AGSM9165 · Intensive 2 · Teaching Plan

Workshop Plan
INT 2

📋 2 Days · 4 Units © Lamont Tang, 2026 — modified from a workshop plan by Assoc. Prof. Dirk Primus
Day 1
AI Readiness, Adoption
& Governance
7
AI Readiness and Leading AI Adoption, Transformation and Assimilation
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Open: What characterizes an AI-first organization? — Student whiteboard brainstorm + instructor framing (BoG gif)
9:00–10:00am
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Instructions

  • Ask students what they believe characterizes an AI-first organization
  • Ask students to record thoughts on whiteboard
  • Note that "AI-first org" is a contested term in the community
  • Instructor may inject humor with BoG gif on slide #2
  • Note this workshop segment will focus on AI readiness towards successful assimilation
  • Briefly introduce the Cisco assessment tool
  • Ask students to complete the Cisco AI Readiness assessment for their project org (15–20 min. to complete)
  • Ask for 2–3 examples to be shared & reflect
  • Briefly revisit the TAM & TOE on slide 4 as established technology management frameworks for assessing adoption readiness (discussed in depth in AGSM9154, Unit 2)

Resources / Materials

  • 🎞 Gif on slide #2
  • 📱 QR code for Cisco AI Readiness Assessment on slide #3
  • 📊 Slide #4: TAM & TOE frameworks
☕ Morning Break — 10:00–10:15am
Organizational Barriers to AI Adoption — Socratic discussion on typical blockers + student experiences
10:15am–11:00am
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Instructions

  • Quickly introduce the contrast between adoption, assimilation and effective transformation
  • Socratic discussion with entire room: What are typical barriers that block AI transformation?
  • Ask students to contribute examples/experiences from their personal orbit

Assigned Reading

  • 📖 Li, Zhu & Hua (2025). "Overcoming the Organizational Barriers to AI Adoption." Harvard Business Review, November 11, 2025 — assigned in prep announcement >2 weeks before workshop
Managing AI Adoption with Guiding Principles — Group activity: shared canvas output
11:00am–12:00pm
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Instructions

  • Introduce the case/context on slide 8
  • Introduce the workflow of activity on slide 9 (10–15 min. to complete)
  • Invite 2–3 groups to share and reflect

Tools & Output

  • 🛠 Any GenAI system: ChatGPT Copilot Gemini Claude
  • 📋 Output: One shared canvas (slide / whiteboard / Miro-style page)
🍽 Lunch — 12:00–1:00pm
6
Governance & Responsible AI
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Open after lunch: Governance as competitive edge — student reaction to statement + Simple Rules video activity
1:00–2:00pm
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Instructions

  • Open: "Organizations with superior governance have a competitive edge because…" — let students respond/react (10 min)
  • Active listen and think activity: How can governance choices be articulated as simple rules that translate into competitive advantage?
  • Play video from lectern
  • Students have 8 min. to listen, think and take notes; then collaborate, consolidate (5–10 min.) and present
  • Show the recommended output format
  • Revisit the Australian VAISS — compare with your simple rules logic from before

Resources / Materials

Case Discussion: Will Microsoft's responsible AI governance be a sustainable competitive advantage?
2:00–2:30pm
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Discussion Questions

  • Will Microsoft's responsible AI governance be a source of sustainable competitive advantage? Why or why not?
  • Are principles translated well into everyday practice (ref. VAISS)?

Assigned Reading

Global governance: Should an IAEA-like agency manage advanced AI? Socratic discussion on nuclear governance transferability
2:30–3:00pm
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Discussion

  • Proposition: An IAEA-like agency to manage advanced AI should be created
  • Do you agree? Which nuclear governance mechanisms are transferable, and which are not?
  • Socratic discussion

Assigned Reading

☕ Tea Break — 3:00–3:15pm
Feedback rounds for Assessment 2, Part B — Group feedback clusters + coaching
3:15–4:30pm
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Instructions

  • Group students in accordance with their feedback clusters (5–10 min. set up with record)
  • Facilitate conversation and coach teams

Materials

  • 💻 Moodle/LMS feedback workshop
Wrap-up: What needs to be unlearned for effective AI use? Bridge to Unit 8
4:30–4:45pm
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Instructions

  • Quick wrap-up discussion and bridge to Unit 8 (skills & talent)
  • What needs to be unlearned for effective AI use? Use your own professional orbit as context.
Day 2
Talent, Agents, Ethics
& Portfolios
8
AI Talent, Agents and Ethical Implications
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Blackout Exercise: Sensemaking — Deliberate critique of the AI-first idea using BCG deck slides
9:00–10:00am
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Instructions

  • A deliberate critique of the AI-first idea
  • Assign slide #3 to half of the students, slide #13 to the other half
  • Instructions are on slide #2
  • Present 2–3 examples from each group

Materials

  • 📄 Handout or send out slide #3 (the operating model) from the BCG deck
  • 📄 Slide #13 (AI-first journey) from the BCG deck
☕ Morning Break — 10:00–10:15am
Skills-building in AI context via Socio-materiality perspective — 5 capabilities, student probing + animated suggestions
10:15–10:45am
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Instructions

  • Step through each capability (5 total) and probe students for appropriate skills-building mechanisms
  • Suggestions for skills-building mechanisms enter each slide as animation (click to enter)

Assigned Readings / Resources

How will a typical MBA graduate interact with Agentic AI? — Microsoft supply-chain example + reflection
10:45–11:15am
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Instructions

  • Using the Microsoft 'best in class example', facilitate a quick reflection on what agents do not decide and what that means for how a typical MBA graduate will likely interact with agentic AI
  • Show the slide after the discussion

Assigned Reading

Optional: CV exploration loop-back from INT1 → Johari window & self-discovery; "Philosophy eats AI" key tenets
11:15–11:30am (if time)
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Instructions

  • If there is time: loop back to the CV exploration from INT1; what did you learn? Connect it to the Johari window & opportunities for self-discovery
  • If there is time: quickly introduce the key tenets of "Philosophy eats AI" and the implications for human skills building

Materials

  • 📊 Key tenets featured on slide #12
9
Managing AI Use Case Portfolios and Investments
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Intro: Import from cross-industry innovation; House of Frames (JBTD × Tech Affordances) activity + use-case mapping
11:30am–12:00pm
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Instructions

  • Briefly mention the "import" process from X-industry innovation; in this and previous units we apply principles to introduce adapted, established, durable frameworks of technology management
  • Start with feeding the funnel & selection of problem/opportunity combinations ("frames") to create use cases with an optimal 'blast radius'
  • Explain the dimensions of the house of frames and the fundamental logic (scoring, matching, clustering)
  • Activity: identify 10 JBTD and 10 Tech Affordances from your professional orbit, matrix them and score their interaction (15–20 min.)
  • Present 2–3 examples
  • Explain how use cases can be mapped and selected based on desirability, viability and feasibility

Assigned Readings

🍽 Lunch Break — 12:00–1:00pm
Balanced investment portfolio — Hayes-Wheelwright matrix + activity: chart 20 use cases
1:00–1:30pm
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Instructions

  • Discuss planning (the mix in) the funnel to a balanced investment portfolio (risk/reward)
  • Introduce the adapted Hayes-Wheelwright matrix
  • Activity: ask students to chart their well-balanced portfolio of 20 use cases (5–10 min.)
  • Present 2–3 examples
Selection via NPV/IRR and uncertainty — "Tomato Garden" real-options logic; development funnel + Agile discussion
1:30–2:15pm
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Instructions

  • Discuss selection/advancement based on NPV/IRR and uncertainty → the Tomato Garden
  • Invite students who know real-options logic to explain the idea
  • Discuss managing the funnel like a development funnel: decrease No's with increase in expenditure/progress
  • Include iteration loops
  • When architectures are modular, requirements uncertain/shifting, speed is required — consider Agile development
  • Invite students who know Agile to elaborate
Metrics & ROI — Value philosophy: C, V, WTP framework; students select metrics for their project
2:15–3:00pm
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Instructions

  • Discuss metrics/estimating and measuring outcomes in practice
  • Provide a short overview of the philosophy: value can come in many forms; value can be translated into ROI via C, V, WTP
  • Let students select metrics for their project

Assigned Reading

☕ Tea Break — 3:00–3:15pm
10
Creating National and Cross-Border AI Advantages
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Porter's Diamond vs. National Innovation Systems (NIS) — Quick contrast + probe & reveal
3:15–3:30pm
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Instructions

  • Introduce a quick contrast: Porter's Diamond vs. National Innovation Systems (NIS)
  • Instructor can probe and reveal, or reveal and ask for examples
Small group activity: Strategic Implications — Complete table with one Simple Rule per area (ref. Unit 6 Governance)
3:30–4:15pm
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Instructions

  • Small group activity: Strategic Implications
  • Groups complete the table on slide 3 with one Simple Rule (introduced in Unit 6 – Governance) per area (approx. 15 min. work time)
  • Share & reflect (in the room)

Materials

  • 🖊 Whiteboards / Flipcharts, Markers
Optional: Apply NIS to Switzerland's "Apertus" AI ecosystem — Will Apertus be a source of national AI advantage?
4:15–4:45pm (if time)
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Instructions

  • If time permits: apply NIS to the case of Switzerland and its "Apertus" AI ecosystem (approx. 10 min. read)
  • 15–20 min. Socratic discussion: Will Apertus be a source of national AI advantage for Switzerland?

Resources

Workshop wrap-up and room clean up (10–15 min)
End of Day
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Instructions

  • Workshop wrap-up
  • Room clean up (10–15 min)
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