Module 2 · What
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Section 2 · What Makes AI Decision-Ready?

What is Decision Intelligence?

Module 2 of 2 · 11 micro‑lessons · ~40 minutes

Welcome

Now that you've seen why more information isn't enough, this module gives you every building block that makes AI genuinely decision-ready — evidence, reasoning, judgement, guardrails, context engineering, and the lifecycle behind every template you'll use next.

Today's Objectives

  • Define Decision Intelligence in one clear model
  • Apply the Evidence → Reasoning → Judgement framework
  • Understand Guardrails and the four decision-ready capabilities
  • Learn the RGCTO context-engineering structure
  • Understand the Discover → Diagnose → Decide & Deliver lifecycle
"By the end of this module, you'll have every building block you need to begin the Decision Journey — starting with Template 1: Decision Framing."
Lesson 2.1

What Is Decision Intelligence?

~4 min · Learn → See

Learn

Decision Intelligence combines: information, human judgment, data and evidence, AI-assisted reasoning, guardrails, and structured decision processes — to improve decision quality and business outcomes.

See
Information Insight Decision Outcome

"Decision Intelligence turns information into action."

Lesson 2.2

From Information to Decisions

~5 min · Learn → See → Reflect

Learn

Good decisions require both evidence and reasoning. AI helps us gather evidence and structure reasoning. Humans apply judgment.

See
AI RoleQuestionDecision Value
Information PartnerWhat do we know?Gathers and organises evidence
Thinking PartnerWhat does it mean?Supports reasoning and evaluation
Human Decision-MakerWhat should we do?Applies judgment and accountability

Which of these three roles does your organisation lean on most heavily today?

Lesson 2.3

Evidence, Reasoning and Judgment

~6 min · Learn → Try → Reflect

Learn
LayerQuestionMain Actor
EvidenceWhat do we know?AI as information partner
ReasoningWhat does it mean?AI as thinking partner
JudgmentWhat should we do?Human decision-maker
Try

Classify: "Conversion fell from 24% to 18%" · "Staff are likely too stretched to close sales" · "We should hire two more floor associates per store." (Evidence, reasoning, or judgment?)

❓ Reveal answer
"Conversion fell from 24% to 18%" — Evidence.
"Staff are likely too stretched to close sales" — Reasoning.
"We should hire two more floor associates per store" — Judgment.

"Evidence informs. Reasoning interprets. Judgment decides." Evidence + Reasoning + Judgment = Better Decisions.

Lesson 2.4

Guardrails Make AI Decision-Ready

~5 min · Learn → See

Learn

AI outputs must be challenged before being used for decisions. Decision-ready AI should check:

  • — What is assumed?
  • — What is unsupported?
  • — What evidence contradicts this?
  • — What bias may be present?
  • — What could be hallucinated?
  • — What needs human approval?
See
Critique Validate Oversight

"Trustworthy AI decision support requires critique, validation and human oversight."

Lesson 2.5

What Makes AI Decision-Ready?

~5 min · Learn → See

Learn

AI becomes a decision partner when four capabilities work together.

See
CapabilityPurpose
ContextHelps AI understand the decision situation
EvidenceGrounds recommendations in data, research and documents
ReasoningConnects facts to explanations, options and trade-offs
GuardrailsChecks assumptions, hallucinations, bias and risks

"AI becomes decision-ready when supported by context, evidence, reasoning and guardrails."

Lesson 2.6

Evidence Powers Better Decisions

~5 min · Learn → See

Learn

Different decision questions require different evidence sources.

See
Evidence needBest source
Concepts and definitionsPretrained knowledge
Recent developmentsWeb search
Complex external investigationDeep Research
Internal documentsNotebookLM / Projects
Business performanceInternal data / dashboards
Customer signalsFeedback, reviews, support tickets

"Better evidence improves decision confidence."

Lesson 2.7

From Possibilities to Decisions

~5 min · Learn → See

Learn
AI Thinking ModePurposeDI Use
BrainstormingExpand possibilitiesGenerate causes and options
ReasoningEvaluate possibilitiesTest evidence and trade-offs
JudgementChoose responsiblyDecide what to do
See
Evidence Interpretation Options Trade-offs Recommendation

"AI becomes useful for decisions when it supports structured reasoning."

Lesson 2.8

Context Powers Better Decisions

~5 min · Learn → See → Try

Learn

Modern AI depends less on prompts and more on context.

See
Poor context

"How do we improve sales?"

Better context

Traffic is increasing. Conversion is declining. CSAT is falling. Customer complaints mention waiting time and stock-outs. Budget is constrained.

"Better context produces better reasoning."

Lesson 2.9

Context Engineering with RGCTO

~6 min · Learn → Try → Use AI

Learn

Prompting is how we ask. Context engineering is how we make AI decision-aware. RGCTO is the reusable structure used across every template in this course.

Role
What lens should AI use?
Goal
What decision outcome is needed?
Context
What situation, constraints and evidence matter?
Tasks
What reasoning steps should AI perform?
Output
What decision deliverable is required?
Lesson 2.10

The Decision Intelligence Lifecycle

~5 min · Learn → See

Learn

Every decision moves through three stages. This lifecycle is the backbone of the six templates you'll use next.

See
Discover
Frame & assess
Diagnose
Identify & validate causes
Decide & Deliver
Evaluate & build the plan

"Decision Intelligence converts business questions into structured decision outputs."

Lesson 2.11

From Thinking Activities to Decision Templates

~4 min · Learn

Learn

These templates teach AI how to think. Each template supports a different decision question — Frame → Assess → Explain → Review → Decide → Execute.

1. Frame
Decision Framing
2. Assess
Situation Assessment
3. Explain
Root Cause Analysis
4. Review
Critical Review & Evidence Validation
5. Decide
Options Assessment
6. Execute
Executive Action Plan
Ready for the Decision Journey?
0/4
Hands-on Activity

Build an RGCTO Prompt

Time: 8 minutes · Apply the Role–Goal–Context–Tasks–Output structure to BeautyCo.

Your Turn: Build the Prompt

Fill in each field, then generate your RGCTO prompt.

RGCTO Prompt

Copy this into ChatGPT or Gemini and compare with an unstructured prompt
Fill in the fields on the left, then click "Generate RGCTO Prompt."
Wrap-Up

Key Takeaways & What's Next

Key Takeaways from What

  • Decision Intelligence = judgement + evidence + AI reasoning + structured process
  • Every claim is Evidence, Reasoning, or Judgement — know which
  • Guardrails check assumptions, bias and hallucinations before you trust an output
  • RGCTO makes any prompt decision-aware, not just well-written
  • Every decision moves through Discover → Diagnose → Decide & Deliver

Coming Up: The Decision Journey

  • Template 1: Decision Framing (ChatGPT/Gemini)
  • Template 2: Situation Assessment (NotebookLM + Colab)
  • Templates 3–4: Root Cause & Evidence Validation
  • Template 5: Options Assessment (+ Google Sheets)
  • Template 6: Executive Action Plan
Appendix

Key Terms Made Simple

A plain-language glossary for Module 2

RGCTO
Role, Goal, Context, Tasks, Output — the five-part structure that turns a prompt into a decision-ready request.
Evidence
A verifiable fact — "conversion fell from 24% to 18%."
Reasoning
An interpretation of evidence — "this suggests understaffing," not yet proven.
Judgement
A decision or action based on evidence and reasoning — "we should hire two more associates."
Guardrails
Checks for assumptions, bias, hallucinations and risk before trusting an AI output.
Lifecycle
The three stages every decision passes through: Discover, Diagnose, Decide & Deliver.
Template
A repeatable structure (prompt + evidence + tool) used to complete one stage of the lifecycle.
Knowledge Check

Test Your Understanding

Covers Module 1 (Why) and Module 2 (What) · 6 questions · ~5 minutes

1. What is the real gap Decision Intelligence addresses?
2. Which AI role best describes NotebookLM in this course?
3. "We should hire two more floor associates per store" is an example of:
4. In RGCTO, what does the "C" stand for?
5. What is the main purpose of Guardrails?
6. What are the three stages of the Decision Intelligence lifecycle, in order?
Begin the Decision Journey: Template 1 →
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