As organizations accelerate their adoption of AI and GenAI technologies, the need for “AI-ready” data—clean, mature, and well-prepared—has become paramount. This presentation introduces a comprehensive framework developed at Vanguard for achieving AI-ready data across the enterprise. The framework is built on eight foundational tenets: Organization and Ownership, Data Management, Timeliness, Performance, Consistent Product Development, Resiliency, Security, and Governance.

Through practical examples, including an end-to-end client address change workflow, the framework demonstrates how these principles apply to both deterministic (structured, semi-structured, unstructured) and non-deterministic (prompt-driven, model-generated) data. The approach emphasizes the interconnectedness of operational, analytical, and GenAI data needs, advocating for a holistic, domain-driven design and a shared responsibility model between platform enablers and data producers.

Attendees will gain actionable insights into reducing data pre-processing time, improving model accuracy, minimizing bias, and ensuring regulatory compliance—while maintaining agility to adapt to emerging AI technologies. The session will conclude with a roadmap for maturing data practices and building a sustainable foundation for effective AI applications.

Speaker: Anita Lotlikar, Chief Data Architect, Vanguard

Anita Lotlikar is a visionary technology leader driving Vanguard’s cloud enterprise data strategy and the evolution of analytics design solutions. With over 25 years of experience in the finance industry, Anita brings deep expertise across application development, enterprise systems, distributed computing, cloud-native architectures, and data platforms. She is a key architect behind Vanguard’s transformation toward AI-Ready Data, enabling integrated, scalable solutions that support advanced analytics and machine learning. Anita is also instrumental in operationalizing Data Mesh principles, fostering decentralized ownership and domain-aligned data products. Her work is grounded in a robust Domain Driven Design (DDD) framework, which she leverages to build modern, adaptive systems that are resilient, interoperable, and future-ready. Anita’s strategic influence spans cross-functional teams globally, where she champions architectural excellence, accelerates innovation, and ensures alignment with business outcomes.

Speaker: Kristy Tomcykoski, Head of Data Governance, Vanguard

Kristy Tomcykoski joined Vanguard in February 2025 as the Head of Data Governance after spending most of her career working in the banking and financial services industry. Before joining the JPMorgan Chase Cybersecurity organization to lead firmwide data protection initiatives, Kristy was instrumental in establishing data governance at Barclaycard US while reporting directly to the Chief Data Officer. In 2021, she and her husband, Chris, relocated to Colorado, where they lived with their Boxer, Bernie, for a few years. During that time, Kristy established governance for employee data at Starbucks and led an initiative to scale the data governance framework across the enterprise. She also established foundational aspects of data and AI governance for Crocs Inc. A Temple University and University of Delaware alum, Kristy holds a Bachelor's degree in Economics and a Master's degree in Information Systems Technology Management. She is PMP, ISO27001:2022 certified, and completed a JPMC Cybersecurity certification program through the University of Delaware. Kristy loves to travel and has visited over 30 countries. She enjoys hiking and other outdoor activities.

Speaker: Matthew DiNatale, Senior Product Manager, Vanguard

Matt has 26+ years of experience at Vanguard, working across the Institutional, Retail, International, and Corporate business operational areas, most recently acting as Senior Product Manager for metadata within the Chief Data Office. In the last 7 years, he was tasked with formulating a strategy for a catalog including integration points with governance, data quality, business operations/enrichment, lineage, and overall master data management. Matt's accomplishments include: establishing an enterprise catalog tool, integrating technical and business metadata within the tool, formulating a lineage process, customizing the user interface, and housing analytical and operational metadata for 1000+ users to find data. As organizations move into the AI era, his focus will be on the utilization of GenAI to reinforce and supplement active metadata and lineage. Matt holds an undergraduate degree from Villanova in mathematics and a master's degree from Penn State in information science.