CDAO Dallas 2025 schedule

The real challenge in scaling AI isn’t the technology—it’s the people, processes, and organizational trust required to embed it sustainably. This discussion explores how leaders can move from pilots to enterprise adoption with lasting impact. 

• Build trust and overcome AI fatigue by aligning adoption with business needs and outcomes. 

• Balance speed of deployment with governance, risk, and executive oversight. 

• Establish AI as a sustained business capability, not a short-lived initiative. 

Moderator: Lauren Inskeep, Vice President - Data Governance, Chief Data Office, T. ROWE PRICE 

Panelists: 

Vinod Surasani, Sr Software Engineer MDM, RBC 

Mohan Krishna Mannava, Business Intelligence and Data Analytics Leader, TEXAS HEALTH RESOURCES 

Parshaw Ghosh, Senior Manager - Software Engineering, CAPITAL ONE 

When done right, governance is a growth engine. In this talk, Jean-Georges “jgp” Perrin will show how data contracts bring precision, trust, and accountability into your data and AI pipelines—without creating bottlenecks. Using the Open Data Contract Standard (ODCS) from the Linux Foundation’s Bitol project, you’ll see how organizations can cut downstream defects, accelerate AI model onboarding, lower compliance risk, and reduce firefighting—often in just days. 

Beyond the pilot phase, real-world GenAI implementation brings new challenges. This session shares tested strategies for navigating that shift. 

• Balancing innovation with oversight in regulated environments 

• Embedding GenAI into workflows without disruption 

• Mitigating hallucinations and measuring what matters 

• Governance frameworks that support scalable GenAI use 

Agentic AI promises to transform how organizations automate business processes - but without a solid data foundation, these initiatives often falter. When AI agents act on behalf of users, they must be able to inherit security permissions, access the right data in real time, and understand business context. Without that, they risk delivering inconsistent answers, exposing sensitive information, or driving the wrong outcomes. 

This session explores why a unified data and business context layer is essential for making Agentic AI both powerful and trustworthy. We’ll discuss the pitfalls organizations face today - from fragmented data silos that starve agents of critical context, to ad-hoc integrations that bypass governance and erode trust. 

We’ll then show how leading enterprises are addressing these challenges with a single, governed data access foundation that gives agents and users consistent, explainable, and secure insights at scale. 

If you want your AI initiatives to move beyond pilots and reliably drive business value, this session will provide the roadmap to get there. 

Proving ROI is the ultimate benchmark for data and AI leaders — but demonstrating value at the board level requires more than metrics. This panel examines how to translate investments into tangible outcomes and communicate them in a manner that resonates with executive leadership. 

• Shifting from operational performance metrics to financial and strategic impact. 

• Framing AI and data initiatives in board-ready language that influences decision-making. 

• Navigating long-cycle and cross-functional use cases where ROI is harder to measure. 

• Avoiding the pitfalls of overpromising and build lasting executive trust.  

Panelists:  

Sivakumar Ganesan, Director-Product Management, FIDELITY INVESTMENTS 

Gowtham Chil, Director - Product Management, HUMANA 

Preetham Kaukuntla, Staff Data Scientist, GLASSDOOR 

Moderator: Jasper Cannon, Management Consultant, CHESTERTON HILLS CONSULTING 

• Developing  practical steps to move from strategic planning to successfully deploying data, analytics, and AI initiatives across the organization 

• Addressing common roadblocks such as data silos, governance, and scalability to ensure a seamless implementation 

• How to leverage AI and analytics to uncover opportunities, enhance decision-making, and achieve measurable business impact 

Moderated by:  
Joshua Burkhow, Chief Evangelist, ALTERYX 

Steve Brodrick, Founder & CEO, HORIZON 5 LLC 

As AI reshapes the enterprise, the CDAO role is evolving from data steward to enterprise strategist. This closing discussion brings together senior leaders to explore how CDAOs can strengthen their influence, build trust across the C-suite, and steer their organizations through transformation. 

Redefine the CDAO mandate in an AI-first enterprise. 

Build influence and trust with IT, risk, innovation, and business leaders. 

Balance strategic vision with the accountability of execution. 

Position the CDAO as a key voice in shaping culture, investment, and enterprise strategy. 

Moderator: Larry Hunt, Field CDO for Financial Services, ATACCAMA 

Panellists: 

Karthik Ilangovan, Vice President - Data Analytics and AI/ML, MODE GLOBAL 

Div Khanna, Global Head of People Data Strategy and Analytics, KENVUE 

Thrushna Matharasi, Director of Engineering, Data and AI/ML, SOLERA HOLDINGS 

Akshay Krishna, Staff Data Analyst, QUINCE 

As enterprises accelerate innovation with new data-driven technologies, the risks grow as quickly as the opportunities. This panel explores how CDAOs and technology leaders can balance performance, compliance, and security without slowing progress. 

• Address data sovereignty, privacy, and compliance challenges in distributed and emerging environments. 

• Build trust by embedding governance and security into new data architectures from the outset. 

• Balance the cost, scale, and speed of innovation with enterprise risk tolerance. 

• Explore how board-level oversight is evolving to cover real-time, technology-driven decision-making. 

Panelists: 

Vipin Kataria, Senior Lead Architect - Data/ML, PICARRO INC. 

Devdas Gupta, Sr. Manager Software Development and Engineering Lead, CHARLES SCHWAB 

Naresh Dulam, Senior Vice President of Software Engineering, JP MORGAN CHASE & CO. 

Moderator: Vinoth Nageshwaran, Senior Data Engineer, BUSINESS INSIDER 

Enterprises are increasingly using AI to interpret text from customers, partners, and regulators.  

Entity extraction and sentiment analysis are core capabilities for transforming unstructured text into structured, actionable data. 

The newest large language models (LLMs) enhance these capabilities but require more than accuracy — they demand orchestration, governance, and activation. 

When properly implemented, AI-native text processing enables: 

• Faster issue resolution 

• Prioritized customer retention strategies 

• Proactive compliance alerts 

• More relevant product recommendations 

• Treating unstructured text as a governed, real-time data source helps enterprises turn conversations into competitive advantage. 

• Analytics is broken at the last mile, where insights stop short of action, costing organizations millions in delay, waste, and inaction.  

• Learn how a three-tier Agentic analytics architecture fuses diagnostics, LLM reasoning, and autonomous action to close this gap.  

• See how enterprises can shift from dashboards to speed of light, closed-loop decision systems, unlocking new levels of resilience and ROI.