Adapting Your Data Strategy for AI

*PLEASE REGISTER ON THE [WEBSITE](https://damaphila.starchapter.com/meetinginfo.php?id=50&ts=1782589865) TO OBTAIN ACCESS TO THE BULDING AND TO PAY FOR THE TICKET.*

Breakfast and lunch are included.

Artificial Intelligence (AI) is transforming the industry, and successful AI needs a strong data foundation. When building your Data Strategy, it can be challenging to balance when to embrace AI and when the foundational aspects of data management, business intelligence, and data governance come into play. This presentation will include how to balance both innovation and foundation with practical, business-focused approaches to building an effective strategy and roadmap. Topics include:

• Prioritizing AI and Analytics Use Cases • Aligning AI with Data Management and Data Governance • Building the Right Team - Roles and Responsibilities • Developing an Effective Roadmap

Donna Burbank will be speaking on this topic. A recognized industry expert in data management with over 25 years of experience helping organizations enrich their business opportunities through data. She is currently the Managing Director of Global Data Strategy, Ltd., where she assists organizations around the globe in driving value from their data. Donna speaks regularly at industry conferences, she has co-authored several books on Data Management, and is a regular contributor to industry publications. Securing Your Data for AI Session Description AI changes what enterprise data does. Beyond reporting and analytics, data now directly shapes model behavior, retrieval, recommendations, automation, and agent actions — making data governance a security concern. This session uses LLM04 2026: Data and Model Poisoning as an industry reference point to examine how poisoning risk enters through untrusted sources, manipulated content, stale knowledge, unsafe feedback loops, and AI-accessible data that is treated as more authoritative than it should be. The session will connect these risks to the governance controls required to secure data for AI systems. Additional Topics

• How AI expands the enterprise data attack surface • How poisoned or manipulated content affects RAG retrieval and recommendations • How compromised fine-tuning sets and feedback loops degrade model behavior • Source trust, provenance, and authority for AI-accessible data • Ingestion controls and lifecycle management for AI pipelines • Vulnerability identification and testing specific to AI data flows • Mapping LLM04 2026 to practical data governance decisions

Mark Roxberry will be speaking on the topics. He is a trusted consultant in AI security and intelligent systems architecture with over 20 years of experience helping organizations navigate the intersection of data, risk, and emerging AI. He is Principal Consultant for Security and Intelligent Solutions at Database Solutions Inc. and holds CISSP and CEH certifications. Mark works with clients across healthcare, gaming, financial services, and other regulated industries. He leads the OWASP HACTU8 AI security testing project and the OWASP LLM04 Working Group, speaks regularly on AI governance and secure architecture, and focuses on making enterprise AI capabilities useful, testable, and governable in production environments.