Building Enterprise AI Agents, What Most Companies Still Get Wrong

About this episode

The episode discusses the complexities of building enterprise AI agents and the critical considerations for deployment and performance management.

Adi Kuruganti, Chief AI and Development Officer at Automation Anywhere, joins Amir to break down what it actually takes to build agents for the enterprise, not in theory, but in environments where complexity, governance, observability, and real business outcomes matter. This conversation gets into the part of enterprise AI that most people skip. Not just what agents can do, but what changes when you have to deploy them across regulated systems, measure performance in production, manage model drift, and rethink how product and engineering teams ship software. It is a smart look at where enterprise AI is going, and what technical leaders need to understand before the market catches up. What stood out • Enterprise agents are only as strong as their data, context, and deployment model. In large companies, that means dealing with hybrid environments, air gapped systems, privacy controls, and process level context, not just model quality. • AI is changing more than coding. Adi explains how his team is using AI across the full software development lifecycle, from spec creation and test generation to production event triage and release workflows. • The release process is shifting from…

People in this episode

Host: Amir

Guest: Adi Kuruganti

Topics covered

• enterprise AI
• AI agents
• software development lifecycle
• model performance
• governance
• observability

Keywords

• enterprise AI
• AI agents
• model drift
• software development
• observability
• security
• performance measurement

Mentioned in this episode

Organizations: Automation Anywhere

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