Data & Analytics Live schedule

• Why most enterprises still struggle to move beyond dashboards 

• The hard truth: aligning data, culture, and leadership is still the #1 roadblock 

• Where organizations are actually seeing ROI from AI and analytics (vs. hype) 

• What leaders must do in 2026 to avoid being left behind by autonomy, regulation, and disruption 

• How are enterprises modernizing legacy architectures without breaking critical operations — and what usually goes wrong first? 

• What does a truly modern data ecosystem look like in 2026, and how do you balance cloud, lake house, and real-time pipelines without adding more complexity? 

• How do leaders prioritize modernization investments when budgets, talent, and timelines are all constrained? 

• What transformation strategies drive business value — and which ones are still stuck in “pilot purgatory”? 

Moderator: Krishna Chaitanya Yarlagadda, Director of Data Science & AI - Atlanticus. 

Panelists: 

Bicckie Solomon, Director of Pharmacy / Residency Program Director PGY2 HSPAL - HCA FLORIDA NORTH FLORIDA HOSPITAL 

Karthikeyan Ilangovan, Vice President, Data Analytics & AI/ML - MODEGLOBAL 

Rahul Zende, Senior Principal Data Scientist – NAVY FEDERAL CREDIT UNION 

Rama Pilli, Staff Data Engineer / Data & AI Architect - KARD 

Session Description  

Most AI analytics platforms force enterprises into an impossible choice: adopt cloud-only solutions that compromise data governance and security policies, or forgo AI capabilities entirely. For organizations with on-premises infrastructure, regulatory requirements, or data sovereignty mandates, this isn't a choice at all—it's a barrier to innovation. 

In this session, you'll discover:  

• Why infrastructure inflexibility kills AI adoption: The hidden deployment gap causing AI pilot failures in regulated industries, and why most vendors can't solve it with cloud-only architectures  

• AI analytics without architectural compromise: How Logi Symphony delivers full AI-driven analytics across any environment: cloud, on-premises, hybrid, or selfhosted, so you maintain complete control over where your data lives and how it's processed  

• Breaking the AI data access bottleneck: How Simba Intelligence solves the cloudonly trap that plagues most AI query tools, providing LLM-agnostic data connectivity across any deployment model without forcing infrastructure changes or vendor lock-in   

• Real-world deployment scenarios: From regulated industries requiring air-gapped environments to global enterprises managing multi-cloud strategies, see how organizations achieve AI intelligence without sacrificing infrastructure control 

The most powerful AI analytics strategy isn't about choosing between intelligence and control. It's about platforms flexible enough to deliver both, wherever your data needs to be. 

• Meeting the evolving regulatory demands across North America and beyond — AI Act, SEC, and state-level frameworks 

• Wrestling with bias, explainability, and transparency under growing legal and ethical scrutiny 

• Can innovation survive compliance — or is compliance becoming the new innovation? 

• How leaders are redefining governance models for faster, safer, and more auditable AI adoption 

• What does “responsible AI” mean in 2026 — and how to make it a competitive advantage? 

Moderator: Nick Rohrbaugh, Sr. Product Marketing Manager – POSIT 

Panelists:  

Akhil Khunger, VP Quantitative Analytics – BARLCAYS 

Gopal Renganathan, Senior Director, Data & Analytics – ANYWHERE REAL ESTATE INC. 

Navneet Tyagi, Senior Software Engineer- FINANCE OF AMERICA 

Shubhankar Shilpi, Software Engineering Director II – TRUIST BANKS 

As AI transitions from innovation labs into mission-critical systems, enterprises are being forced to answer harder questions: Who controls the models? Where does sensitive data flow? How do we manage risk, cost, and compliance at scale? 

Join Pure Storage VP of AI, Kaycee Lai, as he explores why many organizations are reassessing cloud-only AI strategies and incorporating on-prem and private AI deployments as part of a broader governance and trust framework. 

 
The discussion will highlight how infrastructure choices directly impact AI reliability, security, and long-term business value and touch on the following themes: 
 

• Enterprise AI risk management and regulatory readiness 

• Cost predictability and performance for always-on AI systems 

• Private AI as a foundation for trust and IP protection 

• What boards and executive teams are now demanding from AI leaders 

• Real deployments across healthcare, finance, and retail: what worked, what failed 
• Risks, costs, and success frameworks for scaling responsibly 
• How leaders should prioritize investment when budgets are tight 

Customer expectations are rising, and traditional CX strategies can’t keep pace. With trillions in revenue at risk and customers abandoning brands after a single poor interaction, organizations must rethink how they understand and engage their audiences. Data and AI now offer a powerful path forward - enabling unified customer views, real‑time insights, and personalized, predictive experiences at scale. 

This session explores how leading companies are transforming CX through integrated data, advanced analytics, and AI‑driven automation. This session will break down the essential components of a modern CX strategy, and the organizational shifts required to make it successful. 

Key discussion points: 

• Why legacy CX models are failing in today’s environment 

• Building a unified 360° customer view through data integration 

• Turning data into actionable insights that drive measurable improvements 

• How AI enables hyper‑personalization, predictive engagement, and automation 

• IMPACT framework for ROI measurement 

• Overcoming transformation challenges 

Session Overview: 

• How Organization built its LLM tools to accelerate content creation across regions and languages 

• The data and analytics backbone behind AI content workflows — from multilingual datasets to performance measurement 

• Inside Agentic AI journey: how autonomous systems generate, translate, and evaluate content before human review 

• Balancing automation and quality — where human-in-the-loop ensures brand consistency and trust 

• Lessons learned in governance, evaluation, and data-driven decisioning while scaling AI globally 

As AI rapidly reshapes the enterprise, success depends on more than just technology. In this session, Joshua Burkhow explores how organizations can become truly AI-ready by empowering people, embedding context, and establishing strong governance. Learn how these three pillars work together to unlock transformative value, scale AI responsibly, and turn intelligence into real business impact. 

In this session, you’ll learn how to: 

• Enable teams with the skills, tools, and trust needed to confidently adopt AI 

• Apply context and governance to ensure AI is accurate, compliant, and scalable 

• Move from experimentation to enterprise-wide impact with measurable outcomes 

• Exclusive, interactive dialogue among senior executives 

• How leaders balance innovation, ethics, and organizational alignment 

• Building long-term resilience in an AI-driven economy 

Moderator: Kaycee Lai, Vice President of Artificial Intelligence & Analytics – PURE STORAGE 

Facilitators: 

Edgar Nunez, Chief AI and Analytics Officer – Coca-Cola FEMSA 

Troy Howard, Vice President, Data Governance Manager – BANK OF AMERICA 

Farid Sheikhi, Senior Manager, Analytics Innovation & Data Enablement - RBCx.  

Jayson VanHook, Associate Vice President of Data Strategy and Chief Data Officer – UNIVERSITY OF NORTH GEORGIA 

Benjamin Donlon, Chief Operating Officer – Thumbprint  

Scott McKenzie, Chief Technology Officer – Fort Vermilion School Division 

Bickkie Solomon, Director of Pharmacy / Residency Program Director PGY2 HSPAL - HCA FLORIDA NORTH FLORIDA HOSPITAL 

Matt Dixon, Director, Data Platform - NORTHWELL HEALTH