Agentic AI is becoming a reality for enterprises. In this webinar, Chanda Nsofu (Detecon) and Laurel Phelan (Orbus Software) explore how Enterprise Architecture Management can serve as a governance layer, define guardrails and accountability, prioritize high-value use cases and scale AI initiatives while balancing control, innovation and business value.
EAM meets Agentic AI
Discover how EAM can govern, enable and scale Agentic AI.
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More InformationHow EAM can govern and scale Agentic AI.
EAM as a governance layer
Enterprise Architecture Management can play a central role in governing Agentic AI. The webinar shows how architectural transparency can help organizations assess AI initiatives, make dependencies visible and integrate governance into existing decision-making structures.
Guardrails & accountability
Agentic AI requires clear guardrails, accountability and decision rights. The experts discuss how organizations can define boundaries for autonomous AI agents while maintaining room for innovation.
Prioritize AI use cases
Not every AI use case creates the same value. The webinar shows how organizations can assess potential Agentic AI applications, prioritize them by business value and identify suitable areas for further implementation.
Innovation & governance
Scaling Agentic AI requires a balance between innovation, governance and business value. Detecon and Orbus share practical perspectives on how organizations can maintain control while creating the foundations for scalable AI initiatives.
FAQs on Enterprise Archtecture Management and Agentic AI.
What is Agentic AI?
Agentic AI refers to AI systems that can act with a higher degree of autonomy to pursue defined goals and support decisions or processes.
Why does Agentic AI need governance?
As AI systems become more autonomous, clear accountability, decision rights, guardrails and transparency become increasingly important.
