CDAO Chicago
Presentations
Day 1: General Session
Keynote Presentation: Executive Takeaways: What We’d Do Differently Next Time
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Moving beyond pilots and hype to real-world deployment
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Why the most effective AI agents augment human judgment, not replace it
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Trust, not technology, as the main barrier: data quality, hallucinations, and compliance
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Turning agents into measurable business value, not impressive demos
Narayanan Krishnan
Vice President, Digital and Data Technologies, ATHLETICO
Keynote Presentation: AI Agents Unleashed: Why Most Fail and How Some Deliver Real Impact
- Looking back, what is the single decision you would change and why?
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What early signal or risk did you underestimate at the time?
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What would you prioritize in the first 90 days if you were starting again today?
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What advice would you give executives facing the same challenge now?
Jimmy Kozlow
CDO, NORTHERN TRUST
Keynote Presentation: Actian: Why AI Fails without Data Products and Data Contracts
Up to 95% of all AI deployments fail to deliver measurable ROI. Why? And what can enterprise leaders do about it? New global quantitative research from Actian shows a clear pattern: organizations lacking data products and enforceable data contracts are far more likely to fail. Based on survey data from enterprise data leaders, this session reveals what separates scalable AI from perpetual pilots and failed experiments. Attendees will leave with concrete design, governance, and operating practices they can apply immediately to their next AI initiative.
Emma McGrattan
Chief Technology Officer, ACTIAN
Keynote Presentation: Architecting the Data Foundation for AI Execution, Validation, and Continuous Improvement
Agentic AI is transforming enterprise AI from answering questions to executing operational workflows. As a result, real-time, governed business context is becoming the new bottleneck for enterprise AI. In this session, K2view will show why traditional data architectures fall short, and how Business Operational Context becomes the data foundation for AI execution, validation, and continuous improvement. Attendees will learn a practical architecture pattern for decoupling AI agents from data handling, reducing token cost and governance risk, and enabling enterprise-scale agentic AI.
Hod Rotem
Chief Product Evangelist, K2VIEW
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Keynote Presentation: The Missing Control Plane Your AI Needs Before It Scales
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Why scattered AI cost, routing, and governance are symptoms of one architectural gap, not three separate problems
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How intent-and-identity routing cuts token spend without asking anyone to use AI less
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What it takes to govern autonomous agents at the boundary before they reach sensitive data
Anu Jain
Co-founder and CEO, NEXUSONE
Keynote Presentation: Data as a Revenue Driver, Not a Cost Center
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Data enables new revenue streams beyond traditional products
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High-quality data drives smarter, more profitable decisions
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Data-driven products scale with minimal incremental cost
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Strong data capabilities create sustainable competitive advantage
Christine Wallinger
Director Product Management, Data & Analytics, RLI INSURANCE COMPANY
Keynote Presentation: Practical AI for Product Leaders: Turning Data into Customer Value
- Turning data into measurable customer and business value with AI
- Real-world lessons from building AI-powered products
- Scaling AI adoption through governance and actionable frameworks
Anchal Gautam
Digital Product Manager, BLICK ART MATERIALS
Day 2: General Session
Keynote Presentation: From Tools to Teammates: Integrating AI Agents into Data & Analytics
- At what point do AI agents stop being tools and start acting as true teammates in D&A teams?
- How must data and analytics operating models change to effectively integrate AI agents at scale?
- What new skills and roles become critical when humans and AI agents work side by side?
- How do teams maintain trust, accountability, and data governance when AI agents take on more autonomy?
- What early wins should organizations target to prove the value of AI agents in D&A?
Anusha Dwivedula
Director of Product, MORNINGSTAR
Josh Charney
Associate Director, Quantitative Research, Analytics, MORNINGSTAR
Keynote Presentation: The Future-Facing CDAO: Leading with Vision, Velocity, and Data-Driven Impact
- 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
Mir Ali
Senior Director - Data & Analytics, THE HERSHEY COMPANY
Keynote Presentation: From Data Gatekeeper to AI Game-Changer: The CDAO’s New Mandate
- Owning enterprise AI strategy, not just data governance
- Shifting from control and compliance to value and speed
- Redesigning operating models for human + AI collaboration
- Proving business impact while governing AI risk and trust
Tim Turner
Vice President Business Insights & Data Analytics, THRESHOLDS
Keynote Presentation: Intentional Workforce Design in the Age of AI. What and the Why?
- AI is reshaping work faster than annual planning cycles can keep up. This session introduces a methodology for moving workforce planning from reactive headcount forecasting to proactive, intentional workforce design. How?
- We'll walk through the 5S Framework (Signal, Segment, Simulate, Shape, Sustain) — a structured approach for proactively modeling workforce futures and making deliberate "build, buy, borrow, or automate" decisions before they become urgent. So What/Where Is This Going?
- We'll explore how organizations can embed workforce design as a continuous operating practice — not a once-a-year exercise — so that people strategy keeps pace with AI strategy.
Kajal Chokshi
Global Head of Strategic Workforce Planning AI and Automation, MONDELĒZ INTERNATIONAL
Keynote Presentation: Aligning AI and Analytics Initiatives with Real Business Outcomes
- Shifting from experimentation to measurable business impact
- Prioritizing use cases that drive revenue, efficiency, or risk reduction
- Establishing clear KPIs to connect AI initiatives with strategic goals
Tim Riddle
Senior Product Director, Data and Analytics, PREMIER INC.
Shesh Narayan Gupta
Responsible AI, Machine Learning & Data Science Leader, Author, and Researcher
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Keynote Presentation: ROI on AI-Unlocking AI Value
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Defining meaningful AI ROI: Moving beyond cost savings to measure business impact and strategic value.
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From pilots to enterprise value: Key success factors for scaling AI initiatives that deliver measurable outcomes.
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Aligning AI investments with business goals: Prioritizing use cases that drive sustainable growth and competitive advantage.
Jyoti Mishra
Sr. Director Analytics Executive, AMTRAK
Keynote Presentation: Who Authorized the Agent? Governing AI That Acts on Someone's Behalf
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Why agent authorization has become a data-leadership problem, not just a legal one
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The real reason agentic pilots stall before production: sign-off, not model quality
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Designing delegated authority — consent, scope, revocation, and audit — for agents acting on a user's behalf
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What recent regulation signals about the audit trail enterprises will be asked for next outcomes.
Karthik Mahalingam
Secretary, IEEE Chicago
Keynote Presentation: Designing AI-Augmented Enterprise Investigation Systems
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Reimagining enterprise investigations with AI-assisted workflows
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Orchestrating AI agents, enterprise knowledge, and human expertise into a unified decision-support system
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Designing explainable, human-in-the-loop architectures for high-stakes enterprise decisions
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Practical implementation patterns for building trustworthy AI systems that support risk, compliance, and operational decision-making
Santosh Vasudevan
Lead Data Scientist, CATERPILLAR INC.
Keynote Presentation: Turning AI into Business Value: Lessons from Scaling Across the Enterprise
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Key strategies for scaling AI initiatives from pilot projects to enterprise-wide adoption.
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Building the data, governance, and operating model needed to drive sustainable AI success.
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Measuring business impact and demonstrating ROI through real-world AI implementations.
Jubinder Singh
Senior Manager, Corporate Strategy AI, CHARLES SCHWAB