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NOVEMBER 18–19, 2026
PARIS EXPO PORTE DE VERSAILLES

CO-LOCATED SHOWS

Topics for the Data & AI Leaders Summit 2026

THEME: From Data Availability to Data Trust

Companies have never had access to so much data or undertaken so many AI projects. Yet scaling up remains a challenge. The issue is no longer access to data, but the ability to ensure its reliability, governance, and usability in production.

Between data quality, data governance, MLOps, and AI compliance, organisations must structure their approaches to move from promising use cases to robust systems. True transformation hinges on the ability to build lasting trust in data and models.

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Bad data can ruin good AI

A high-performance model can never compensate for poor-quality data. Issues related to data quality, ownership, and accountability are now central to artificial intelligence projects.

Teams must address practical issues such as data integrity, data lineage, and data ownership to avoid bias, errors, and misuse. The performance of AI depends directly on the quality of the data it is fed.

Industrialisation makes all the difference

Many data and AI projects get stuck at the prototype stage. Moving into production requires robust practices related to MLOps, data pipelines, and model monitoring.

Without model monitoring, model drift management, and continuous verification, even the most promising use cases quickly lose their value. The challenge is to integrate AI into reliable operational environments that can stand the test of time.

Governance fosters trust at scale

Deploying AI in complex environments places significant demands on data governance. Concepts such as explainability, traceability, and auditability are essential to ensuring the trust of business units and regulators.

Organisations structure their approaches around data governance frameworks, AI explainability, and data lineage to ensure that decisions are understandable and verifiable. Without governance, AI remains difficult to deploy at scale.

Compliance underpins responsible use

Regulatory frameworks such as the GDPR and the AI Act require that risk management and compliance be built in from the design stage. AI can no longer be developed without a rigorous approach to AI compliance and data protection.

Companies must demonstrate their ability to monitor usage, document models, and manage associated risks. Compliance is becoming a key driver for deploying responsible and sustainable AI.

Join the Data & AI Leaders Summit at Tech Show Paris 2026, at Paris Expo Porte de Versailles

Designed for Chief Data Officers, data managers, AI leaders, and business decision-makers, the Data & AI Leaders Summit helps you transform your data and artificial intelligence initiatives into measurable drivers of performance.

Whether you’re in the exploration phase or scaling up, you’ll find practical insights, peer-to-peer discussions, and solutions to ensure the reliability of your data, scale up your models, and create lasting value.

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