The fundamental promise of artificial intelligence (AI) is to enable innovation. You have identified how you want to apply AI, you’re eager to execute, but how do you know which AI strategy is right for your context? Are you capable of picking the right AI tool for the job, or are you merely following the herd over the large language model (LLM) cliff?

The appropriate application of AI is a critical goal of all modern enterprises. In machine learning (ML), artificial intelligence (AI) models are created by training an AI algorithm on data. Due to the overwhelming market hype, most organizations equate AI to LLMs such as Claude, GPT, Gemini, or DeepSeek. But LLMs are just one of many AI options available to you. There are dozens more; how do you pick the right one(s)?

In this talk, Scott will work through:

• How ML-AI models are created from data and algorithms.
• When LLMs make sense and when they don’t.
• Common AI use cases and the applicable algorithms.
• When to apply non-ML strategies.

Learning Objectives:

• Understand how business process analysis fits into the AI-development lifecycle
• Discover how to identify the right AI algorithm(s) for your context
• Explore how predictive AI and generative AI are required for most business solutions