Organizations are rapidly investing in AI initiatives, expecting to unlock value from their data. At the same time, many recognize the need for data governance to support these efforts. However, a critical gap often remains unaddressed: the lack of a clear understanding of how data is created, transformed, and used across end-to-end business processes.

In a large, multi-decade organization operating across complex operational and supply chain processes, this gap became evident when the Director of Analytics identified the need to enable AI-driven use cases and improve trust in data. While data governance was recognized as a priority, it quickly became clear that governance alone would not be sufficient without a strong understanding of the underlying business architecture and data flows.

This session presents a real-world case study where AI readiness is being addressed by first establishing clarity in business processes and how they generate data. Rather than starting with models or tools, the initiative focuses on building a foundation for trusted, decision-ready data—while also improving the way the business operates on a daily basis.

The approach includes:

• Identification and prioritization of critical operational processes required to support analytics and AI use cases
• Mapping of end-to-end processes (AS-IS) to understand how work is actually performed, how data is generated, and how inefficiencies in operations directly impact data quality and decision-making
• Identification of gaps in process definition, ownership, and data flows impacting data quality and governance
• Development of a heatmap that connects each macro business process with key data, technology, and AI initiatives
• Design of future-state processes (TO-BE) to improve operational performance, simplify daily activities, and enable more consistent, reliable, and decision-ready data across the organization
• Definition of an initial data governance model tailored to the Operations function
• Establishment of metrics to measure improvements in business processes, data quality, consistency, and AI readiness

This work provides a structured roadmap that connects business processes, data, technology, and AI—allowing the organization to move from fragmented initiatives toward a more aligned and scalable approach.

Attendees will learn:

• Why AI readiness depends on understanding how data is generated across business processes
• How to connect business architecture with data governance and data management practices
• How to design a practical, domain-specific governance approach (e.g., Operations)
• How to build a roadmap that aligns data, technology, and AI initiatives to business processes
• How to use artifacts like process maps and heatmaps to drive alignment and prioritization

Speaker: Jessica Zuñiga, Head of AI Readiness & Data Governance, Co-founder, BlueYeti

Jessica Zuñiga is a Cybersecurity expert and Certified Data Management Professional (CDMP), recognized for leading data governance and AI readiness initiatives across organizations in Latin America and the United States. She is one of the Co-founders of BlueYeti, a consulting firm focused on helping organizations establish data governance as an operating model that enables trusted, scalable, and business-aligned data capabilities. Jessica currently advises companies on the implementation of data governance frameworks, strengthening data trust, and enabling capabilities that support the effective adoption of advanced analytics and artificial intelligence. Her experience focuses on translating data strategies into operational capabilities that deliver measurable business value. She has served as an adjunct professor in the Master in Business Analytics program at EGADE Business School, where she has trained future leaders at the intersection of data governance, strategy, and innovation. She is also the founder of the regional initiative Hablemos de Gobierno DATA & AI, focused on promoting data culture, data literacy, and responsible AI adoption. Additionally, she has experience as an international speaker in the United States, Mexico, and Colombia, where her presentations focus on data governance and its impact on business value generation.