As organizations move AI from experimentation into real-world use, the challenge is no longer simply what AI can do. It’s whether you can trust the outcomes it produces.
Dependable enterprise AI needs reliable information, meaningful context and the right controls around how data is accessed and used. Without that foundation, fragmented or poorly governed data can undermine the accuracy, explainability and reliability of AI-powered applications. This is closely aligned with current Progress Data Platform trusted AI positioning, which emphasizes unified data, semantic context and governance as the foundation for accurate and explainable AI outcomes.
What you will learn:
Why trusted data and context are critical to dependable AI outcomes
How semantic context helps AI understand meaning and relationships, not simply retrieve information
Why governance and access controls matter as AI moves into enterprise workflows
How organizations can establish a stronger foundation for trusted, explainable enterprise AI
The session is ideal for:
Leaders and teams responsible for trusted AI, data governance and enterprise decisioning, including:
- CIOs, CDOs, Heads of Data/AI & Enterprise Architects
- Risk, Compliance, Legal & Security Leaders
- Knowledge, Content & Information Management Teams
- Product, Engineering, Innovation & Data Platform Owners
View the webinar on demand!
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