CDAO NY
Presentations
CDAO NY
Opening Remarks
John Shaw, Chief Executive Officer, PRAXIS IQ
Is your Enterprise Data Ready to Scale Analytics and AI?
- Identifying the architecture maturity gaps preventing organizations from scaling analytics and AI.
- Strengthening core capabilities to create reliable and scalable data foundations.
- Key milestones for assessing enterprise data readiness and prioritizing architectural improvements.
Lovedeep Saini, Chief Analytics Officer, CONNER STRONG & BUCKELEW
Limiting Agentic AI Decision Risk and Driving ROI with Real-Time Data Platforms and Data-Layer Governance
Legacy batch ETL pipelines and fragmented data silos aren't just expensive — they're dangerous. By consuming up to 80% of IT budgets on maintenance and creating OLTP-to-OLAP visibility gaps, they expose autonomous AI agents to stale data, the root cause of model hallucination and flawed operational decisions. This session demonstrates how a converged, zero-ETL architecture — enforcing governance directly at the data layer eliminates pipeline latency, neutralizes vendor lock-in, and gives AI agents the real-time, high-fidelity data they need to act safely and decisively. Attendees will leave with a FinOps framework for data and a Return on Data (ROD) model to help CDAOs transform their data stack from a maintenance cost center into a sovereign governance engine for agentic AI at scale.
Ava Chawla, Field CTO, ENTERPRISE DB
Rethinking the Enterprise Data Operating Model
- What operating model best supports scalable enterprise data and analytics delivery?
- How should organizations define ownership across data products, engineering, analytics, and business teams?
- Approaches for funding and governing enterprise data initiatives.
Dr. Ram Singh, Chief Performance Media Officer, NIGHT MARKET
The Next AI Breakthrough Isn’t a Model, It’s ROI
- Assigning a business owner and P&L targets to every AI initiative with clear KPIs and SLAs.
- Stack-ranking bets by ROI and time-to-value, time-boxing pilots, and doubling down on compounding wins.
- Productizing models into workflows/agents and driving adoption with enablement, incentives, and change management.
- Instrumenting value end-to-end: establishing baselines, unit economics, TCO, and risk-adjusted ROI with continuous optimization.
Abhishek Mittal, Chief Product & AI Officer, AML RIGHTSOURCE
CAIO New York
Human-AI Co-Adaptation: A Core Driver of Sustained AI Adoption
Despite rapid enterprise investment in AI, approximately 80-90% of AI tools purchased by US companies fail to yield gains in efficiency or ROI (NBER, 2026). An overlooked reason is that tech adoption typically takes years, whereas AI evolves in weeks to months. This talk argues that lasting AI adoption and transformation require human-AI co-adaptation: a continuous process in which leadership, staff, workflows, governance, and AI systems evolve together.
- Why most AI deployments fail to bring impact
- How AI’s speed is breaking traditional change management
- What successful human-AI co-adaptation entails, with a real-world case study
- How to build trust, uptake, performance, and impact in parallel, rapidly and adaptively
Linda Hermer, Chief Data Strategy Officer/ CEO
Building the Blueprint: The Core Pillars of a Successful AI Strategy
- Aligning AI initiatives with business objectives to deliver measurable value.
- Establishing strong data foundations and governance for scalable innovation.
- Embedding ethical, transparent, and responsible AI practices across the enterprise.
- Fostering a culture of experimentation, agility, and continuous improvement.
Ali Abedini, Chief AI Officer, METROPOLITAN COMMERCIAL BANK
Upskilling Everyone: Building AI Capability at Scale
Organizations invest heavily in AI, but without skilled people, those investments stall. DataCamp's two-track model drives real transformation: broad AI literacy for all and deep technical training for builders, backed by insights from 18M learners across 6,000+ organizations.
Charlie Hecht, Senior Director, North America Sales, DATACAMP
Beyond Algorithms: The Age of Agentic Intelligence and Quantum Disruption
- How agentic AI is reshaping enterprise operations — and why the identity and security gaps are already exposing organizations before quantum arrives.
- Why the cryptographic infrastructure beneath your AI agents is on a depreciation schedule — and what Harvest Now, Decrypt Later means for data you encrypted today.
- How quantum breakthroughs and binding regulatory deadlines are converging in the same five-year window — and why the compliance clock runs ahead of the hardware threat.
- What leaders must do in the next 90 days to build quantum-ready, agent-secure infrastructure before the window closes.
Ellis Wong, Chief Information Security Officer, JST CAPITAL