Agentic AI is a top priority, but scaling it is the biggest hurdle. While 93% of organizations are already developing or planning to develop their own custom AI agents, 90% report that their core AI agent use cases remain in pilot mode. The journey from pilot to enterprise production is stalled by several key challenges, including disconnected systems, talent gaps, high costs, and a lack of governance and security.
Agentic AI platform considerations
Taking a unified platform approach to agent development, orchestration, and governance can help overcome these challenges and realize the full potential of agentic AI. With this approach, teams can build AI agents and applications faster while maintaining quality, governance, and control. And enterprises can reduce redundancy and eliminate AI agent sprawl.
Getting started: How to build your agentic AI roadmap
This e-book is your guide to successfully moving from agentic AI pilots to full-scale enterprise production. Access foundational insights, strategies, and a roadmap to get started with agentic AI.
In this guide, you will learn how to:
- Understand agentic AI vs. generative AI: Learn the difference between generative and agentic AI and its four key functions.
- Address common challenges: Get an in-depth look at roadblocks like agent sprawl, developmental complexity, and talent gaps.
- Build an agentic AI framework: Follow a four-step readiness checklist to prepare your organization for agentic AI.
- Explore agentic AI use cases: See how agentic AI is being put to work where it matters most, across IT, customer service, operations, and beyond.
