AI agents are moving beyond basic automation and reactive interactions to support more complex enterprise workflows. Advances in foundational models and computing power are enabling AI systems to process large volumes of information, interact with multiple data sources, and execute tasks within defined boundaries.

For enterprises, this shift is particularly relevant because employees often spend significant time collecting information from different applications, processing data, and following established workflows. Agentic AI can connect these activities and support faster execution while keeping human review within the process where required.

In this episode of the Analytics Insight Podcast, Priya Dialani speaks with Vikram Jeet Singh, Partner at BTG Advaya, to examine how agentic AI is changing enterprise workflows, where organizations can apply these systems, and what businesses need to prepare before deploying them at scale. Here are the excerpts of the interview:

I see generative AI as largely reactive. We ask it a question or give it a prompt, and it provides an answer. It is extremely useful for creating content, summarizing documents, answering questions, and supporting productivity.

Agentic AI adds another dimension. I see it as an extension of generative AI where the system understands an objective, plans the required actions, interacts with different information sources, and completes multiple tasks within defined boundaries.

The system can work with databases and enterprise applications, make decisions based on established rules, and execute one step after another. It can also be designed to return to a human or analyst for confirmation when necessary. That is what makes agentic AI more applicable to complex enterprise workflows.

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