Workshop contents
Session 1 · Overview
How AI Works in Business
From Prompt to Governed Decision
Session 1 shows how AI becomes useful in a business setting. We start with a simple prompt, then add the things a company needs before AI can support a real decision: context, tools, monitoring, guardrails and human approval.
What AI Needs to Be Useful
The session moves through the main capabilities that turn AI from a chatbot into something a business can rely on.
| Capability | What it gives the business |
|---|---|
| Prompt Engineering | A clearer question, so the answer is easier to use. |
| Context Engineering | Company rules, targets and history, so the answer fits the business. |
| Workflows and Tools | Access to data, charts and drafts, so AI can help produce the work. |
| Agentic AI | Scheduled monitoring, so AI can check for problems without waiting for a prompt. |
| Guardrails and Human Authority | Decision limits and approvals, so the company stays in control. |
The Business Example
The examples use DataCo supply chain data, where many orders arrived late. The important lesson is not the dataset itself. The important lesson is how the AI answer changes when the business gives it better instructions, better context and clearer decision limits.
Core ideaThe same AI and the same data can produce a weak answer, a better analysis, or a decision-ready recommendation. The difference is what the business gives the AI to work with.