CDAO Washington D.C. | Enterprise Data & AI schedule

During this 5-minute networking session, the aim of the game is to go and meet two people you don't already know. 

• Where decisions really happen and why data still is not there
• Why AI sits outside live workflows
• What leaders changed to influence earlier and closer to the point of action
• What to stop doing if you want decisions to shift
• How data gets embedded into actual business action

Moderator: Priyo Chatterjee, Chief Analytics Officer - Excelsior University

Jitin K. Singhal, Senior Director - Portfolio Analytics and Credit Strategy – Sallie Mae

Trevor Teason, Head of the Talent Intelligence & Innovation Lab -Capital One

Marcos Oliveira, Technology & Digital Senior Manager –Reckitt

Zoe Hsu, Data Scientist- Lasa Health

An interactive session where attendees put their questions directly to an experts on AI ethics, privacy, governance, and regulation. Designed to give practical, real-world answers on operating responsibly under growing scrutiny.

Focus Areas: AI ethics, data privacy, regulatory challenges.

Navin Kumar, Director, Data Engineering and AI Risk – CITI

Harish Vundavalli, Senior Information Technology Architect - Strategic Education

Dr. Andrew Omidvar, Vice President Government – Philips

AI is expected to move faster, deliver value sooner and work across the business. The catch? It wants access to your most valuable data.

Join Kaycee Lai, VP of AI at Everpure, to explore how organizations can move beyond experimentation and scale AI across the enterprise—building a modern data foundation that accelerates time to value, supports business agility and keeps production AI secure and adaptable, without exposing sensitive data to model training.

Challenge: 
Melt (dropping out of course registration before term start) rates have been historically high 

Approach: 
Leverage StIR (Student Intervention Recommender), a proprietary AI platform we have developed, to mitigate the impact 

Work closely with Partners to make sure that deployment is seamless and effective 

Results: 
After deployment of Machine Learning Module, our Melt rates have seen historic lows for 6 consecutive terms 

What Still Slows Delivery When the Team and Tools Are Already There

• Where delivery stalls between priorities, dependencies, and decision rights
• Why adding AI into the mix often creates more noise, not more speed
• How leaders decide what capability to build, buy, or drop
• When vendors help and when they create more complexity
• What operating discipline improves time to value

Moderator: Abhinav Shankar, Global Head – Reporting and Analytics – Tradeweb

Vaidehi Rao, Director of Enterprise Data Program – Capital One

Marcos Oliveira, Technology & Digital Senior Manager –Reckitt

Sumahitha Vadnala, Director – Capital One

Elina Abel, Head of Transformation – T. Rower Price

• How we identified target sales behaviors (internal/external research)
• Turning those into agent experiences (prompts and software)
• Evaluating them for legal compliance and experience (LLM judges, HITL)
• Confidently measuring incrementality (fastest way to statistical significance)
• Result: i.e., Case study drove X.X% engagement, link to sales

• Where data quality breaks across ownership, pipelines, and definitions
• Why no one owns trust end-to-end
• How poor data quietly kills adoption and confidence
• What the business cost really looks like
• What leaders should fix first

Abhinav Shankar, Global Head – Reporting and Analytics - Tradeweb

Chetan Desai, Head of Data Governance and Operations – Guardian Life

Yunlong (Mark) Wang, Director, AI Science -IQVIA

• What happens when AI and data decisions go wrong
• Who is accountable when outcomes fail
• How leaders think about risk versus speed
• Where liability sits across business, risk, and data leadership
• How organisations protect the business and themselves

Brandy O'Shields, Sr Manager, Enterprise Data Governance – PayPal

Navin Kumar, Director, Data Engineering and AI Risk – CITI 

 Subha Madhavan, Vice President & Head of AI/ML & Digital Sciences, Global Product Development – Pfizer  

• Hiring for a landscape changing faster than job descriptions can keep up
• Retaining strong people when tools, priorities, and expectations keep shifting
• How leaders are redesigning teams around data, analytics, ML, and GenAI
• Whether AI is reducing headcount pressure or simply changing where talent is needed
• How leaders keep teams motivated when the market narrative is “AI can do this now”

Trevor Teason, Head of the Talent Intelligence & Innovation Lab -Capital One

Jitin K. Singhal, Senior Director - Portfolio Analytics and Credit Strategy – Sallie Mae

Sean Lensborn, Chief Technology Officer –ZAIS Group

 Senthil Kumar, Senior Director, Digital Core (Cloud Platforms & Infrasturcture) - CSL  

The pilot looked great. Then it met messy data, legacy systems, security reviews, unclear ownership and the people who have to use it.

Join Kaycee Lai, VP of AI at Everpure, and a small group of technology leaders for an honest conversation about what it really takes to move AI into production.We’ll get into where projects tend to stall, what’s working, and how teams are turning early momentum into measurable business value.

• Understand how the attack surface changes when AI moves beyond prompts and outputs to using memory, tools, APIs and enterprise systems.
• Explore the OWASP Top 10 risks, including goal hijacking, tool misuse, privilege abuse, supply-chain vulnerabilities, code execution and memory poisoning.
• Apply Zero Trust across agent identities, authorisation, data, tools, APIs and agent-to-agent interactions.
• Use least privilege, runtime policies, human approvals and agent containment to scale securely without slowing innovation.

• How CDOs can effectively partner with Boards to secure AI investment and align on value realization, not just experimentation
• Practical governance models that balance innovation with risk oversight, including what Boards expect from data leaders
• The evolving CDO-to-Board pathway. What it takes to influence, educate, and build long-term trust at the executive level
• Lessons from the field. Insights from a study of 150+ CDOs and Board directors on what is working in large, complex organizations

Dr. Elena Alikhachkina, Board Director, NACD | Author, “AI Oversight”

Subha Madhavan, Vice President & Head of AI/ML & Digital Sciences, Global Product Development - Pfizer

Deploying autonomous agents inside an alternative asset manager, and what a year of production taught us about trust

• Why the model is the most swappable part of an agent system, and what survives when you replace it
• Where guardrails fail in practice: what happens to safety instructions written into prompts once context gets compacted, and why the fix has to live in code
• Building on proprietary data that never leaves the perimeter, and what changes when the agent's output has to withstand review rather than impress a demo audience
• What we measure now that we didn't measure a year ago, and why observed behavior beats declared capability every time

• • What works across centralised, federated, and hybrid models
  • Where ownership breaks across data, models, and decisions
  • Why duplication and friction keep happening
  • How decision rights are defined, enforced, or avoided
  • What leaders are redesigning right now

Navin Kumar, Director, Data Engineering and AI Risk – CITI

Harish Vundavalli, Senior Information Technology Architect - Strategic Education

Sumahitha Vadnala, Director – Capital One

Shaurya Tripathi, Senior Data Scientist - Munich Re

Babu Thomas, Associate Director, Product Management - Verizon

Alejandro Zarate, Chief Data & AI Officer –Santander

Harish Vundavalli, Senior Information Technology Architect - Strategic Education

 

• Where governance slows or blocks delivery in practice
• Where teams bypass controls to get things done
• How leaders balance speed against risk
• What gets enforced versus what only exists on paper
• How organisations operate under growing scrutiny without freezing progress

Abhinav Shankar, Global Head – Reporting and Analytics – Tradeweb

Michael Stefkovich, Data Science Manager - CarMax

• How AI urgency is changing internal power dynamics across data, tech, risk, and the business
• Where good work gets blocked internally even when the case is clear
• Why alignment breaks across business, tech, risk, and operations
• How leaders build influence without formal control
• What resistance looks like at senior level

Dr. Andrew Omidvar, Vice President Government – Philips

Amanda Bryce, Retired CIO for the Civil Rights Division - U.S. Department of Justice

Zoe Hsu, Data Scientist- Lasa Health

Dr. Elena Alikhachkina, Board Director, NACD | Author, “AI Oversight”

 Go behind the scenes as Reckitt reveals how it collaborated with a major retail partner to deploy AI-powered insights directly in stores. How AI guided specific shelf-level actions and the lift that followed.  

• How the data and AI ecosystem has changed over the last 3–5 years
• Which categories are consolidating, blurring, or becoming harder to separate
• What leaders are still buying, what they are rationalising, and what they regret
• How GenAI changed vendor strategy, budgets, and internal expectations
• What capabilities now matter more than shiny tooling

Dr. Elena Alikhachkina, Board Director, NACD | Author, “AI Oversight”

Daniel Chen, Senior Data Scientist -The Hartford