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The world is being transformed by artificial intelligence (AI). Many businesses and industries are implementing this technology to improve predictability, streamline processes, and stay ahead of the competition. But introducing AI software and practices isn’t always easy.

In this course, you will learn how to successfully integrate AI into any organization. You’ll learn how to determine whether your organization could fully benefit from AI, as well as the technical capabilities necessary for deployment. You’ll learn how to perform business analysis and present a case for implementation.

Further, you’ll learn project management best practices to help install AI successfully. You’ll use the Scrum framework to build and deploy AI and to maintain the system when in production to collect data and model scenarios.

AI Project Management: Deploying and Maintaining AI for Business

# Stages of the AI journey

Companies need to evaluate where they are along the AI journey before moving on to the next stage. We’ve divided the AI journey into four stages:

1. The descriptive AI stage

2. The diagnostic AI stage

3. The predictive AI stage

4. The prescriptive AI stage 

As we go through these stages, we further develop our AI practice. The less time we spend acquiring data and the more time we spend analyzing and acting on it, the more developed our AI practice becomes.


# Descriptive AI stage

The foundation of AI is descriptive analytics. In this stage, vital business data is recorded, but it can only tell us what happened. In descriptive analytics, data is gathered to identify trends, but the machine cannot make decisions based upon that data yet.  

What’s the best way to tell if we’re still in the descriptive AI stage? There are a few clear indications. Normally, business stakeholders rely on business intelligence, which is primarily concerned with regularly reporting previous performance to business leaders.




Let’s learn about the first stage of AI.

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AI Stage Evaluation: Part 1

Stages of the AI journey