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World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

From Data Mesh to AI Mesh: Integrating Distributed Intelligence on Decentralized Data Architectures

Olga Woschitz , Thomas Görz

AI pilots stall without a trustworthy data foundation. Evolve your data mesh into an AI mesh to deliver distributed, domain-specific intelligence as a product at scale.

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#1 about 3 min

Identifying the scaling crisis in enterprise AI

A lack of governed and accessible data prevents organizations from moving agentic AI projects beyond the pilot phase.

#2 about 3 min

Core principles of decentralized data mesh architecture

Decentralized data ownership and federated governance enable scalable and self-service data management across domains.

#3 about 2 min

Addressing the human bottleneck in data interpretation

Manual metadata curation and human decision-making prevent organizations from scaling intelligence at the speed of data.

#4 about 3 min

Designing AI mesh through distributed domain intelligence

Distributing intelligence through specialized agents and standard protocols enables automated decision-making and composable intelligence products.

#5 about 3 min

Navigating the maturity stages of AI mesh

Organizations must build a solid data foundation before advancing from basic automation to autonomous self-optimizing systems.

#6 about 2 min

Establishing an AI-ready data foundation for agents

Data must be findable, understandable, trustworthy, and consumable for agents to execute intent-based semantic searches accurately.

#7 about 6 min

Solving cross-domain ESG reporting with distributed architecture

Distributing data ownership across departments streamlines complex regulatory reporting and eliminates manual reconciliation workflows.

#8 about 4 min

Building decentralized data mesh infrastructure on AWS

Utilizing Amazon SageMaker and DataZone environments establishes clear domain ownership and simplified data catalog discovery.

#9 about 4 min

Automating regulatory compliance through distributed AI agents

Integrating domain-specific intelligence allows automated validation of regulatory changes without manual cross-department reconciliation.

#10 about 3 min

Defining core capabilities for enterprise AI mesh

Distributed agents, a centralized registry, model locality, and standard protocols ensure privacy and seamless interoperability.

#11 about 8 min

Implementing an AI mesh architecture stack on AWS

Layering agent cores and interoperability protocols over a data foundation creates a scalable and governed intelligence network.

#12 about 4 min

Exploring data catalogs in SageMaker Unified Studio

Navigating data catalogs and inspecting schema lineage highlights the manual effort required before implementing an intelligence layer.

#13 about 4 min

Orchestrating distributed agents for cross-domain queries

Using an orchestrator agent automates data retrieval across multiple domains while maintaining strict lineage and access control.

#14 about 3 min

Implementing AI governance and adoption strategies

Extending existing data policies with agent guardrails and model monitoring enables secure transitions to intelligence-as-a-product models.

Matching moments

1:50 min

The future of data engineering and AI mesh

Sandhya Menon Sandhya Menon · WWC Europe 2026

4:29 min

The impact of agentic AI on data architecture

Hellmar Becker Hellmar Becker · WWC Europe 2026

3:11 min

Decentralizing data bottlenecks with data mesh principles

Matthias Niehoff Matthias Niehoff · WWC 2024

2:25 min

Adopting a decentralized data mesh architecture model

Sandhya Menon Sandhya Menon · WWC Europe 2026

3:52 min

Establishing a structured framework for enterprise AI

Julian Joseph · LIVE

4:20 min

Connecting data and modern AI with data fabric architecture

Andreas Christian · LIVE

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