22-25 April 2026 
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SQLBits 2026
The Database Strikes Back: Reclaiming Power in the AI-First Architecture
AI empowers data professionals by bypassing middleware. Master governance, logic enforcement, and auditing to secure your role and regain architectural power from app developers.
Technology is constantly evolving, perpetually reshaping all job roles. This talk will discuss a major emerging architectural shift: how Artificial Intelligence (AI) is transforming data professional roles and explore what these careers will look like in the near future.
We will begin by reviewing the general technology job life cycle to establish a framework for understanding disruption. We'll then examine the underlying mechanics of modern AI applications—specifically, their interaction with databases—demonstrating their present functionality and anticipating their future capabilities. With that crucial context, we’ll discuss where current data roles are positioned on this cycle and contrast two possible, diverging future scenarios for data professionals.
Finally, we will dig into the technical aspects of the more empowered future and show that if we proactively navigate this new software landscape, we can successfully reclaim architectural control. This involves mastering new capabilities such as:
1. Granular Logic Enforcement: Ensuring the AI can only access and update data according to strict data governance policies and existing business logic rules.
2. Proactive Query Impact Analysis: Developing methods to understand and mitigate the performance impact of ad-hoc AI-generated queries on the database before they execute.
3. Data Transparency and Auditing: Guaranteeing complete visibility and accountability for all data access, including sensitive and personal data, for regulatory compliance and auditing purposes.
By mastering these challenges, we will demonstrate how data professionals can regain significant power from the application layer and application developers, positioning the database team as the central authority in the AI-driven enterprise.
We will begin by reviewing the general technology job life cycle to establish a framework for understanding disruption. We'll then examine the underlying mechanics of modern AI applications—specifically, their interaction with databases—demonstrating their present functionality and anticipating their future capabilities. With that crucial context, we’ll discuss where current data roles are positioned on this cycle and contrast two possible, diverging future scenarios for data professionals.
Finally, we will dig into the technical aspects of the more empowered future and show that if we proactively navigate this new software landscape, we can successfully reclaim architectural control. This involves mastering new capabilities such as:
1. Granular Logic Enforcement: Ensuring the AI can only access and update data according to strict data governance policies and existing business logic rules.
2. Proactive Query Impact Analysis: Developing methods to understand and mitigate the performance impact of ad-hoc AI-generated queries on the database before they execute.
3. Data Transparency and Auditing: Guaranteeing complete visibility and accountability for all data access, including sensitive and personal data, for regulatory compliance and auditing purposes.
By mastering these challenges, we will demonstrate how data professionals can regain significant power from the application layer and application developers, positioning the database team as the central authority in the AI-driven enterprise.