Live Virtual Session

Automating Data Governance and Guiding AI with Computational Policies

Discover how computational policies can turn data governance into an automated, verifiable and scalable process, without slowing teams down or compromising agility.

During the session, we’ll explore two core capabilities that are reshaping modern data governance:

🔹 Automated Governance
Learn how governance rules can be expressed as executable policies that shift compliance left, act as quality gates at deployment, and monitor data behavior in production—ensuring continuous alignment with standards and avoiding late-stage surprises.

🔹 AI-Guided Data Product Design
See how AI can be empowered and directed through computational policies to support the creation of compliant and governable data products. From generating business metadata to providing architectural guidance, AI becomes a co-pilot that enhances, not risks, governance.

Topics covered include:

- Deploy-time policy enforcement: data contract validation (ODCS), breaking change detection, and metadata quality checks
- Runtime validation with alerting and notifications
- AI-assisted creation of data contracts and semantic metadata
- Using governance policies to guide AI in building trustworthy and well-governed data products

If you’re looking to scale governance effectively while embracing AI safely, this session will offer practical insights and actionable examples

Amy Raygada is a seasoned Data and AI Strategist with over 15 years of experience transforming how organizations leverage data for strategic advantage. As a Data and AI strategist at Thoughtworks, she specializes in data mesh architecture, data governance frameworks, and data product strategies that align technical capabilities with corporate vision. Throughout her career at leading organizations, Amy has developed expertise in bridging the critical gap between business stakeholders and technical teams to drive measurable ROI from data initiatives. Amy's approach combines deep technical acumen with strategic business insight, enabling organizations to move beyond traditional data silos toward distributed, product-oriented data architectures.

After earning a master’s degree in Telecommunications Engineering from Politecnico di Torino, Paolo specialized in distributed technologies, achieving top certifications in software development. He co-founded Agile Lab in 2014, where he serves as CTO, leading Operations and Architectures in Big Data and AI. Over the years, he has worked on complex Big Data projects across Europe.Since 2019, Paolo has emerged as a leader in Data Mesh and Data Strategy, driving six large-scale implementations, contributing to the community, and creating Witboost, a Data Product Management platform.