CDAO Fall Day 2 schedule

•    What are the biggest data management challenges that slow down digital transformation, and how can they be overcome?
•    How can organizations balance data quality, governance, and scalability to accelerate digital initiatives?
•    What role do AI and automation play in enhancing data management for a seamless digital transformation?
•    How can businesses effectively measure the impact of their data management strategies on digital growth?

Panelists:
Venkat Achanta, Chief Technology Data and Analytics Officer, TransUnion
Rafique Awan, VP Director, Information & Solution Architecture, MFS INVESTMENT MANAGEMENT
Randall Gordon, Head of Data Governance, CROSS RIVER

•    How future-focused CDAOs are aligning data strategy with long-term business goals, customer-centric innovation, and emerging technologies like GenAI
•    Building agile data organizations that can move fast—balancing governance with experimentation, and enabling real-time, high-impact decisions
•    Translating data investments into tangible business outcomes by embedding analytics into core operations, managing risk, and demonstrating value to the C-suite

•    Solving complex data challenges with a unified, scalable platform that balances governance and agility
•    Enabling AI-powered collaboration across business and technical teams to accelerate innovation
•    Real-world applications of AI and machine learning in modern data management and decision-making
•    Building resilient, future-ready data ecosystems that support continuous learning and adaptability
•    Lessons from TransUnion’s journey in adopting a platform-first approach to AI transformation

•    How to support the transition from decision support (charts and graphs) to decision automation (models) 
•    Managing accountability for the Amplified Value and Amplified Risk of AI (AI Governance) 
•    Scaling AI despite unprecedented operational complexity (AI Change Management) 
•    How to embrace the CDO/CDAO responsibility as the Enterprise AI leader (AI Portfolio Management) 

Panelists:
Sam Marks, Director of Business Strategy & Analytics, BOSTON BRUINS & TD GARDEN
Frederique De Letter, Head of Data Analytics & AI, PLANTE MORAN

•    How do you know when your organization is ready to move beyond basic analytics?
•    What’s needed to position analytics as a core business driver, not just a support tool?
•    How do you balance innovation and governance as analytics capabilities grow?
•    What are the main blockers to analytics maturity—and how have you overcome them?

Panelists:
Rita Fuller, Corporate VP Center for Data Science and Artificial Intelligence, NEW YORK LIFE INSURANCE COMPANY
Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING

•    How to align analytics KPIs with broader business goals to track meaningful impact
•    Balancing financial outcomes (e.g., cost savings, revenue growth) with intangible benefits like improved decision-making and customer experience
•    Balancing financial outcomes (e.g., cost savings, revenue growth) with intangible benefits like improved decision-making and customer experience
•    Balancing financial outcomes (e.g., cost savings, revenue growth) with intangible benefits like improved decision-making and customer experience

Sadashiv K Vaasista, Senior Director, Analytics, HONEYWELL
Kevin Kramer, Former SVP, Data Science & Analytics, RECOVERY CENTERS OF AMERICA

•    What are the foundational elements needed to successfully scale data and analytics in support of AI initiatives?
•    How can organizations strike the right balance between speed, scalability, and governance when building AI-ready data architectures?
•    What lessons have you learned from scaling AI across the enterprise, and what would you do differently in hindsight?

•    How executive support and consistent messaging shape organizational mindset around data
•    Translating high-level data goals into practical behaviors, tools, and workflows
•    Equipping employees with the right data literacy and tools to make informed decisions at every level
•    Using success stories and feedback loops to reinforce a culture of data use and continuous improvement

Panelists:
Thomas Shola, Former Chief Risk Information & Privacy Officer NORTHERN BANK
Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING

•    Strategies to generate revenue from data, such as through data products, services, insights, or a modern data- and analytics platform  
•    How a modern data infrastructure and technologies supports the business strategy  
•    Strategies and experience with fostering a culture where data is valued and used effectively by all employees 

•    Developing policies for data quality, security, and privacy 
•    Designing processes for data collection, storage, and management 
•    Best practices for data integration and interoperability 

•    How can data and AI leaders ensure ethical and responsible AI deployment while still driving innovation?
•    What are some real-world examples where AI has been used to generate measurable social or environmental impact in financial services?
•    How can organizations empower their data teams to prioritize “AI for Good” initiatives alongside business objectives?
•    What frameworks or partnerships are essential to scaling AI solutions that serve the greater good across industries?

 

•    Defining what constitutes AI-ready data and why it is crucial for achieving successful AI outcomes
•    How should you do this, and what are others doing?
•    Exploring how clients and vendors are currently preparing their data for AI
•    Best practices and recommendations for getting data AI-ready

 

•    Pre ChatGPT: Natural Language Understanding (NLU) driven architectures and why they were successful
•    ChatGPT: Advent of large language models and their impact on conversational AI design, development, and deployment. Do we abandon the old in pursuit of the new?
•    Post ChatGPT: How do enterprise conversational AI systems evolve to meet existing and future challenges. What are some good design principles to keep in mind while building for the future?

 

PANEL DISCUSSION: Driving Efficiency and Innovation: Data Quality Management: Ensuring Accuracy, Consistency, and Reliability
•    Techniques for assessing and improving data quality.
•    Common data quality challenges and how to address them.
•    Tools and technologies for monitoring and maintaining data quality
Eric Higgins, Vice President, Global Online Data Science, THE ESTÉE LAUDER COMPANIES INC.
Joe Delpercio, Director, Analytic Services, ZEUS INDUSTRIAL PRODUCTS
Bappaditya Roy, Chief Cloud Architect, THE TJX COMPANIES, INC

•    Why being slow to adopt AI can hinder a company’s ability to remain competitive in today’s rapidly evolving business landscape
•    Examples of AI tools and strategies that are revolutionizing processes, improving decision-making, and enhancing overall business agility
•    Addressing challenges like resistance to change, skill gaps, and the need for cross-departmental collaboration to successfully implement AI

Panelists:
Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING
Frederique De Letter, Head of Data Analytics & AI, PLANTE MORAN
Andrew Patricio, Chief Data and AI Officer, UNIDOSUS