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Beyond the Prompt: Governing AI-Extracted Data
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Waterfall Project Management
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Biopharma Data Governance Solutions
Healthcare Data Governance Solutions
Tech & Software Data Governance Solutions
Solutions
Turnkey Portfolio Management
Project Portfolio Management Solutions
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Lineage
SOPs
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Healthcare
Technology
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Beyond the Prompt: Governing AI-Extracted Data
All Articles
FAQS
AI
AI Data Governance
Governance vs. Data Governance
How Do AI Functions Access Governed Data
Selecting AI Governance Frameworks
Governance Frameworks Compared
Data Governance
Data Governance
Why is Data Governance Important
Data Governance in Healthcare
Data Governance Framework
Data Access Governance
Data Governance Policy
Data Governance Tools
Data Lineage in Data Governance
How to Implement Data Governance
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AI Stewardship in Regulated Industries
Running Time: 42 min
Webinar
·
May 08, 2026
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Overview
Chapters & Timestamps
Interactive Transcript
0:00
Welcome to the StewardIQ deep dive on the Intelligent Data Management Cloud.
0:12
In the next forty minutes we'll walk through the auditability problem that every regulated AI program runs into.
0:34
Most teams treat prompts as ephemeral. We're going to argue that the prompt itself is the new control point.
1:02
We'll show how prompt capture becomes evidence, how model version locking prevents silent drift, and how stewards stay accountable.
1:50
Let's start with a story from a top-five life sciences customer who shipped a Part 11 AI workflow in nine weeks.
2:48
The pattern they followed is the same one we'll generalize today: name the human, capture the prompt, lock the model.
4:00
Now, on to the architecture. The reference design centers on a steward control plane sitting beside the model gateway.
5:20
When a model output is generated, the system writes a tamper-evident signature record into the governance ledger.
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