Implementing agentic AI

- When it comes to implementing AI agents in organizations, the biggest mistake many make is to start with technology instead of strategy. It's critical to evaluate how AI agents can support your broader business objectives by looking at the three biggest strategic imperatives for your organization. The first step is asking what are the biggest roadblocks, or the biggest opportunities that exist in your strategies. Explore areas where AI agents could unlock obstacles or enable efficiency and scale to support these strategic initiatives. Define the expected outcomes from your AI agents. Linking agentic AI to strategic objectives is a crucial step because you'll be asking for significant resources and investments to develop AI agents. You must build a compelling business case for agentic AI from the start. Otherwise, it will never get off the ground. Small individual use cases won't get you the resources you need for AI agents to make a difference. Second step is to assess your data, tech, and team for readiness. Begin by assessing your existing data. As you saw earlier, every single type of AI agent relies on having clean, formatted data. The assessment process may identify the need to resolve data inconsistencies or combine data from multiple sources. The third step is selecting AI agent platforms and solutions tailored to your industry or function. As you can imagine, there are already hundreds of AI agent solutions and software available. Narrow your options by understanding the six types of AI agents we covered, and identify the type of agent you need to solve the problem at hand. When selecting an AI agent software, also consider compatibility with your current systems and also integration difficulties, scalability, and of course, support. You also need to prepare to train and monitor your AI agents. This means having clear definitions of success, especially metrics of accuracy and quality. Other metrics to consider include response and processing time, user satisfaction, cost savings, and even revenue generation potential. That's a quick overview of how to approach implementing AI agents. Join me in the next video as we address common agentic AI challenges.