Creating AI agents is easier (and faster) than you think

This year, the conversation in the C-suite has shifted from agentic AI to, “How do we make AI work safely, repeatedly, and at scale?” The answer lies in AI agents, autonomous or semi-autonomous systems that don’t just chat, but reason, plan, and execute multi-step tasks across your enterprise ecosystem.

For many CIOs, the perceived barrier to agentic AI is a mountain of custom coding and infrastructure complexity. But thanks to the deep co-engineered innovation between HPE and NVIDIA, that mountain has become a molehill. By leveraging the HPE AI factory with NVIDIA, building and deploying production-ready agents is now a matter of clicks, not months.

The shift from chatbots to intelligent agents

While first-generation AI focused on single-turn interactions, like a basic chatbot answering a question, agentic AI represents a fundamental evolution. An agent can:

• Reason: Break down a complex goal (“Optimize our Q3 supply chain”) into actionable steps.
• Use tools: Access your SQL databases, ERP systems, or external APIs to pull real-time data.
• Act: Execute the final task, such as generating a purchase order or updating a CRM entry.

Making it practical: The blueprint approach

The secret to speed is not building from scratch; it’s building on what is already proven.  NVIDIA’s NIM Agent Blueprints provide preconfigured, reusable reference workflows for common enterprise use cases, with the required microservices sample code and deployment guides built-in.