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Industry AI Programme

Team AI training for process clarity, productivity workflows, internal knowledge, and responsible review.

Beginner to team-readyScoped cohortTeams and organisations
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01 / OVERVIEW

What this programme is

The Industry AI Programme adapts Academy training for larger teams that need shared language, process clarity, and reviewable outputs.

The programme can frame productivity workflows, internal knowledge practices, research briefings, and simple operational prototypes without presenting training artifacts as production systems.

02 / WHO IT IS FOR

Built for the right context

  • Teams exploring practical AI productivity.
  • Managers who need shared AI usage norms and review checkpoints.
  • Organisations that want a scoped training brief before delivery.

03 / OBJECTIVES

What learners should leave with

  • Map where AI fits team processes and where review remains human.
  • Create reusable prompts and workflow notes for repeated team tasks.
  • Draft a simple internal knowledge or process artifact.
  • Review AI-assisted work before it becomes operational or public-facing.

04 / MODULE OUTLINE

Seven modules, summary only

M-01

AI Basics

Understand what AI can and cannot do before using it for real work.

  • Common AI uses
  • Human judgement
  • Safe first tasks
Safe-use checklist
M-02

Prompting

Give clearer instructions and review the result instead of accepting the first answer.

  • Prompt structure
  • Context and constraints
  • Review loops
Reusable prompt template
M-03

Workflows

Break a repeated task into steps where AI can help without taking over.

  • Task mapping
  • Drafting support
  • Human checkpoints
Workflow map
M-04

Research

Use AI to explore and compare information while checking sources and missing context.

  • Question framing
  • Source comparison
  • Briefing notes
One-page comparison brief
M-05

Build Practice

Turn the learning into a visible output, prototype, worksheet, tracker, or build-lab path.

  • Output selection
  • Build planning
  • First useful draft
Practical build artifact
M-06

Review And Safety

Check AI output for mistakes, privacy risk, weak claims, tone issues, and missing review.

  • Accuracy checks
  • Privacy awareness
  • Share-readiness review
Review checklist
M-07

Final Project

Package one useful result and explain what was made, how it was checked, and what comes next.

  • Project story
  • Evidence of work
  • Next improvement
Final project story

05 / DELIVERY

How it runs

  • Delivery is scoped around team size, workflows, data boundaries, and facilitation needs.
  • Training uses sample, public, sanitized, or approved data only.
  • Outputs are treated as drafts, prototypes, or training artifacts unless separately validated.

06 / NEXT ACTION

Review the path, then choose the right next step.

Public pages stay at overview level. Academy learning surfaces hold the actual lessons, labs, and resources.

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