Many organizations are under pressure to become more data-driven and adopt AI. At the same time, concerns around data sovereignty, geopolitical risks, legislation, vendor lock-in and rising cloud costs are increasing.

The Koninklijke Notariële Beroepsorganisatie (KNB) faced a fundamental question:

How do we create a future-proof data and intelligence platform that enables advanced analytics and AI while maintaining control over our data, architecture and long-term choices?

In this session, KNB shares its real-world experience, including:

• The business and regulatory challenges that triggered the initiative.
• The architectural choices that were made and the alternatives that were considered.
• How data sovereignty requirements influenced technology selection.
• Lessons learned around vendor lock-in, portability and future flexibility.
• The practical reality of balancing innovation, governance and cost.
• What surprised the project team during implementation.
• Which decisions they would make differently if they started again today.

You will leave with practical insights into how organizations can prepare for a future where AI capabilities, data control and strategic independence increasingly need to coexist.

Whether you work in data, analytics, architecture, governance or executive leadership, this session offers concrete lessons from an organization that successfully navigated these challenges in practice.

Many organizations are under pressure to become more data-driven and adopt AI. At the same time, concerns around data sovereignty, geopolitical risks, legislation, vendor lock-in and rising cloud costs are increasing.

The Koninklijke Notariële Beroepsorganisatie (KNB) faced a fundamental question:

How do we create a future-proof data and intelligence platform that enables advanced analytics and AI while maintaining control over our data, architecture and long-term choices?

In this session, KNB shares its real-world experience, including:

• The business and regulatory challenges that triggered the initiative.
• The architectural choices that were made and the alternatives that were considered.
• How data sovereignty requirements influenced technology selection.
• Lessons learned around vendor lock-in, portability and future flexibility.
• The practical reality of balancing innovation, governance and cost.
• What surprised the project team during implementation.
• Which decisions they would make differently if they started again today.

You will leave with practical insights into how organizations can prepare for a future where AI capabilities, data control and strategic independence increasingly need to coexist.

Whether you work in data, analytics, architecture, governance or executive leadership, this session offers concrete lessons from an organization that successfully navigated these challenges in practice.

Many organizations are under pressure to become more data-driven and adopt AI. At the same time, concerns around data sovereignty, geopolitical risks, legislation, vendor lock-in and rising cloud costs are increasing.

The Koninklijke Notariële Beroepsorganisatie (KNB) faced a fundamental question:

How do we create a future-proof data and intelligence platform that enables advanced analytics and AI while maintaining control over our data, architecture and long-term choices?

In this session, KNB shares its real-world experience, including:

• The business and regulatory challenges that triggered the initiative.
• The architectural choices that were made and the alternatives that were considered.
• How data sovereignty requirements influenced technology selection.
• Lessons learned around vendor lock-in, portability and future flexibility.
• The practical reality of balancing innovation, governance and cost.
• What surprised the project team during implementation.
• Which decisions they would make differently if they started again today.

You will leave with practical insights into how organizations can prepare for a future where AI capabilities, data control and strategic independence increasingly need to coexist.

Whether you work in data, analytics, architecture, governance or executive leadership, this session offers concrete lessons from an organization that successfully navigated these challenges in practice.