Do you foresee Agentic AI being capable of self-healing test systems—automatically maintaining, repairing, or creating test cases without human input?
How can enterprises leverage agentic AI to self-optimize workflows and processes?
How do you architect recovery when an agent optimizes for local goals but harms global enterprise objectives?
What’s the right balance between architectural automation vs. requiring human approvals at critical checkpoints?
What are the important security aspects to be kept in mind for AI-Agents in Automation Pipelines for Enterprise?
What’s the right balance between AI autonomy and human-in-the-loop controls?
How should stringent adversarial testing strategies be designed and implemented to identify vulnerabilities and potential misuse of agentic AI by internal or external actors?
How can enterprises measure ROI of agentic AI beyond productivity gains?
What are the main considerations and challenges in integrating agentic AI with existing legacy systems and data infrastructure within an enterprise?
Should enterprises define a clear “AI Ethics Charter” for QA before scaling Agentic AI, just like they define coding or security standards?
How can organizations effectively design and manage human-in-the-loop mechanisms to ensure appropriate oversight and intervention capabilities for Agentic AI?
Considering the matter of scale, how should the implementation and refinement of agentic AI and automated testing processes differ between enterprise-level and SMB-level orgs?
Could agentic AI redefine business strategies faster than human teams?
How can agentic AI improve risk management and compliance guarantees?
If AI agents can negotiate goals among themselves, should enterprises let them?
What architectural trade-offs exist between centralized orchestration of AI agents vs. fully decentralized autonomy?
What architectural safeguards are needed to prevent autonomous agents from drifting away from enterprise-defined goals?
How can organizations ensure AI agents meet strict enterprise-level SLAs?
To the panelists: where and how have you fully integrated AI or Agentic AI in your projects that are live? Or is it just another buzz and yet to be implemented?
How do we balance autonomy vs. accountability when deploying agentic AI at scale?