CDAO West Coast schedule

As organizations race to integrate AI across the enterprise, success hinges on more than just technology. This panel brings together senior data and AI leaders to explore how to effectively align AI initiatives with broader business and product strategies. 

• Strategies for embedding AI into core business roadmaps to drive measurable impact 
• How talent models and team structures evolve as AI maturity grows 
• Real-world lessons in overcoming internal resistance, fostering adoption, and building a culture of AI readiness 

Panelists:  

Justin Molavi, Director, Commercial Strategy and Insights, GENENTECH 

Jaya Gali, Vice president - National Integration Services, FEDERAL RESERVE BANK OF SAN FRANCISCO 

Das Dasgupta, Chief Data Analytics & AI Officer, GLOBAL FORTUNE 500 COMPANY

Ankur Uttam, VP of Data Science and Analytics, POSHMARK 

Three out of four companies are betting big on AI – but most are digging on shifting ground. In this $100 billion gold rush, none of these investments will pay off without data quality and strong governance – and that remains a challenge for many organizations. Not every enterprise has a solid data governance practice and maturity models vary widely. As a result, investments in innovation initiatives are at risk of failure. What are the most important data management issues to prioritize? See how your organization measures up and get ahead of the curve with Actian. 

What does it take to build AI strategies that scale across not just teams—but entire industries? In this session, Rama Kattunga shares insights from her cross-sector leadership to explore how organizations can develop AI architectures that are flexible, reusable, and future-ready. 

• Designing AI frameworks that transcend organizational boundaries and adapt to diverse industry demands 

• Building modular data and AI infrastructure that supports rapid experimentation and innovation 

• Applying AI lessons learned in one vertical to solve challenges in another 

In today's fast-paced financial landscape, reliable data is the backbone of informed decision-making, and Artificial Intelligence (AI) is revolutionizing the way financial institutions approach risk management. As financial institutions navigate vast amounts of complex data, ensuring its accuracy and integrity is crucial for strategic initiatives, risk management, and regulatory compliance. 

Join Curtis O'Dell, Global Business Director for Data Integrity, as he delves into the critical relationship between data integrity and the success of AI and ML initiatives. This session will explore: 

• The importance of data integrity and its impact on AI/ML initiatives 

• Building a resilient and trustworthy data testing system for AI success 

• Real-world challenges and success stories from enterprises that have achieved AI-driven results with high-quality data 

• Strategies for leading enterprises to confidently leverage data-driven risk management for AI-powered risk mitigation, like fraud detection 

• How maintaining data integrity for the regulated enterprises is crucial in providing an auditable, compliant, and a rigorous approach to managing data, conversions, and mergers. 

20 min Breakout Session + 20 min Discussion Groups

• Revolutionizing Customer Insights: Learn how CoastHills Credit Union leveraged SurveyMonkey and Power BI to deliver next-day analytics, transforming raw customer feedback into actionable strategies that drive organizational success. 

• Accelerating Decision-Making: Discover how dynamic Power BI dashboards empowered leadership teams with real-time visibility into key metrics, enabling faster, data-driven decisions. 

• Streamlining Operations: Discover how CoastHills optimized customer feedback workflows, enhanced efficiency, and aligned those workflows with strategic business goals. 

• Bridging the Business-Analytics Gap: Learn how to foster collaboration between business leaders and front-line teams to deliver world-class customer service by combining innovative solutions with practical, measurable results. 

Learn how leaders are balancing innovation with compliance as they modernize infrastructure and decision-making with AI. 

• Real-time AI applications in trading, credit decisioning, and fraud detection 
• Leveraging cloud-based architectures for forecasting, risk modelling, and customer insights 
• Navigating regulatory complexities while deploying AI across critical financial functions 

Moderator:

Ashlyn Lackey, Director, Innovation Strategy, PRUDENTIAL FINANCIAL  

Panelist:  

Annie Ross, Vice President, Analytics Solutions, Global Banking, J.P. MORGAN CHASE 

• Embedding AI into strategic and operational decision-making across the enterprise 

• Scaling automation to enhance agility, efficiency, and cross-functional impact 

• Designing AI-native organizations built for continuous learning and innovation 

• Shaping a data-driven culture that supports real-time, intelligent execution 

This session offers a practical lens on how data leaders can enable intelligent automation and operational responsiveness at scale. 

• Designing low-latency data pipelines for AI-driven financial insights 

• Embedding decision intelligence into real-time operational systems 

• Technical strategies for integrating AI models into live business processes 

Moderator:  

Senior Representative of Attacama 

As organizations move beyond experimentation, data and AI leaders are tasked with operationalizing AI responsibly, strategically, and at scale. This panel explores how to move from isolated wins to enterprise-wide transformation—balancing innovation with structure, and velocity with trust. 

• Evolving AI governance frameworks to support scalable, secure, and responsible AI adoption  

• Embedding GenAI into business processes while avoiding tool sprawl and ensuring alignment with strategic goals  

• Building the right data and AI infrastructure to support agility across business units  

• Measuring and communicating the business value of AI initiatives to executive stakeholders 

Moderator:  

Jeremy Epstein, Senior Analyst, AMERICAN FAMILY VENTURES 

Panelists:  

Awais Sher Bajwa, Head of Data & AI Banking, BANK OF AMERICA 

Aravind Peddiboyina, AI Innovation, COE GenAI Global Analytics Leader, KIMBERLY-CLARK 

• What investments should AI & data leaders prioritize in 2025? 

• What organizational shifts will be needed for AI-driven companies? 

• Actionable steps attendees can take within 6-12 months. 

As organizations race to integrate AI across the enterprise, success hinges on more than just technology. This panel brings together senior data and AI leaders to explore how to effectively align AI initiatives with broader business and product strategies. 

• Strategies for embedding AI into core business roadmaps to drive measurable impact 
• How talent models and team structures evolve as AI maturity grows 
• Real-world lessons in overcoming internal resistance, fostering adoption, and building a culture of AI readiness 

Panelists: 

Justin Molavi, Director, Commercial Strategy and Insights, GENENTECH 

Jaya Gali, Vice president - National Integration Services, FEDERAL RESERVE BANK OF SAN FRANCISCO 

Das Dasgupta, Chief Data Analytics & AI Officer, GLOBAL FORTUNE 500 COMPANY

Ankur Uttam, VP of Data Science and Analytics, POSHMARK 

Three out of four companies are betting big on AI – but most are digging on shifting ground. In this $100 billion gold rush, none of these investments will pay off without data quality and strong governance – and that remains a challenge for many organizations. Not every enterprise has a solid data governance practice and maturity models vary widely. As a result, investments in innovation initiatives are at risk of failure. What are the most important data management issues to prioritize? See how your organization measures up and get ahead of the curve with Actian. 

What does it take to build AI strategies that scale across not just teams—but entire industries? In this session, Rama Kattunga shares insights from her cross-sector leadership to explore how organizations can develop AI architectures that are flexible, reusable, and future-ready. 

• Designing AI frameworks that transcend organizational boundaries and adapt to diverse industry demands 

• Building modular data and AI infrastructure that supports rapid experimentation and innovation 

• Applying AI lessons learned in one vertical to solve challenges in another 

• Designing for Agentic Flow in Human-Centered Healthcare AI: Explore how reasoning algorithms help AI agents navigate complex clinical workflows while fostering collaboration and trust with healthcare professionals. 

• Ethics in Agentic Healthcare Systems: Learn how to embed ethical principles into AI behavior to ensure responsible, transparent, and safe decision-making in patient care. 

• Advanced Reasoning Techniques for Clinical Adoption: Discover approaches like abduction to help AI make sense of incomplete clinical data—driving more accurate support and boosting confidence among clinicians. 

• Psychology-Driven UX for Trust and Engagement: Explore UX strategies rooted in psychology that give AI human-like qualities to increase clinician trust, reduce cognitive load, and support adoption. 

• Driving Real-World Impact in Healthcare Transformation: Examine how agentic AI is already transforming care delivery—streamlining diagnostics, optimizing workflows, and improving patient outcomes across healthcare systems. 

Explore how AI and large-scale experimentation are transforming modern retail marketing. This session will dive into how data-driven testing and optimization can enhance customer targeting, improve campaign performance, and unlock new opportunities for growth. Gain practical insights into building a culture of experimentation that delivers measurable business impact. 

As healthcare organizations accelerate AI adoption, safeguarding patient data has never been more critical. This session explores how to enable innovation without compromising security or compliance. 

• Strategies for protecting sensitive healthcare data in AI-driven environments 

• Navigating HIPAA, GDPR, and evolving global regulatory frameworks 

• Real-world examples of secure, scalable data architectures in healthcare 

• Large scale ML-driven Recommender system to drive global B2C streaming service subscribers’ personalized experiences and retention 

• AI-powered recommendations and next best actions for B2B e-commerce platform and sales consultants to improve customer engagement and sales revenue 

• Gen AI innovation to drive B2C and B2B personalization and future outlook 

• How to align data architecture, governance, and business objectives to support enterprise-wide analytics and AI.  

• Best practices for modernizing data ecosystems 

• Breaking down silos and building a data-driven culture that empowers decision-making and innovation.  

• Ensuring data integrity, security, and regulatory alignment while enabling seamless adoption across business units. 

Moderator:  

Radhika Rangarajan, Co-Founder, WOMEN IN BIG DATA 

Panelists: 

Mike Doll, VP of Data, THE GUITAR CENTER COMPANY  

Vineet Kumar, Vice President, Data Science, FANATICS COMMERCE 

Ganesh Sivakumar, Global Head of Data Analytics & AI, RECKITT (IT&D) 

• Explore how AI and advanced analytics are being applied to streamline eCommerce and retail operations, from inventory management to dynamic pricing. 

• Learn how to integrate siloed data sources to create a unified analytics layer that supports smarter, real-time decision-making across business units. 

• Understand the role of predictive models and intelligent automation in driving measurable improvements in speed, cost-efficiency, and customer experience. 

• Gain insights into aligning analytics capabilities with operational strategy—ensuring cross-functional teams can act on insights at scale. 

Moderated by Krishna Karuturi, Director, Research Data & Analytics,

SUTTER HEALTH  

As organizations move beyond experimentation, data and AI leaders are tasked with operationalizing AI responsibly, strategically, and at scale. This panel explores how to move from isolated wins to enterprise-wide transformation—balancing innovation with structure, and velocity with trust. 

• Evolving AI governance frameworks to support scalable, secure, and responsible AI adoption  

• Embedding GenAI into business processes while avoiding tool sprawl and ensuring alignment with strategic goals  

• Building the right data and AI infrastructure to support agility across business units  

• Measuring and communicating the business value of AI initiatives to executive stakeholders 

Moderator:  

Jeremy Epstein, Senior Analyst, AMERICAN FAMILY VENTURES 

Panelists:  

Awais Sher Bajwa, Head of Data & AI Banking, BANK OF AMERICA 

Aravind Peddiboyina, AI Innovation, COE GenAI Global Analytics Leader, KIMBERLY-CLARK 

Krishna Karuturi, Director, Research Data & Analytics, SUTTER HEALTH 

• What investments should AI & data leaders prioritize in 2025? 

• What organizational shifts will be needed for AI-driven companies? 

• Actionable steps attendees can take within 6-12 months.