CDAO New York - Agenda

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8:00 AM

Registration & Networking Breakfast in the Exhibition Area
08:45 AM

Chairperson Opening Remarks & Icebreaker
09:00 AM

OPENING PANEL: Blueprint for the Autonomous Enterprise – Mapping Data Strategy and AI Investment for the Future
- Designing an actionable roadmap toward autonomy, grounded in data maturity rather than experimentation.
- Prioritising AI investments that deliver measurable operational and financial impact under increasing board and market scrutiny.
- Aligning CDAO, CAIO, and Engineering into a single execution engine, breaking down silos that slow scale.
- Clarifying what “autonomy” realistically looks like in the next 3–5 years — and what must be built now.
09:40 AM

KEYNOTE: Execution Debt in the AI Enterprise - How to Make Data & AI Programs Work Past Year One?
- How complexity, handoffs, and misaligned incentives accumulate over time?
- What early decisions silently constrain scale later?
- Signals leaders should watch for before progress stalls.
- How leading organizations reset execution without re-platforming.
10:10 AM

KEYNOTE: Autonomous AI and Data Readiness: What Enterprises Must Fix Now for a Long-Term Advantage
- The core data and architecture gaps blocking enterprises from adopting autonomous intelligence.
- Upgrading governance, lineage and observability to enable safe, scalable autonomy.
- How to future-proof data foundations against rapidly evolving AI capabilities?
- Practical readiness milestones that correlate with long-term competitive advantage.
10:40 AM

Mid-Morning Coffee Break & Networking in Exhibition Area
TRACK A: Enterprise Data Strategy for AI
11:10 AM

DISCUSSION GROUP: Understanding Trust Signals in Enterprise Data Strategy for AI Readiness
- Identifying the trust indicators that reliably predict AI performance and adoption.
- Foundational capabilities to prioritise before scaling AI.
- How to map data strategy to enterprise-wide transformation goals?
- How to avoid common traps that slow AI maturity despite strong investment?
12:00 PM

ROUNDTABLE A: Can I Trust My Data? Implementing Trust Frameworks Across Regulated Industries
12:00 PM

ROUNDTABLE B: Who Decides? Establishing Clear Decision Authority Across the AI Lifecycle
TRACK B: Executional Excellence
11:10 AM

DISCUSSION GROUP: Designing the AI Operating Model for Maximum Organizational Impact
- Selecting the right structure for analytics, ML, LLM, product and engineering teams.
- Funding and prioritisation models that accelerate delivery.
- Talent strategy for building multidisciplinary, product-focused AI teams.
- How do leaders ensure accountability and speed without over-centralisation?
12:00 PM

ROUNDTABLE C: Executive Playbook for Industrializing AI and Driving Enterprise-Wide Adoption
- Frameworks for progressing from POC → production → enterprise adoption.
- Why AI initiatives stall—and how to unblock value delivery?
- Adoption accelerators: change management, incentives and productization.
- Tips on building repeatable systems for continuous AI deployment.
12:40 PM

Lunch and Networking Break in the Exhibition Area
TRACK A: Enterprise Data Strategy for AI
1:40 PM

TRACK KEYNOTE: FinOps, Efficiency and Value Realization in the AI Enterprise
- How executives apply FinOps to quantify the ROI of data and AI initiatives.
- Creating financial guardrails for AI experimentation and scaling.
- Cost-to-value visibility: aligning cloud, data, and AI investments to outcomes.
- Building operating rhythms that enforce efficiency without slowing
2:15 PM

CASE STUDY: Preparing Your Enterprise for Agentic and Autonomous Intelligence
- Governance, data, workflow and risk controls needed before deploying agentic systems.
- Readiness models for assessing organizational maturity.
- Capability building for engineering, product and operations teams.
- Practical steps to safely introduce autonomy into high-value workflows.
2:50 PM

FIRESIDE CHAT: You Can’t Scale AI on Weak Data — Why Data Strategy Comes Before AI Scale
- How leading enterprises link data architecture to AI scalability and trust.
- Practical lessons from healthcare, retail, media and energy on building AI-ready foundations.
- Where data investment yields the highest returns for AI programs.
- The strategic consequences of skipping foundational work.
TRACK B: Executional Excellence
1:40 PM

FIRESIDE CHAT: New Value Frameworks for Communicating Data and AI ROI to the Board
- How senior leaders redefine value in terms that resonate with the Board.
- Building narrative frameworks that translate technical impact into business outcomes.
- Separating meaningful impact from superficial metrics
- Tips on improving cross-functional alignment through transparent, repeatable reporting.
2:15 PM

CASE STUDY: Navigating Change Management, Enablement and Workforce Strategy in the New Era of Leadership
- What executives must change in communication, incentives and enablement for AI success.
- Upskilling strategies tailored to modern hybrid human–AI workflows.
- Building internal evangelists who accelerate adoption across business units.
- Responsible leadership practices to manage fear, resistance and displacement concerns.
2:50 PM

CASE STUDY: How Industry Leaders Deliver Measurable Business Outcomes with AI
- How leading enterprises moved from experimentation to enterprise-scale AI adoption, and where they focused first to unlock value?
- What operating and governance choices helped connect AI outputs directly to revenue or efficiency, rather than isolated use cases?
- Why the most successful examples treat data and AI capabilities as products, not projects, and how this shift improves alignment and sustainability?
3:20 PM

Afternoon Break & Networking
09:50

PANEL: When AI Becomes “Business as Usual” and What It Means for Chief Data and AI Roles
- How success quietly reshapes the CDAO mandate.
- Which responsibilities should be expanded, and which should be handed off?
- Managing relevance once AI is embedded across the business.
- Preparing successors and future leadership models.
4:30 PM

CLOSING KEYNOTE: Beyond the Hype Cycle — How the Intelligent Data Stack Drives Measurable Enterprise Value
- What in the data stack creates value — and what doesn’t?
- How leading enterprises turn data and AI investment into measurable outcomes.
- The next critical decisions CDAOs must make to sustain impact at scale.
5:00 PM

Chairperson Closing Remarks
5:00 PM

Networking Drinks Reception
6:00 PM

END OF SUMMIT

CDAO NY schedule

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