As organizations push toward AI‑ready ecosystems and next‑generation data products, data architects are being asked to do more than design systems — they’re being asked to connect architectural decisions directly to business outcomes. But making that shift requires more than new tools or frameworks. It requires a deeper understanding of the Why: the business purpose, the intended outcomes, and the clarity that guides meaningful progress.

This session explores that evolving mandate through the lens of Difficult‑Easy and Difficult‑Difficult, a framework that distinguishes between effort that feels productive and effort that actually creates change. In many organizations, architects and technical teams get stuck in Difficult‑Easy work: familiar, effortful, often exhausting tasks that keep everyone busy but don’t move the business forward. The real mandate for architects lies in the Difficult‑Difficult work: clarifying purpose, aligning stakeholders, defining shared semantics, and making intentional decisions that support trust, interoperability, and AI‑ready data products.

Drawing on real-world experience navigating complex enterprise environments, this session will help architects anchor their decisions in a clear business Why — and recognize when they’re being pulled back into familiar but unproductive patterns.

Attendees will learn:

• How to articulate the *Why* behind architectural decisions in business terms  
• How to distinguish between Difficult‑Easy work that feels productive and Difficult‑Difficult work that drives outcomes  
• How clarity of purpose helps align developers, leaders, and value streams  
• How next‑generation data products depend more on shared intent than on any specific technology  
• This session offers a grounded, human-centered perspective on the evolving role of the data architect — one that emphasizes purpose, alignment, and the courage to do the work that truly matters.

Speaker
Frances Stoor
Manager, Data & AI Governance
Jackson Financial

Frances Stoor is a seasoned data governance and technology leader with more than 20 years of experience spanning software development, enterprise architecture, and modern data management. She brings a rare blend of deep technical expertise and strategic governance leadership, enabling organizations to build trust in their data and make confident, insight-driven decisions.

Frances has led enterprise data and AI governance programs that empower business units across HR, finance, legal, operations, and delivery to own and steward their data with clarity and accountability. She specializes in designing practical governance frameworks, modernizing data architecture, and embedding automated controls that strengthen operational resilience and reduce risk.

A certified Applied Data Governance Practitioner (ADGP) and Certified Data Management Professional (CDMP), Frances is recognized for translating complex technical concepts into actionable strategies that resonate with executives, data stewards, and engineering teams alike. Her leadership consistently bridges the gap between business and technology, fostering a culture of collaboration, transparency, and excellence in data management.