Prathap Raghavan

As agentic AI systems take on more complex decision-making and autonomous workflows, trust becomes a critical success factor. If employees can’t understand why an agent made a decision or leaders can’t validate its reasoning adoption stalls, risk increases, and AI value erodes. Break down strategies for designing transparent, auditable, and trustworthy agents that operate confidently in enterprise environments.

• Techniques for rendering agent decision paths transparent and interpretable
• Methods for validating autonomous reasoning and minimizing hallucinated logic
• How to build confidence scoring and explainability into workflows
• Frameworks for user trust, audit trails, and chain-of-accountability
• Ways to provide guidance without over-controlling or slowing agents
• Organizational strategies to increase trust and adoption across teams