor:
Krishna Cheriath | VP, Head of Digital, Data, and Analytics, Zoetis

This module will discuss the business case (value realization of data) for enterprise data management, and the foundational importance to digital transformation initiatives, through the development of a mission- aligned, data-driven strategic roadmap. The module will also outline the role of the data executive and their charter to drive strategic decisions for data infrastructure and various technologies, aligning these decisions with the company’s data strategy. Finally, the module will define good data governance, look at the different elements of establishing good data governance, and consider ways to implement an effective data governance agenda.

Instructor:
Doug Laney | Data, Analytics, and AI Strategy Advisor & Author

Organizations are utilizing maturity models to assess their data management gaps and capabilities and compare their progress against industry peers. Becoming data-driven requires a degree of maturity regarding the organization’s data assets, as well as an appreciation of data’s unique properties. Treating data as an actual business asset should go beyond just talking about it as one. Typically, other traditional assets are measured, managed, and monetized with great discipline, using standards, frameworks, specialized roles, and technologies to do so. By aligning the data program with industry best practices, a firm can establish a benchmark from which to develop and grow their program.

Instructor:
Olga Lagunova | Chief Product and Technology Officer, GoTo

As companies seek to gain a competitive advantage through data, analytics, and AI, CDAIOs face increased pressure to provide data infrastructure that enables and accelerates data-driven innovation. CDAIOs are chartered to drive strategic decisions for data infrastructure and technology, aligning these decisions with the broad company's data strategy. To stay competitive, companies must understand and adopt modern trends: leveraging cloud, deploying automation, adopting emerging architectures, implementing best practices, and tooling. This module will provide students with an understanding of the critical technology choices that organizations need to make and prepare them to make these decisions.

Instructor:
Craig Brabec | Former Chief Data and Analytics Officer, Best Buy

This module focuses on the analytic component of Business Intelligence (BI) in the context of its practical application. Participants will have a chance to gain and solidify knowledge of the most important contemporary methods of analytics (from descriptive to prescriptive), to develop understanding of practical applicability, how to formulate analytic tasks in support of business objectives, and how to define successful projects.

Instructor:
Sharad Kumar | Field CTO, Qlik

The Data Operations module is a critical component within an organization's data infrastructure, responsible for managing and optimizing the flow, storage, and accessibility of data throughout its lifecycle. This module encompasses a range of functionalities aimed at ensuring data quality, reliability, and efficiency in processing. Data Operations plays a pivotal role in enabling organizations to harness the full potential of their data assets, driving innovation, efficiency, and competitiveness in today's data-driven landscape.

Instructor:
Doug Laney | Data, Analytics, and AI Strategy Advisor & Author

Organizations have begun looking beyond traditional business income streams, not only due to the pandemic drying them up, but due to the imperative to drive evermore value for their customers, investors and other stakeholders. Moreover, many savvy executives have realized that their company’s greatest asset is not one that’s on the balance sheet, it’s one that is overlooked by current accounting standards: data. The discipline of Infonomics takes you beyond thinking and talking about information as an asset to valuing and treating it as one. This module provides the foundation and methods for quantifying information asset value and tactics for using information as your competitive edge to drive growth. Getting this right is a challenge that chief data officers (CDAIOs) must master for their organizations to survive, let alone thrive in the digital economy. This module exposes leaders to the process of developing and implementing a data monetization strategy and how to apply the unique economics of information.

Instructor:
Mario Faria | Applied Data and Analytics Advisor
Krishna Cheriath | VP, Head of Digital, Data, and Analytics, Zoetis

This module will provide a more in-depth view of the strategy, process, and needed resources for the development of data products to support the growth strategy of the organization. This module provides data leaders with the ability to structure a plan for data product innovation that their workforce can meaningfully accomplish. This module is also focused on the requirement for today’s CDAIOs to develop the business case and budget for data and analytics investments that align with the annual strategic planning process and is supported by key organizational stakeholders.

This module will provide students with an understanding of the latest in data science and machine learning modeling methodologies. Particular attention will be paid to formulating problems to be amenable to data science and machine learning solutions. The goal of the session is to introduce the most common techniques and give a taste of more advanced techniques to help CDAIOs operationalize these practices at scale.

Instructor:
Dr. David Steier | Distinguished Service Professor, Carnegie Mellon University's Heinz College

This module establishes the foundational knowledge necessary for understanding the vast landscape of artificial intelligence by tracing the history and evolution of AI, highlighting pivotal moments and key advancements that have shaped today's AI capabilities. Participants will explore the latest developments in AI, including the rise of generative AI, and discuss the significant impact these technologies are having on various industries.

Instructor:
Dr. Inderpal Bhandari | Global Chief Data Officer (ret), IBM
Krishna Cheriath | VP, Head of Digital, Data, and Analytics Zoetis

This module delves into the strategic implications of AI on business value creation, exploring the economic transformation driven by AI technologies. Participants will understand how AI reshapes business models by enhancing efficiency and effectiveness across operations. By the end of this module, participants will have a clear understanding of how to develop and implement an AI strategy that complements and enhances their overall business strategy, positioning AI as a key driver of competitive advantage. In addition, participants will understand the importance of building a governance structure that not only manages AI risks but also actively cultivates trust between AI systems and the humans who interact with them.

Instructors:
JoAnn Stonier | Data and AI Fellow, former Global Chief Data Officer, Mastercard

This module is an overview of the practical operations of the CDAIO function and will cover how to properly plan, structure, budget, run and obtain organizational “buy-in” for the data and AI office function. The goal of this module is to balance the art and the science of strategic data management and its intersection with business strategy, product development, information technology, and operations. It will address how the CDAIO function needs to balance data innovation with the evolving data and AI risks that need to be managed and how to structure, staff and organize the function.

Instructors:
Chris Stephens | Field CTO - Robotics and Industrial AI, NVIDIA; former Head of Data Ecosystems, Geico

This module bridges the gap between the strategic business functions of the CDAIO and the technical realms managed by the Chief Information Officer (CIO), specific to modern AI-infused IT architecture, essential for supporting advanced analytics and AI capabilities. Participants will emerge from this module with a clear understanding of how to align AI strategies with IT infrastructure, ensuring that their AI initiatives are built on robust, flexible, and scalable architectures.

Instructors:
Dr. Anand Rao | Distinguished Service Professor, Carnegie Mellon University's Heinz College

This module marks the transition from the conceptual phase of data science to the practicalities of enterprise-wide AI application. It underscores the shift in focus from creating accurate models to deploying AI systems that are robust, secure, and operationally efficient. By the end of this module, participants will have a comprehensive understanding of the challenges and best practices associated with deploying and monitoring AI systems at scale within their organizations.

Instructor:
Dr. Beibei Li | Professor of IT and Management, Carnegie Mellon University's Heinz College

As the world rapidly embraces Artificial Intelligence, the potential for both benefit and harm escalate. This module navigates the complexities of responsible AI use. Our focus is on providing a detailed and practical understanding of the key risks and harms traditional and generative AI can pose, the principles guiding ethical use of AI, and the intricacies of how these harms manifest themselves in the AI lifecycle. This module places a strong emphasis on bias, fairness, transparency, safety, security, privacy, and accountability, demystifying these foundational concepts and highlighting their relevance in the end-to-end AI life cycle.

Instructor:
Dr. Anand Rao | Distinguished Service Professor, Carnegie Mellon University's Heinz College

Agentic AI systems represent a fundamental shift in how organizations design, deploy, and govern intelligent technologies. Unlike traditional predictive or generative models, agentic AI introduces continuous autonomy, multi-agent coordination, and dynamic interaction with real-world systems, creating both unprecedented opportunities and new categories of strategic, operational, and ethical risk. This module equips leaders with the conceptual frameworks, leadership strategies, and governance mechanisms required to responsibly lead the adoption of agentic AI at enterprise scale. Participants will explore how agentic systems reshape organizational decision-making, human–AI collaboration, operating models, and accountability structures. Emphasis is placed on translating technical capabilities into business value while ensuring alignment with organizational goals, regulatory expectations, and societal norms.

Instructor:
Dr. David Steier | Distinguished Service Professor, Carnegie Mellon University's Heinz College

This module explores the evolutionary journey from traditional rule-based AI to the cutting-edge realm of Generative AI, offering insights into its development and the plethora of business applications it enables. Upon completing this module, participants will have a thorough understanding of generative AI's trajectory, its potential for enterprise- level application, and the need for responsible deployment to harness its benefits while managing its risks effectively.

Instructors:
Omar Khawaja | VP and Field CISO, Databricks
Lisa Martinelli | VP, Chief Privacy and Data Ethics Officer, Highmark Health

In today's rapidly evolving technological landscape, Artificial Intelligence plays a pivotal role in reshaping industries, automating processes, and enhancing decision-making capabilities. However, with the increasing reliance on AI, the need for robust security measures and rigorous testing processes has become more critical than ever. The Data and AI Cybersecurity and Risk Management module is designed to equip participants with the essential knowledge and skills to ensure the resilience, reliability, and security of AI systems. Also, collecting and sharing information raises opportunities and creates challenges for organizations. Privacy in the corporate arena has undergone a metamorphosis over the last two decades. To understand the evolution of privacy and ethics as integral corporate imperatives, this module also explores their transformation through the lens of a Chief Privacy and Data Ethics Officer.

Instructors:
Allison Sagraves | Data Advisor, Coach, Teacher, Former CDO, M&T Bank
Chris Labash | Associate Professor of Communication and Innovation, Carnegie Mellon University's Heinz College

This module focuses on improving effectiveness as a manager and leader by introducing frameworks for understanding organizations and organizational processes. Today’s business world requires leaders who have a strong sense of empathy, sharp critical-thinking skills, and a diverse view of society. As such, an effective data and AI leader should be able to lead and inspire, foster teamwork, and create a culture which helps them be better managers. Also, telling a great data-driven story can be useful for both stakeholders and your customers and can drive better decision making within an organization. However, turning data into a great story can be an intimidating task that many organizations struggle to accomplish. This module will also review tactics to help facilitate better communications between internal and external company stakeholders regarding data as an enterprise asset.