How to Design Application Automation for Agentic AI

• Identify the execution-layer dependencies that determine whether AI agents can operate reliably across enterprise applications.

• Assess automation readiness by evaluating governance, integration, observability, failure-handling and recovery capabilities

• Distinguish between AI capabilities that interpret and recommend actions and automation capabilities that execute and control business processes

• Design governed execution capabilities that enable reliable agent behavior while reducing operational risk
  
  

Application architects are under increasing pressure to deploy AI agents across CRM, ERP and other enterprise applications. However, many initiatives struggle because the underlying automation foundation is fragmented, insufficiently governed or not designed for agent-driven execution. In many cases, automation maturity, not AI sophistication, determines whether agents can execute work reliably at scale.

This webinar explores the execution layer behind agentic AI, including workflows, integrations, governance controls and recovery mechanisms. Learn how to assess automation readiness, identify architectural gaps and strengthen the governed execution capabilities that enable reliable, scalable and controlled AI agent behavior across enterprise systems.

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