Models, Tools, and Products: Stop Mixing Them Up

AI models vs tools for business leaders: models, products, and workflows explained in plain English. A practical AI implementation guide that clarifies the difference between AI models, tools, and products—and how real AI workflows actually work. Walk away knowing how to evaluate AI products, ask better vendor questions, and reduce AI risk and compliance surprises.

What You'll Learn:

• Understand the core difference between an AI model, an AI tool, and an AI product—and why mixing them up causes confusion and bad decisions.
• Map out a simple AI workflow for your own business, from raw data input through models, products, and guard-rails to business outcomes.
• Use clear questions to separate vendor marketing from reality so you know exactly what you’re buying (model vs product vs full workflow).
• Spot when procurement, IT, or the business is blaming the wrong layer—model, product, or workflow—for an AI failure or limitation.
• Identify where risk, compliance, data protection, and quality controls actually live in the stack so you can design practical safeguards.
• Apply three memorable analogies that make it easy to explain AI models vs tools to non-technical stakeholders and your leadership team.
• Recognize four common misconceptions about AI capabilities that lead to overpromising, under-delivery, and poorly scoped AI projects.
• Turn today’s episode into action by documenting your own landscape of models, tools, and products—and choosing one small experiment to run this week.