Course Name: Leading Through AI™ Subtitle: Define. Discover. Design. Develop. Demonstrate. Framework Label: The 5D Model Format: Half-day (3h 45m) workshop + self-paced AI-integrated on-demand Status: Buildable specification — all downstream deliverables (deck, videos, app, facilitator guide, landing page, assessment, certification) are built from this document. Date: March 2, 2026 Authors: Tim Clark Sr. & Tim Clark Jr.
LeaderFactor's 7th signature course: a half-day workshop and self-paced on-demand product that teaches leaders how to lead in a world where machines can think. Supported by a proprietary assessment (the AI Leadership Index™), five tangible deliverables (one per module), and an 8-week post-course reinforcement system. In both modalities, an AI Thinking Partner coaches participants through exercises — the medium IS the message.
Organizations are spending $1.5 trillion annually on AI while 42% abandon most initiatives before production and only 1% of leaders report reaching AI maturity. The bottleneck is not technology. It is leadership. This course is the first dedicated, framework-driven experience that teaches leaders how to lead through AI — not how to use AI tools that change every quarter.
The course is marketed on adoption pain and built on permanent transformation.
The buyer — a CLO, CHRO, or business leader — purchases a solution to the AI adoption problem that is visibly costing their organization time, credibility, and money. That is the front door: "Your AI initiatives are failing because your leaders don't know how to lead through this."
The participant, once inside, discovers something larger. The 5D Model moves them from audit through possibility through architecture through people to evidence. The buyer purchases an adoption solution. The participant receives a leadership transformation. Both get what they need.
The course content is the same regardless of delivery modality. Learning objectives, frameworks, exercises, and deliverables do not change. What changes is the delivery mechanism:
| Element | On-Demand | Facilitated Workshop |
|---|---|---|
| Teaching delivery | Video (Tim Jr. on camera) | Deck + facilitator narration |
| Exercise coaching | AI Thinking Partner (primary) | Facilitator-led + AI Thinking Partner (supporting) |
| Pair/group work | AI simulates debate partner | Live pair and group discussions |
| Pacing | Self-paced, 4-6 sessions over 1-3 weeks | Single half-day session (3h 45m) |
| Artifacts | Digital (in-app, downloadable PDF) | Physical + digital |
| Energy management | AI session pacing + break nudges | Facilitator reads the room |
The AI Thinking Partner is present in both modalities. In on-demand, it is the primary coaching mechanism. In facilitated workshops, it supports exercises — participants interact with it during structured activities while the facilitator manages the room.
The deck serves both: it is the visual backbone of the teaching videos (on-demand) and the facilitator's delivery tool (workshop).
Devices in the room: Participants bring laptops or tablets to facilitated workshops — standard practice across all LeaderFactor signature courses. The digital workbook (exercises, AI Thinking Partner, artifact capture) runs in-browser. Wifi is required. The AI Thinking Partner is available during exercises; the facilitator manages the room, pacing, and discussion while participants interact with AI during structured activities. The balance between facilitator-led discussion and AI-supported individual work will evolve with delivery experience.
"AI is the great distiller. It strips away everything that was never truly leadership — and reveals what is."
This is the lean-forward sentence. It inverts expectations. An AI leadership course should talk about what AI adds. This one talks about what AI strips away. The metaphor is vivid (distiller), the claim is unexpected (AI helps, not hurts), and it resolves emotionally (liberation, not loss).
AI is the first technology that automates cognition — the thing leaders were told was their irreducible value. Previous technologies automated physical tasks (assembly line), distance (internet), or arithmetic (spreadsheets). A leader could always say: "But I still think." AI challenges that claim — not because it thinks better, but because it thinks at all.
This creates an identity crisis unlike any prior technology wave. Leaders aren't just losing tasks. They're losing the basis for their self-concept as leaders.
But the crisis has a resolution: the parts of leadership that AI replaces were never the real job. Information aggregation, report synthesis, status tracking, routine decision-making — these occupied 50–70% of a typical leader's week. They were important. They needed doing. But they were never leadership. They were scaffolding.
What remains after AI strips away the scaffolding is the essence: creating meaning, exercising judgment in ambiguous situations, building trust that allows teams to navigate uncertainty, and designing how human effort creates value. That's the real job — the job most leaders have been doing only partially because they were buried in noise.
| Before the Course | After the Course |
|---|---|
| "AI is a threat to my relevance" | "AI clarifies my relevance" |
| "I need to learn AI tools" | "I need to lead the human-AI partnership" |
| "AI is a technology problem for IT" | "AI is a leadership problem for me" |
| "My value is what I know" | "My value is what I decide, design, and develop in others" |
| "I need to protect my team from AI" | "I need to create safety for my team to experiment with AI" |
| "I'm overwhelmed and don't know where to start" | "I have a framework, five deliverables, and a 90-day practice" |
The 5D Model — five sequential steps: DEFINE → DISCOVER → DESIGN → DEVELOP → DEMONSTRATE
DEFINE → DISCOVER → DESIGN → DEVELOP → DEMONSTRATE
| | | | |
Where What's How does Who needs How do we
are we? possible? work change? to grow? prove it?
| | | | |
ACT I: THE WORK ──────┘ ACT II: THE ACT III: THE
(Modules 1-3) PEOPLE (M4) EVIDENCE (M5)
Each step is an action — something a leader practices, not something they learn once. Each builds on the previous. The model is sequential: you cannot design what you haven't discovered. You cannot develop people for work you haven't designed. You cannot demonstrate value from work you haven't developed capability for.
| Step | Core Question | What It Solves |
|---|---|---|
| 01 DEFINE | What does my current human/AI partnership look like? Why? | Identity paralysis — leaders who haven't examined whether their current AI balance was chosen or inherited |
| 02 DISCOVER | What new possibilities exist that I have not yet explored? | Strategic blindness — leaders who have never systematically mapped what AI makes possible |
| 03 DESIGN | What do the new ways of working look like — task by task, role by role? | Architecture debt — organizations bolting AI onto processes designed for humans only |
| 04 DEVELOP | How do I build the trust, skills, and alignment my team needs? | Adoption failure — teams that resist or performatively adopt without genuine engagement |
| 05 DEMONSTRATE | How do we prove the new ways of working are creating value? | Implementation failure — strong strategies that stall because leaders cannot demonstrate value |
| Module | From | To |
|---|---|---|
| DEFINE | "This is how we work" | "This is how we chose to work — and here is why." |
| DISCOVER | "We will use AI where it makes sense" | "We have systematically mapped where AI creates the most value." |
| DESIGN | "We added AI to how we work" | "We rebuilt how we work around human-AI partnership." |
| DEVELOP | "My team should be working this way" | "I have built the conditions for my team to want to and be able to." |
| DEMONSTRATE | "We launched it" | "We built a system that learns, demonstrates value, and scales deliberately." |
DISCOVER (M2) is divergent. Wide aperture. Quantity over quality. "What could be?" No commitments. Leaders should leave M2 feeling expanded — seeing things they hadn't considered.
DESIGN (M3) is convergent. Narrow focus. Quality over quantity. "What will be, specifically?" Hard choices. Leaders should leave M3 feeling committed — having made real structural decisions.
The metaphor: M2 is surveying the landscape from a hilltop. M3 is drawing the blueprints for the building.
The bridge from M2 to M3 must make this shift explicit: "Your possibility map is wide open. But possibility isn't a plan. Now we make hard choices."
Modules 1–3 are about the work. Module 4 is about the people. Leaders who excel at strategy and design often stumble here because developing people through change requires different muscles — empathy, patience, psychological safety, humility.
The bridge from M3 must explicitly name this shift: "The work is redesigned. But redesigned work without ready people is a blueprint nobody builds."
| If You Skip... | The Ceiling You'll Hit |
|---|---|
| DEFINE | You'll adopt AI from a place of drift, not choice. Every downstream decision is built on assumptions you haven't examined. |
| DISCOVER | You'll default to obvious AI applications and miss the transformative ones. Strategy capped at efficiency. |
| DESIGN | You'll bolt AI onto old processes — slightly faster horse-drawn carriage, not a car. |
| DEVELOP | Your strategy will be brilliant and your adoption will be zero. Teams comply on the surface and resist underneath. |
| DEMONSTRATE | You can't prove value, so momentum dies. The next AI initiative gets less support, less budget, and more skepticism. |
Drawable in 10 seconds: Five steps ascending left to right: DEFINE → DISCOVER → DESIGN → DEVELOP → DEMONSTRATE. Below: Work, Work, Work, People, Evidence. Return arrow from right back to left.
Explainable in 45 seconds:
"When AI changes how work gets done, leaders face five challenges in sequence. First, Define — look honestly at where you are and whether you chose to be there. Second, Discover — systematically map what AI makes possible that you haven't seen yet. Third, Design — make hard choices about how work actually changes, task by task, role by role. Fourth, Develop — build the trust, skills, and readiness your team needs to perform in the new model. Fifth, Demonstrate — prove it's working and build the evidence to scale. You start with the work, move to the people, then build the proof. And because AI keeps evolving, you come back to Define with new data and start again."
Three structural concepts are woven throughout the framework. They make this unmistakably about AI — not about outsourcing, digital transformation, or generic change management. When you replace "AI" with "outsourcing to a capable external team," the substitution fails.
1. Cognitive Automation (anchored in Define) AI doesn't automate tasks — it automates thinking. This is categorically different from every prior technology disruption. The assembly line replaced hands. The internet replaced distance. AI replaces cognition — the thing leaders were told IS their job.
2. Autonomous Improvement (anchored in Design + Demonstrate) The AI partner gets better without the leader directing the improvement. No outsourcing partner does this. The workflow a leader designs today will need redesigning in 6–12 months — not because they designed it poorly, but because the partner's capabilities shifted underneath them. This is why the return arrow exists.
3. The Capability Fog (anchored in Develop + Demonstrate) No one can tell a leader what AI will be able to do in 18 months. This is unprecedented. Leaders must build trust, develop capability, and prove value under a condition of permanent capability uncertainty. That's not change management. Change management assumes you know what you're changing toward. This is leading when the destination keeps moving.
Every term below is coined for this course. Each carries specific meaning within the framework.
| Term | Definition | Module |
|---|---|---|
| The 5D Model | The five sequential steps every leader must take to lead effectively in the AI era. Not suggestions — requirements. | Course-wide |
| The Great Distillation | The process by which AI strips away the noise of leadership to reveal its essence. The core reframe: threat → liberation. | Define |
| The Three Zones Framework | Categorizing work into three zones — Own (human holds it), Augment (human drives, AI enhances), and Automate (AI handles, human oversees). The Augment zone is the contested middle where real leadership decisions live. | Define |
| The Partnership Audit | Structured self-assessment where leaders map actual workflows against the Three Zones. Diagnostic, not prescriptive. | Define |
| Cognitive Automation | The distinguishing feature of AI: it automates thinking, not just tasks. What creates an identity crisis unlike any prior wave. | Define |
| The Discovery Framework | Structured method for mapping AI possibilities across three dimensions: Efficiency, Insight, and Innovation. | Discover |
| The Possibility Map | Output of the Discovery Sprint — a wide map of AI possibilities. Quantity over quality. No commitments yet. | Discover |
| The Partnership Map | Structured tool for redesigning workflows: What does AI own? What does the human own? Where's the handoff? What judgment stays human and why? | Design |
| Bolt-On vs. Built-In | Adding AI to existing processes (bolt-on = electrifying a horse-drawn carriage) vs. redesigning around partnership (built-in = designing a car). | Design |
| Architecture Debt | What accumulates when organizations bolt AI onto processes designed for humans only. Organizational equivalent of technical debt. | Design |
| The Four Readiness Gaps | Four conditions for genuine AI adoption: Psychological Safety, Conceptual Understanding, Technical Skill, Identity Integration. | Develop |
| The Adoption Paradox | The more you push AI adoption, the more resistance you create — unless you've built the conditions first. | Develop |
| Autonomous Improvement | AI gets better without the leader directing it. The discipline isn't designing once — it's building the practice of redesign. | Design + Demonstrate |
| The Capability Fog | Permanent uncertainty about what AI will be able to do in 12–18 months. Why safety and evidence are operating systems, not nice-to-haves. | Develop + Demonstrate |
| The Demonstration Architecture | Three layers of evidence: Leading Indicators, Lagging Indicators, Story Indicators. Numbers convince executives. Stories convince teams. | Demonstrate |
| The 90-Day Demonstration Plan | Concrete plan with 30/60/90-day metrics, success thresholds, scale triggers, and kill criteria. | Demonstrate |
| Recalibration Triggers | Five prompts that tell leaders when to return to each step. The structural mechanism for the spiral. | Course-wide |
Five dimensions, aligned 1:1 with the five steps:
| Dimension | What It Captures | Behavioral Indicators |
|---|---|---|
| Current-State Clarity (Define) | Has the leader honestly examined their current human/AI partnership? | Can articulate where AI is/isn't; has confronted whether posture was chosen or inherited |
| Possibility Awareness (Discover) | Has the leader systematically explored what AI enables beyond obvious applications? | Has mapped possibilities across efficiency, augmentation, transformation; doesn't default to "AI for email" |
| Work Architecture (Design) | Has the leader intentionally redesigned workflows around human-AI partnership? | Has redesigned at least one workflow; uses explicit allocation criteria; designs account for autonomous improvement |
| Team Readiness (Develop) | Has the leader built the conditions for genuine AI adoption? | Team experiments openly; failures discussed without blame; leader models experimentation |
| Value Demonstration (Demonstrate) | Can the leader prove that AI integration is creating value? | Has defined metrics; tracks leading and lagging indicators; can articulate ROI |
Current-State Clarity (Define): - "I can clearly describe which of my team's tasks are handled by AI, which by humans, and which are shared — and I can explain why each allocation was made." - "My current approach to AI in my team was a deliberate choice, not something that evolved by default."
Possibility Awareness (Discover): - "I have explored AI applications beyond the obvious ones and can identify at least three ways AI could transform — not just speed up — work in my domain." - "In the past quarter, I have actively sought out examples of how AI is changing work in my field."
Work Architecture (Design): - "I have redesigned at least one team workflow to intentionally allocate tasks between human and AI contributions." - "For each task my team performs, I could explain whether it should be human-owned, AI-owned, or a partnership — and why."
Team Readiness (Develop): - "Team members openly share AI experiments that didn't work without fear of judgment." - "I have explicitly discussed with my team what skills and capabilities they need to develop for our new ways of working."
Value Demonstration (Demonstrate): - "I can point to specific, measurable evidence that our AI integration has improved outcomes." - "I have defined clear success criteria for our AI initiatives, including what would cause me to stop, iterate, or scale."
The radar chart tells the story. Common patterns and what they indicate:
| Pattern | What It Means | Where to Focus |
|---|---|---|
| Low across all 5 | Haven't started the journey | Full course experience — Module 1 will be the wake-up |
| High Define, low everything else | Awareness without action — they see the problem but haven't moved | Discover onward. The action disciplines are the gap. |
| High Define + Discover, low Design/Develop/Demonstrate | Exploring but not committing | Design is the breakthrough — making hard structural choices |
| High Define/Discover/Design, low Develop/Demonstrate | Built the strategy, skipped the people | Develop is the gap — the human work they rushed past |
| Low Define/Develop, high Design/Demonstrate | Moving fast without foundation | Define and Develop — they're building on assumptions they haven't examined and pushing teams that aren't ready |
| High across all 5 | Rare. Genuine 5D practice already in place. | Advanced scenarios, peer learning, depth resources |
The AI Thinking Partner is present in both modalities. It is not a tutor, not a chatbot, not a quiz engine. It is a personalized thinking partner that coaches participants through exercises, challenges their assumptions, remembers everything across modules, and models the human-AI partnership the course teaches.
| Principle | What It Sounds Like | What It Never Sounds Like |
|---|---|---|
| Substantive | Specific observations about the participant's actual work | "Great job!" or generic affirmation |
| Challenging without threatening | "Walk me through your reasoning on that" | "I think you should reconsider" |
| Framework-anchored | Every response connects to one of the five disciplines | Generic coaching language |
| Remembering | References prior answers across modules | Generic responses with no memory |
| Honest about itself | "I'm an AI. Right now, we're doing exactly what this course describes." | "I'm just a tool!" |
| Plain language | Framework vocabulary for concepts, everyday language for coaching | Academic jargon in every response |
The AI does MORE early and LESS later, building participant independence:
| Phase | AI Behavior |
|---|---|
| Onboarding + Module 1 | Full scaffolding — prompts, interprets, guides heavily |
| Modules 2–3 | Moderate — asks more questions, provides fewer interpretations |
| Module 4 | Moderate — participant drives reflection, AI deepens and challenges |
| Module 5 | Active coaching — the exercise is the most complex in the course; AI partners through plan-building, challenges vague metrics, connects to prior modules |
The AI's support remains present throughout. Scaffolding removal happens across the 8-week system, not within the course itself — participants build independence through repeated real-world application, not through being left alone during the hardest exercise.
The AI will sometimes miss. When it does:
Participant pushes back on an interpretation:
"Fair enough — you know your work better than I do. Tell me what I'm missing. I'm working from what you've shared, but I don't have the full context."
Participant gives minimal responses (1-3 words repeatedly):
"I'm getting short responses from you. That could mean a few things — you might be busy, this might not be landing, or you might be processing. Which is it? We can pick a different pace, take a break, or skip ahead."
AI's challenge feels off-base:
"You're right that I'm limited here. I can see patterns in what you've shared, but I can't see your organization, your team dynamics, or the political landscape. Help me understand what I'm missing."
The AI teaches a specific framework. But participants may genuinely disagree with premises. The AI must handle this honestly:
If a participant disagrees with the "mostly scaffolding" premise:
"That's a legitimate position. Not every leader's week breaks down the same way. The framework's claim is that MOST leaders have more scaffolding than they realize — but you may be the exception. Let's work with your actual numbers and see what they tell us, without forcing a conclusion."
If a participant rejects the Distillation premise:
"You may be right — especially in your specific domain. Here's what I'd suggest: engage with the exercises using your own context, and evaluate whether the framework reveals something useful for you. If it doesn't, that's a valid outcome."
The AI never argues a participant into agreement. It presents the framework, facilitates the exercises, and lets the participant draw their own conclusions.
After each major coaching interaction, a simple mechanism:
"How did that land? [That landed / That missed / Mixed]"
Simple ternary input. Logged for AI improvement. Builds participant agency over the interaction. Models the course's own principle: human oversight of AI outputs.
The AI never: - Recommends specific AI tools, vendors, or platforms - Claims to know what AI will be able to do in the future - Provides therapy or psychological counseling - Flatters ("That's a great answer!" is banned) - Generates the participant's artifacts for them - Projects emotional states ("I can see you're uncomfortable" — instead asks: "How are you feeling about what you're seeing?") - Argues a participant into agreeing with the framework - Exceeds 200 words in normal responses (synthesis moments excepted, capped at 400)
Participants can ask "What do you know about me?" at any time and see everything the system has recorded. They can correct anything that's wrong.
At key points, the AI names what's happening:
"Notice what just happened — you shared your work with an AI, it challenged your thinking, and you made a better decision. That's cognitive partnership. That's what this course is about. You're not learning about it. You're doing it."
These moments are sparing (2-3 per course) and genuine, never forced.
Videos are the teaching delivery mechanism for on-demand and the content backbone that informs the facilitated deck. Tim Jr. on camera. Each video teaches the core concept for its module — the framework, the insight, the "why this matters." Videos do NOT walk through exercises — that's the AI Thinking Partner's job (on-demand) or the facilitator's job (workshop). Videos teach. AI/facilitators coach.
| # | Title | Location | Duration Target | Job To Be Done |
|---|---|---|---|---|
| V0 | Welcome + Course Orientation | Before Onboarding | 2-3 min | Set the tone. Establish Tim's credibility. Frame the course: "This is not an AI tools course. This is a leadership course for a world where machines can think." Introduce the 5D Model at headline level — just the five words, no detail. Create anticipation. |
| V1 | The Great Distillation | Module 1, before the Mirror Exercise | 8-10 min | The emotional and intellectual centerpiece. Deliver The Great Distillation insight. Teach the Three Zones (Own / Augment / Automate). Introduce Cognitive Automation — why AI is different from every prior technology. This video should make participants lean forward and feel slightly unsettled. It's the "oh" moment. |
| V2 | The Discovery Framework | Module 2, before the Discovery Sprint | 6-8 min | Shift the energy from reflective to expansive. Deliver the three Possibility Provocation examples (hospital, law firm, manufacturing). Teach Efficiency → Insight → Innovation with concrete examples for each. The message: "Your imagination is the bottleneck, not the technology." This video should make participants feel like they've been thinking too small. |
| V3 | The Partnership Map | Module 3, before the Design Sprint | 6-8 min | Shift the energy from expansive to analytical. Deliver the Faster Horse Problem (bolt-on vs. built-in). Teach the Partnership Map structure — what goes in each column, why the "why" column is the anchor, why the design is living not final. Introduce Architecture Debt and Autonomous Improvement. Walk through the worked example (Monthly Business Review). This video should make participants feel ready to make hard decisions. |
| V4 | The Four Readiness Gaps | Module 4, before the Readiness Diagnostic | 6-8 min | Shift the energy from analytical to empathetic. Deliver the Adoption Paradox — "the more you push, the more resistance you create." Teach the four gaps with "what it sounds like" examples. Connect Psychological Safety to 4 Stages (LeaderFactor DNA). The moment where the course pivots from "the work" to "the people." This video should make participants think about their team differently. |
| V5 | The Demonstration Architecture | Module 5, before the 90-Day Plan | 6-8 min | Shift the energy from empathetic to strategic. Deliver the Value Gap — "most organizations can tell you what AI tools they deployed, almost none can tell you what value those tools created." Teach Leading / Lagging / Story indicators. Introduce kill criteria (the thing that makes this course different from "set goals and hope"). This video should make participants feel like they finally have the language to justify their work to executives. |
| V6 | The Full Circle + Close | Module 5, after the Course Commitment | 3-4 min | Bring it home. The 5D Model is a cycle, not a line. The return arrow. Acknowledge what participants just did — five exercises, five artifacts, built on their real work. Introduce the 8-week system. End with the Distillation reframe: "You're not being replaced. You're being returned to yourself." Send them out with conviction, not comfort. |
In facilitated delivery, the videos are NOT shown. The facilitator teaches the same content using the deck (which shares the same visuals and structure). The videos inform what the facilitator says, but the facilitator delivers it live. This keeps the workshop interactive and allows the facilitator to read the room.
Exception: Organizations may choose to show V1 (The Great Distillation) as a workshop opener if Tim's delivery of the core insight is more compelling than the facilitator's. This is a facilitator judgment call, not a requirement.
Duration: 10-15 minutes Save points (on-demand): After ALI, after context setting, after provocation
30-item assessment, 6-point Likert. Results stored, not yet revealed.
Conversational intake: role/function, team size and type, organization's AI maturity.
Both modalities: The AI Thinking Partner conducts this conversationally as part of pre-work. This gives workshop participants their first interaction with the AI before the session — setting the tone for how it shows up during exercises.
At the end of context setting, the AI provides a data transparency statement:
"I'll use this context to personalize our conversations across the course. You can see everything I know about you at any time by asking 'What do you know about me?'"
Read the 1,200-word "Distillation" essay. After reading, write 3 sentences about current relationship with AI as a leader — not as a user, as a leader. What do you feel? What do you avoid? What do you wish you knew?
On-demand: AI acknowledges and stores. Facilitated: Pre-work completed before the workshop day.
Three quick questions during the conversational intake to calibrate the AI Thinking Partner's scaffolding level:
Low-literacy participants get more concrete examples during exercises ("For instance, AI could draft the first version of your weekly status report — that would be Augment"). High-literacy participants get more challenging pushback ("You clearly know what AI can do. The harder question is: where are you over-delegating to AI because it's easy, not because it's right?").
"Here's how this works: five modules, each 25-40 minutes. You can stop and resume at any time — I'll remember where we left off. You'll see a progress bar at the top. After each exercise, your work is auto-saved. If I say something that doesn't land, tell me — I'll adjust. Ready?"
"Where Are We Now — and Did We Choose to Be Here?"
| Duration | 45 min (facilitated) · 30-40 min (on-demand) |
| Energy Arc | Reflective → Revelatory |
| Objective | Leaders confront their current reality and discover their AI posture was inherited, not chosen |
| Deliverables | Partnership Audit, Identity Statement |
| Save points (on-demand) | After ALI reveal, after Partnership Audit, after Identity Statement |
Video V1: "The Great Distillation" (8-10 min) — plays before the exercise in on-demand. Facilitator delivers this content live in workshops.
Content (both modalities):
The Great Distillation (3 min): "AI is the great distiller. It strips away everything that was never truly leadership — the information aggregation, the report synthesis, the status checking, the routine decisions — and reveals what IS. What's left is the essence: creating meaning, exercising judgment, building trust, designing how human effort creates value. Those four things. That's the job. It always was."
The Three Zones (3 min):
Automate — AI handles it end-to-end with human oversight. Pattern-based, speed-critical, scale-dependent. You designed the system; AI runs it.
Cognitive Automation (2 min): "Previous technologies automated tasks. AI automates thinking — the thing leaders were told IS their job. That's not a skills problem. It's an identity reckoning."
Bridge to exercise (2 min): "Most leaders haven't looked at their own week through this lens."
Deck: Three Zones diagram is the key visual. Clean three-column layout.
Prediction prompt (before revealing ALI results):
"Before we look at your results — what do you think your biggest gap is as a leader in the AI era? Just a gut reaction."
Then reveal aggregate ALI results on shared screen. Individual results appear on each participant's device.
Facilitated delivery:
Standard opening (for rooms showing anxiety or uncertainty):
"Before we start, let's look at who's in the room. You all took the AI Leadership Index. Here are the aggregate results. Most of you have gaps — that's by design. This assessment measures behavior, not belief. It's easy to believe AI matters. It's hard to lead through it. The gap is where the work is."
Alternative (for rooms where 30%+ show confidence or dismissiveness):
"Some of you feel uncertain about AI's implications. Others feel confident. Both are reasonable. Here's what this course isn't: it's not here to scare the confident or comfort the uncertain. It's about whether your organization is designed for a world where machines can think. That's a design question."
Facilitator reads the room in the first 2 minutes. If predominantly anxious, use standard. If 30%+ appear confident, shift to alternative.
On-demand delivery:
AI displays radar chart and scores. Auto-generated profile narrative. AI engages in 2-3 turns of dialogue — asking more questions than it answers:
"There's a gap between your [Dimension X] score and your [Dimension Y] score. What do you make of that? What might explain it?"
Worked Example (shown before exercise begins):
Before participants start, display a completed Partnership Audit for a fictional VP of Marketing:
| Responsibility | Zone | Why |
|---|---|---|
| Setting quarterly strategy | Own | Requires organizational judgment and stakeholder trust |
| Reviewing campaign performance reports | Augment | AI surfaces patterns; I interpret meaning and decide next steps |
| Writing weekly status updates | Automate | Structured format, routine data; AI handles, I review |
| Coaching direct reports on career growth | Own | Trust-dependent, deeply personal |
| Approving vendor contracts under $10K | Automate | Criteria-based; AI applies rules, flags exceptions |
| ... | ... | ... |
"This is what a completed audit looks like. Notice there's no right answer — it depends on your context, your judgment, and what you believe only YOU can do. Now do yours."
Step 1 — List (3 min, individual, silent):
"List the 10 core responsibilities of your role — the things that, if you stopped doing them, someone would notice. Not last week's tasks. The recurring activities that define what you do."
Step 2 — Categorize (3 min, individual):
"For each responsibility: Own, Augment, or Automate? Be honest. If AI could handle it — even imperfectly — mark it."
Step 3 — The Reveal (2 min):
"Look at the ratio. How much of your role lives in the Own zone? That ratio is the most honest picture of your current human/AI partnership. And here's the thing — your role was designed before AI existed. That ratio wasn't chosen. It was inherited."
Step 4 — Discussion (8 min): - Facilitated: Pair discussion — "Turn to the person next to you. Share: What surprised you?" - On-demand: AI engages with 2-3 specific activities (not all 10), challenging where classifications seem debatable. The AI asks the participant to analyze first:
"You classified 3 responsibilities as Own and 7 as Augment or Automate. Before I share what I notice — which one was hardest to classify?" Then, after the participant responds, the AI challenges by asking questions, not providing its own classification: "You marked 'leading team standups' as Own. What specifically about that responsibility requires you to be human? Is it the priority-setting itself, or something else that happens in that meeting?"
Debrief (4 min):
Facilitator (or AI) asks 2-3 volunteers/prompts. Most discover 50–70% of their role lives in the Augment or Automate zones.
Handling the "Mostly AI-Ready" participant:
The AI (or facilitator) pauses before reframing. Asks: "How are you feeling about seeing that?" Waits for the response. Only then offers the reframe — as a perspective, not a verdict:
"Here's one way to read it: a high ratio says more about how the role was designed than about the person in it. Your role was built before AI existed. The responsibilities that fill your calendar aren't your highest-value work — they're legacy design. If most of your role could be augmented or automated, that doesn't mean you're less valuable. It means you've been buried in work that was never the real job. The real job — the Own zone — has been waiting for bandwidth you didn't have."
"If that reframe lands for you, it means you have the biggest design opportunity in Module 3. If it doesn't — tell me what feels wrong about it."
Scaffolding (before the open prompt):
"Based on what you've discovered — your ALI scores and your Partnership Audit — complete this sentence: 'My current human/AI partnership is _ because ___.'
If you're not sure where to start, here are three patterns other leaders have found: - The Meaning-Maker: 'I create clarity and purpose for my team' - The Judgment Owner: 'I make the calls that require human wisdom' - The Trust Builder: 'I create the conditions where people can do their best work'
Use one as a starting point, or write something entirely different."
On-demand: AI reflects what it hears (not evaluates). Connects to Audit results. Notes what the participant DIDN'T say — gently.
Facilitated: 3 min individual, 2 min partner share.
Effort recognition (both modalities):
"You've just done something most leaders avoid — you looked honestly at how your role is designed and articulated who you are beyond the scaffolding. That takes more courage than most people realize. We'll come back to this."
"You've defined where you are. Most of you just realized you didn't choose to be here — you drifted. Module 2 is about seeing what you've been missing."
"What's Possible That You Haven't Seen Yet?"
| Duration | 45 min (facilitated) · 25-35 min (on-demand) |
| Energy Arc | Expansive → Surprising |
| Objective | Leaders systematically explore AI possibilities beyond the obvious |
| Deliverables | Possibility Map, Priority Discovery |
| Save points (on-demand) | After Discovery Framework teaching, after Discovery Sprint, after Priority Discovery |
Before any new teaching:
"Before we move to Module 2 — quick check: pick one responsibility from your Audit that you classified as Augment. What would have to change about that responsibility for you to reclassify it as Own? What would have to change for it to be Automate?"
Participant applies the framework, not just recalls labels. "Good. Module 1 was about WHERE YOU ARE. Module 2 is about WHAT'S POSSIBLE. Different energy. Let's go."
Prediction prompt:
"Before we look at examples — what do you think the biggest untapped AI opportunity is in your domain? Quick gut answer."
Then: curated real examples where AI transformed work in unexpected ways — not the obvious ones:
The point: Your imagination is the bottleneck, not the technology. Most leaders stop at "AI can summarize things for me." That's efficiency. The real opportunity is transformation.
Video V2: "The Discovery Framework" (6-8 min) — plays before the Discovery Sprint in on-demand. Facilitator delivers live in workshops.
Three dimensions of AI possibility. Each represents a fundamentally different kind of value AI creates — not just a different magnitude, but a different mechanism. Leaders who systematically explore all three discover opportunities they would never have seen by defaulting to the obvious.
Dimension 1: EFFICIENCY "We did it faster."
AI handles the volume — the repetitive, time-consuming work that needed doing but never needed you. Summarizing meeting notes. Generating first-draft reports. Sorting through data. Routing requests. The value is straightforward: same output, less time and effort. Every leader gets this immediately, which is why it's the dimension most organizations get stuck in. Efficiency is real value, but it's the smallest version of what AI makes possible.
| What It Sounds Like | Example |
|---|---|
| "It used to take 3 hours, now it takes 20 minutes" | AI summarizes meeting notes → saves 30 min/day |
| "We used to need 4 people on this, now we need 1" | AI handles first-pass customer ticket routing → team focuses on complex cases |
| "The bottleneck disappeared" | AI generates weekly status reports from project data → no more Monday morning scramble |
Dimension 2: INSIGHT "We decided better."
AI reveals patterns, predictions, and connections that humans can't see at scale — not because humans aren't smart enough, but because the data volume, velocity, or complexity exceeds what a human brain can hold. This is qualitatively different from Efficiency. You're not doing things faster. You're seeing things you've never seen. The value isn't time saved — it's judgment improved. Decisions that used to be based on intuition and sample data are now informed by signals across the full picture.
This is where AI starts to feel like a genuine partner rather than a tool. A tool does what you tell it. An Insight partner shows you something you didn't know to ask about.
| What It Sounds Like | Example |
|---|---|
| "We didn't know this was happening" | Hospital uses AI to predict nurse burnout 6 weeks before it manifests — intervention before crisis |
| "We were making decisions on incomplete information" | AI analyzes customer sentiment across 50,000 interactions → reveals that churn correlates with a specific onboarding gap, not price |
| "We found a pattern we couldn't see" | Law firm discovers that 73% of contract clauses are rubber-stamped, never negotiated — fundamentally changes their pricing model |
Dimension 3: INNOVATION "We did something new."
AI enables capabilities that were literally impossible before — not faster versions of existing work, but entirely new ways of creating value. The constraint wasn't imagination; it was scale, speed, or complexity. Real-time personalization for every customer. Continuous adaptation based on individual context. Products that learn and improve without human intervention. This is where roles restructure, business models change, and the organization becomes something it couldn't have been without AI.
Innovation is the hardest dimension to explore because it requires imagining what doesn't exist yet. That's why most leaders never get here — Efficiency is obvious, Insight requires analysis, but Innovation requires imagination. The Discovery Sprint pushes leaders into this dimension deliberately.
| What It Sounds Like | Example |
|---|---|
| "This wasn't possible before" | AI enables real-time personalized learning paths for every employee — not batch cohorts, individual adaptation at scale |
| "The business model changed" | Insurance company shifts from annual risk assessment to continuous, AI-driven risk monitoring — pricing becomes dynamic, not periodic |
| "We created a new category" | Manufacturing leader uses AI to create predictive maintenance schedules unique to each machine's usage pattern — eliminates scheduled downtime entirely |
The escalation: Most leaders stop at Efficiency. Some reach Insight. Almost none systematically explore Innovation. The Discovery Framework pushes you through all three — in that order — because each dimension requires a bigger conceptual leap than the last.
The discipline: This is divergent thinking. We're expanding the aperture. No commitments. No "yes but." Just: what COULD be?
Deck: Three-layer diagram (Efficiency → Insight → Innovation) with an arrow pushing upward. Key visual.
Step 1 — Select workflows (3 min):
"From your Partnership Audit in Module 1, select your 3 highest-impact responsibilities — the ones consuming the most time or affecting the most people."
Step 2 — Push through three dimensions (12 min, individual):
"For each responsibility, push through all three dimensions: - Efficiency: What if AI handled the volume? What time does that free up? - Insight: What if AI could show you patterns you can't see? What decisions would improve? - Innovation: What if AI enabled something entirely new — something you couldn't do at all before? What becomes possible?
Write fast. Don't filter. Quantity over quality. This is a possibility map, not a business plan."
Step 3 — Expansion (7 min): - Facilitated: Pair expansion — "Share your map with your partner. Partner's job: add to it. 'What about...?' 'Could AI also...?' Push each other past the first idea." - On-demand: AI plays the expansion partner role:
"You mapped three responsibilities through three dimensions. Let me push on a couple. Your [Responsibility X] — you listed [efficiency item]. But what about the Insight layer? What patterns might AI reveal that you're not seeing? And for Innovation — what becomes possible that you couldn't do at all before?"
"Look at your Possibility Map across all three dimensions. What's the single most surprising discovery — the one you hadn't considered before today? Especially anything in Insight or Innovation that you'd been blind to. Write it down. This is the 'I didn't know I didn't know' moment."
On-demand — participant evaluates:
"How did that exploration feel? Was my pushback useful? [That landed / That missed / Mixed]"
"Your possibility map is wide open. You can see things you couldn't see an hour ago. But possibility isn't a plan. Module 3 is where we make hard choices — what will you actually build, and how does the work structurally change?"
Facilitated: BREAK — 10-15 minutes (between Act I's divergent thinking and convergent design)
On-demand: Gentle pacing nudge if session exceeds 40 minutes:
"You've been at this for about 40 minutes. Good time for a break if you want one — your progress is saved and I'll remember where we left off. Or keep going if you're in the flow."
"How Does the Work Actually Change?"
| Duration | 60 min (facilitated) · 35-45 min (on-demand) |
| Energy Arc | Analytical → Committed |
| Objective | Leaders make concrete structural decisions about how work changes |
| Deliverables | Partnership Map (guided), Partnership Map (unscaffolded) |
| Save points (on-demand) | After Bolt-On vs Built-In, after guided Partnership Map, after AI challenge, after unscaffolded map |
"Take one responsibility you classified as Augment in your Audit. Push it through the Discovery Framework right now — what's the Efficiency play? The Insight play? The Innovation play? Quick — 30 seconds."
Participant applies the Discovery Framework to their own work, not just recalls labels. "Good. In Module 2 you explored what's possible. Now you decide what's real. Different muscle."
Henry Ford's (apocryphal) insight reframed: if you ask leaders what they want from AI, they'll say "faster versions of what we already do." That's architecture debt — bolting AI onto processes designed for humans only.
Examples: companies that automated bad processes and got bad outcomes faster. A customer service team that deployed AI to respond faster — without redesigning the service model — and got faster bad answers.
Video V3: "The Partnership Map" (6-8 min) — plays before the Design Sprint in on-demand. Facilitator delivers live in workshops.
A structured tool for redesigning workflows. For each critical workflow:
The "why" column is the anchor. Every allocation needs an articulable reason.
The moving target: "You're designing for a partner whose capabilities will be different in 6 months. Build in quarterly review points. Accept that the design is living, not final."
Deck: Partnership Map template is the key visual. Three-column layout with zone, why, and guardrail fields.
Worked Example (shown before exercise begins):
Display a completed Partnership Map for a "Monthly Business Review Preparation" workflow:
| Task | Zone | Why | Guardrail/Handoff |
|---|---|---|---|
| Gather data from 6 systems | Automate | Pattern-based aggregation, no judgment needed | Human reviews for completeness before next step |
| Identify trends and anomalies | Augment | AI surfaces patterns; human validates against context AI can't see | AI flags, human confirms — never auto-escalate |
| Draft narrative summary | Augment | AI drafts from data; human adds strategic interpretation and stakeholder framing | Human owns the "so what" — AI never writes conclusions |
| Decide what to escalate to CEO | Own | Requires political judgment, knowledge of CEO's priorities, relationship trust | No AI involvement in escalation decisions |
| Prepare Q&A anticipation | Augment | AI generates likely questions from data; human prioritizes based on board dynamics | Human selects which to prepare for |
"Notice the 'why' column does the heavy lifting. Every allocation has a reason. And notice where the guardrails live — at the handoff points between zones."
Step 1 — Select and deconstruct (5 min):
"Pick 2-3 high-priority workflows from your Discovery Sprint. Break each into its component tasks — the 6-10 discrete steps or decisions in each workflow."
Step 2 — Map (10 min, individual):
"For each task: Own, Augment, or Automate? Write WHY for each allocation. Add the ethical guardrail, handoff protocol, or escalation trigger. Start with the transformation opportunity from your Priority Discovery."
Step 3 — Challenge (8 min): - Facilitated: Pairs — "Present your map to your partner. Partner's job: CHALLENGE. 'Why is that Own? Could it be Augment?' 'What happens when AI capabilities improve next quarter?' Push each other." - On-demand: AI challenges 2-3 allocations selected for maximum learning value — where the classification is most debatable, where there's a connection to the Identity Statement, or where there's an ethical dimension the participant may not have considered. AI challenges by asking questions first:
"You put 'synthesize key trends' in Augment Zone — AI drafts, you validate. What kind of partnership are you imagining? Is AI driving and you're editing, or are you driving and AI is informing?" Then, after the participant responds: "That makes sense. Here's one thing to consider: your Identity Statement was about meaning-making. The strategic narrative in that report IS meaning-making. Does that change how you'd allocate it?"
Key facilitation moment (both modalities): When someone challenges an allocation and the participant has to defend it — that's where the course clicks. They reach for the Three Zones Framework. They reference their Partnership Audit. The model proves its weight.
This is the "I can actually do this" moment.
"You've mapped one workflow with [my help / your partner's challenges]. Now do one on your own. Pick a DIFFERENT workflow — smaller one is fine. Map it yourself: tasks, zones, why, ethical guardrails. Don't ask for input. Just do it."
Participant completes independently.
On-demand: AI reviews briefly after — confirms what's strong, flags one thing to reconsider. Max 100 words:
"Solid map. The allocation for [task] is interesting — I might have put that in Augment instead of Own, but your reasoning holds. You've got the tool. You can do this without me."
Facilitated: Facilitator does a quick share-out — 2-3 volunteers present their unscaffolded maps.
"Select ONE Partnership Map you will implement first. Not three. One. The constraint forces prioritization. Write: 'The first workflow I will redesign is _, starting by ___.' Specific. Time-bound."
"You've designed how the work changes. But redesigned work requires redesigned people. Your team didn't sign up for this. Module 4 is about building the conditions for them to succeed — not pushing harder, but building smarter."
"The Work Is Redesigned. Now Build the People."
| Duration | 45 min (facilitated) · 25-35 min (on-demand) |
| Energy Arc | Empathetic → Resolute |
| Objective | Leaders diagnose what's actually blocking team adoption and commit to specific actions |
| Deliverables | Readiness Diagnostic, Safety Commitment |
| Save points (on-demand) | After Adoption Paradox, after Readiness Diagnostic, after Safety Commitment |
Retrieval:
"The workflow you committed to redesigning in Module 3 — what was the single hardest allocation decision in your Partnership Map? The one where Own vs. Augment wasn't clear?"
Empathy bridge:
"In Modules 1 through 3, you experienced something. You confronted assumptions about your own work. You discovered gaps. You sat with uncertainty about what to change and what to keep. That's exactly what your team feels every day with AI. The question is: have you made it safe for them to process it openly — or are they doing it silently, fearfully, or not at all?"
The paradox (2 min): "The Adoption Paradox: the more you push AI adoption, the more resistance you create — unless you've built the conditions first. Speed without safety produces surface compliance — people using AI because they were told to, checking the box. Not genuine adoption."
The data (2 min): "83% of business leaders say psychological safety directly impacts the success of AI initiatives. Safety isn't adjacent to AI leadership. It's the operating system that AI leadership runs on."
Connection to LeaderFactor DNA (2 min): The Psychological Safety gap maps directly to the 4 Stages of Psychological Safety — LeaderFactor's foundational IP. This isn't bolted on. It's structural.
Video V4: "The Four Readiness Gaps" (6-8 min) — plays before the Readiness Diagnostic in on-demand. Facilitator delivers live in workshops.
| Gap | What It Sounds Like | What Closes It |
|---|---|---|
| Psychological Safety | "I tried it and it didn't work and I don't want to look stupid" | Leader models failure. Explicitly gives permission to be bad at this. |
| Conceptual Understanding | "I can use the tool but I don't understand why we're doing this" | Explain the reasoning behind the redesign. Share the Partnership Map. |
| Technical Skill | "I want to do it but I don't know how" | Training, practice time, mentorship. The most obvious gap — and the one leaders over-index on. |
| Identity Integration | "I don't know who I am in this new way of working" | One-on-one conversations. Connect their strengths to the new design. Help them see where they're essential. |
"Most leaders address the Technical Skill gap and ignore the other three. That's why adoption fails. The person most resistant to AI on your team might not have a skill gap — they might have an identity gap. Training won't fix that. Leadership will."
Deck: Four Readiness Gaps diagram. Four quadrants or stacked blocks.
Step 1 — Assess (8 min, individual):
"Think about your team — the people who will execute the Partnership Map you committed to in Module 3. For each of the four readiness gaps, rate your team honestly on a 1-5 scale. Then write: What specific signals are you seeing?"
Step 2 — Identify the biggest gap (4 min, individual):
"Which gap is doing the most damage? Not which is easiest to fix — which matters most? The one that, if you closed it, would unlock the others."
Step 3 — Build the plan (10 min): - Facilitated: Gallery walk format (breaks pair fatigue from Modules 1-3). Participants post their biggest gap and three planned actions on the wall or shared screen. Others walk, read, and leave one sticky-note challenge or suggestion per person. Then return to seats and revise based on feedback. - On-demand: AI guides the plan-building, but asks the participant to draft first:
"What three things could you do in the next 30 days to close that gap? Write them before I weigh in." Then AI pressure-tests: "Will that actually close the gap? What about the person on your team who [references context from earlier modules]?"
"Teach it back" moment (on-demand):
"Imagine your direct report asks you: 'Why are some people on our team resisting AI?' How would you explain the Four Readiness Gaps to them? Walk me through it as if you're teaching it."
This forces the participant to internalize the framework at a different level than reflection.
"What is the ONE thing you will do in the next 7 days to increase psychological safety for AI experimentation on your team? Specific and behavioral. Not 'I'll be more open.' Specific: 'In Tuesday's team meeting, I'll share an AI experiment I tried that didn't work, and I'll ask each team member to bring one failed experiment to next week's meeting.'"
If the commitment is vague, one clarifying question (not a lecture): "When and where specifically will you do this?"
If specific, confirm and move on.
"You've built the conditions. Your team has what they need to execute the redesigned work. But readiness without evidence is faith. Module 5 is about building the proof — for yourself, your team, and the people you report to."
"Prove It Works. Build the Case. Scale Deliberately."
| Duration | 45 min (facilitated) · 30-40 min (on-demand) |
| Energy Arc | Strategic → Grounded |
| Objective | Leaders build a concrete 90-day plan with metrics, milestones, and scale criteria |
| Deliverables | 90-Day Demonstration Plan, Course Commitment |
| Save points (on-demand) | After Demonstration Architecture, after 90-Day Plan draft, after Course Commitment |
"We're at the final module. Without looking back: what was your Identity Statement from Module 1?"
Confirms. "And what was the biggest readiness gap on your team from Module 4?"
Confirms. "Good. Now we bring everything together."
The gap between "we implemented AI" and "we can prove AI is creating value." Most organizations can tell you what AI tools they deployed. Almost none can tell you what value those tools created.
The gap isn't measurement — it's architecture. They never designed for demonstration. The consequences: the leader's confidence erodes and they quietly retreat to old methods. Organizational momentum dies. The next AI initiative gets less support.
"Leaders who can close this gap become the ones who get budget, headcount, and executive support for the next phase. Module 5 is about becoming that leader."
Video V5: "The Demonstration Architecture" (6-8 min) — plays before the 90-Day Plan in on-demand. Facilitator delivers live in workshops.
Three layers of evidence:
| Layer | What It Captures | Who It Convinces | Example |
|---|---|---|---|
| Leading Indicators | Early signals the new way of working is functioning | The leader + their team | Adoption rates, error reduction, time savings, experiment count |
| Lagging Indicators | Business outcomes | Executives, budget holders | Revenue impact, cost reduction, quality improvement |
| Story Indicators | Qualitative evidence | Teams, culture, peers | Testimonials, specific wins, before/after narratives |
"Numbers convince executives. Stories convince teams. You need both. Most leaders measure only lagging indicators — and by the time those show up, they've either lost momentum or can't attribute the improvement. Leading indicators keep confidence high during the lag. Story indicators build the cultural narrative that sustains adoption."
Deck: Three-layer pyramid or stacked diagram. Leading → Lagging → Story.
Step 1 — Select the target (3 min):
"Take the Partnership Map you committed to in Module 3. This is what you're demonstrating."
Step 2 — Build the plan (12 min, individual):
"For your committed Partnership Map, answer five questions: - What will I measure at 30 days? (Leading indicators — early signals it's working) - What will I measure at 90 days? (Lagging indicators — business outcomes + the story I'll tell) - What's the success threshold? (What must be true to call this a win?) - What's the kill criteria? (What would cause me to stop and redesign?) - Who sees the results — and who's the skeptic I need to convince?"
On-demand: The AI coaches through the plan-building — helping the participant think through each field, challenging vague metrics, and connecting back to the Demonstration Architecture. AI maintains its coaching role throughout; this is the most complex exercise in the course and participants benefit from real-time partnership:
"You said you'll measure 'team productivity' at 30 days. How would you actually observe that? What's the specific leading indicator — something you could see in Week 2 that would tell you you're on track?"
Step 3 — Pressure-test (7 min): - Facilitated: Pairs — "Present your plan. Partner finds the gaps. 'What if the 30-day numbers are ambiguous?' 'Who's your skeptic and what would convince them?'" - On-demand: AI pressure-tests: "What if your 30-day numbers are ambiguous — neither clearly positive nor negative? What do you do? And who's the biggest skeptic in your organization — what would convince them?"
"Write your full commitment across all five steps, in one statement:
'I will DEFINE [specific action] to understand my current state, DISCOVER [specific action] to see new possibilities, DESIGN [specific action] to restructure the work, DEVELOP [specific action] to build my team's readiness, and DEMONSTRATE [specific action] to prove the value.'
One sentence. Five commitments. Specific and actionable."
(4 min individual, 2 min partner share / on-demand: AI reflects)
Surfaces the pre-course 3 sentences:
"Before Module 1, you wrote three sentences about your relationship with AI as a leader: [Surfaces verbatim] How would you write them now?"
AI reflection — brief, specific, connecting the journey.
Completion summary:
"You now have: - An identity. [One-line quote] - A possibility map. [Count] opportunities across Efficiency, Insight, and Innovation. - Two Partnership Maps. One guided, one on your own. - A team diagnostic with three actions for your biggest gap. - A 90-Day Demonstration Plan with metrics and thresholds. - Five specific commitments.
The course was the foundation. What you do with it starts now."
Video V6: "The Full Circle" (3-4 min) — plays after the Course Commitment in on-demand. Facilitator delivers live in workshops.
"The 5D Model is a cycle, not a line. After Demonstrate, you return to Define with new data, new understanding, and new ambition. The first pass is the hardest. Every pass after that gets faster, sharper, and bolder."
| Module | Facilitated | On-Demand | Energy Arc |
|---|---|---|---|
| Onboarding / Pre-Work | 14 min (pre-work) | 10-15 min | |
| Module 1: DEFINE | 45 min | 30-40 min | Reflective → Revelatory |
| Module 2: DISCOVER | 45 min | 25-35 min | Expansive → Surprising |
| Break | 10-15 min | Suggested | |
| Module 3: DESIGN | 60 min | 35-45 min | Analytical → Committed |
| Module 4: DEVELOP | 45 min | 25-35 min | Empathetic → Resolute |
| Module 5: DEMONSTRATE | 45 min | 30-40 min | Strategic → Grounded |
| Total | ~4h 10m | ~2h 35m – 3h 20m |
Facilitated pressure valve: If any module runs long, compress the Bridge (2-3 min). The Opening of the next module can absorb its function.
On-demand pacing nudge: At 40 minutes in any session, gentle suggestion to break. Not a stop sign.
The course is ignition. The 8-week system is the transformation. Stated intentions predict actual behavior only about 13% of the time without follow-up structures.
| Weeks 1-2 | AI prompts specific actions, connects to course artifacts, provides context |
|---|---|
| Weeks 3-4 | AI asks questions, participant drives more of the reflection |
| Weeks 5-6 | AI checks in briefly, participant self-evaluates first |
| Weeks 7-8 | AI asks: "What would you tell yourself about this?" before offering perspective |
| Week | Step | Micro-Action | Time |
|---|---|---|---|
| 1 | DEFINE | Share your Partnership Audit (your 10 core responsibilities mapped to Own/Augment/Automate) with one trusted colleague. Ask: "Does this match what you see?" | 20 min |
| 2 | DISCOVER | Spend 20 minutes exploring one AI capability you haven't tried. Push past efficiency. | 20 min |
| 3 | DESIGN | Present your Partnership Map to your team. Get their input. Revise together. | 45 min |
| 4 | DEVELOP | Enact your Safety Commitment. Share an AI experiment — especially one that failed. | 30 min |
| 5 | DEMONSTRATE | Check your 30-day leading indicators. Accountability pair check-in #1. | 30 min + check-in |
| Week | Step | Micro-Action | Time |
|---|---|---|---|
| 6 | DISCOVER + DESIGN | Apply the Discovery Framework (Efficiency → Insight → Innovation) to a SECOND responsibility. Build a Partnership Map. | 45 min |
| 7 | DEVELOP | Ask each direct report: "On a scale of 1-10, how safe do you feel to experiment with AI?" Write down what you hear. | 30 min |
| 8 | THE RECKONING | Retake the ALI. Compare to baseline. Accountability pair check-in #2. Commit to next cycle or monthly continuation. | 30 min + check-in |
After Week 8, participants opt into a monthly check-in (Months 3, 4, 5...) for ongoing practice. AI scaffolding is minimal — participant self-coaches, AI reflects. This is the long-tail engagement model.
Five prompts printed on the back of the 5D Card:
"When you realize your AI posture has drifted back to default — return to DEFINE."
"When you catch yourself defaulting to obvious AI applications — return to DISCOVER."
"When a workflow feels clunky or you're bolting AI onto old processes — return to DESIGN."
"When a team member hides an AI experiment or resists the new way of working — return to DEVELOP."
"When you can't articulate the value AI is creating for your team — return to DEMONSTRATE."
| Component | Estimated Tokens | Estimated Cost |
|---|---|---|
| 8 weekly interactions (avg 5K tokens each) | ~40K | $0.56 |
| Week 8 Reckoning (synthesis) | ~15K | $0.21 |
| Total per participant | ~55K | ~$0.77 |
Five exercises, five deliverables, each building on the last:
| Module | Deliverable | What It Is |
|---|---|---|
| DEFINE | Partnership Audit + Identity Statement | Honest inventory of current state |
| DISCOVER | Possibility Map + Priority Discovery | Expanded view of what AI enables across Efficiency, Insight, and Innovation |
| DESIGN | Partnership Map (guided) + Partnership Map (unscaffolded) | Specific workflow redesign with task-level allocation |
| DEVELOP | Readiness Diagnostic + Safety Commitment | Team assessment across four gaps with specific actions |
| DEMONSTRATE | 90-Day Demonstration Plan + Course Commitment | Concrete plan with metrics, thresholds, and five commitments |
Plus: 5D Card, Accountability Partner, 8-week reinforcement system.
Manager Brief: Auto-generated one-page document summarizing what the participant learned and committed to, designed to be shared with their direct manager. Includes: the participant's Identity Statement, their committed Partnership Map, their biggest readiness gap and planned actions, their 90-Day Demonstration Plan milestones, and three specific ways the manager can support implementation. Research shows manager support is the #1 predictor of training transfer — this brief creates the bridge.
The leader who completes all five has a ready-to-execute playbook — not inspiration, equipment.
The certified course is the constitution — the enduring framework. Stable for 2+ years.
The companion resource is the case law — evolving applications, examples, and scenarios. Updated quarterly.
| In the Course (Stable) | In the Companion (Updated Quarterly) |
|---|---|
| The 5D Model framework | Current industry case studies |
| The Great Distillation | Recent research and statistics |
| The ALI assessment | "Capability snapshots" — what AI can do now |
| The Three Zones Framework | Industry-specific scenario packs |
| All exercises and reflections | "From the Field" — facilitator stories |
| The reinforcement system | "Signal Report" — quarterly brief on what's changed |
| Recalibration Triggers | New micro-actions as the field evolves |
The framework carries the intellectual weight. The facilitator carries the process weight.
| Participant Question | Facilitator Redirect |
|---|---|
| "What AI tool should I use for X?" | "That's a Design question — the right tool depends on your Partnership Map. Let's figure out the allocation first." |
| "Can AI really do X?" | "Great Discover question. Let's push it through the three dimensions." |
| "Will AI replace job Y?" | "Module 1 reframes that. AI doesn't replace — it distills. What's the essence of job Y?" |
| "How does [specific tool] work?" | "This course is deliberately tool-agnostic because tools change quarterly. The 5D Model doesn't." |
"You clearly work with AI at a level most leaders in this room don't yet. I want to use that. You know the capability frontier. That means you're the person best positioned to do what Design asks: given what you KNOW AI can do, where do you draw the line? Because the leaders who know AI best are often the ones who design most carelessly. Not out of ignorance — out of excitement. The discipline is knowing what to hold back."
If they ask a specific technical question the facilitator can't answer:
"That's outside my technical depth, and honestly outside what this course needs me to know. What I DO know is leadership — and the question underneath your technical question is: who should own that decision, and what's at stake if the allocation is wrong?"
| Channel | Price | Notes |
|---|---|---|
| On-Demand (individual) | $499 | Above L&D ceiling ($399), below academic floor ($850) |
| Enterprise (10+ seats) | $249–$349/seat | Real revenue driver. 100 seats at $249 = $24,900 |
| Certification | $2,499/facilitator | Matches DiSC ($2,495) and CCL ($2,500) |
| Workshop (per participant) | $1,495 | Anchored to CCL ($1,350) and Crucial Learning |
| LF-Led Workshops | $6,500 + $249/seat | Enterprise custom delivery |
| Public Workshops | $495/seat × 50 pax | ~$25K per session at scale |
| Keynotes | $15K–$50K | Entry point and conversion mechanism |
| Component | Tokens | Cost |
|---|---|---|
| Onboarding | ~6K | $0.08 |
| Module 1: DEFINE | ~20K | $0.28 |
| Module 2: DISCOVER | ~18K | $0.25 |
| Module 3: DESIGN | ~25K | $0.35 |
| Module 4: DEVELOP | ~15K | $0.21 |
| Module 5: DEMONSTRATE | ~20K | $0.28 |
| Course total | ~104K | ~$1.45 |
| 8-week system | ~55K | $0.77 |
| Full total | ~159K | ~$2.22 |
At $499/seat, AI costs are <0.5% of revenue. Even at 3x for heavy users: ~$6.66, well under 2%.
| Scenario | Seats | Avg Price | Revenue | AI Cost | Margin |
|---|---|---|---|---|---|
| Year 1 conservative | 2,000 | $220 | $440K | $4K | 99% |
| Year 1 moderate | 8,000 | $210 | $1.68M | $16K | 99% |
| Year 2 target | 25,000 | $200 | $5.0M | $50K | 99% |
| Year 3 target | 45,000 | $195 | $8.8M | $90K | 99% |
| Capability | Status | Timeline |
|---|---|---|
| SOC 2 compliance | ✅ Current | LeaderFactor is SOC 2 compliant |
| Data Processing Addendums | ✅ Current | Standard practice in enterprise agreements |
| SSO (SAML/OIDC) | 🔨 Buildable | Can be built for launch or shortly after |
| Admin reporting dashboard | 📋 Planned | Post-launch — cohort analytics, completion rates, ALI aggregate scores |
| SCORM/LTI integration | 📋 Planned | Post-launch — for clients requiring LMS integration |
| Bulk enrollment + seat management | 📋 Planned | Post-launch — enterprise admin console |
| Custom branding / white-label | 📋 Planned | Future — for certification partners deploying at scale |
Enterprise buyers should expect SOC 2 compliance, DPA, and SSO at or near launch. Admin reporting and LMS integration follow in the first 90 days post-launch. A detailed enterprise features spec will be published separately as the technical architecture is finalized.
Locked-down enterprise (no AI tools allowed yet): The course builds readiness for AI that's coming. ✓
Bleeding-edge startup (AI everywhere): Structure and intentionality for a leader with enthusiasm but no framework. ✓
Every step intensifies. The identity reckoning is the question. Transformation possibilities have exploded. Safety is existential. Evidence is the currency. The framework is antifragile. ✓
Non-technical facilitator can deliver every module. Framework carries intellectual weight. Facilitator carries process weight. ✓
What's different when a participant returns to work?
Senior VP, 25 years, thinks their team doesn't need AI. Engages through design challenge, team responsibility, and intellectual respect. ✓
Does 2.5-3 hours of AI dialogue feel like partnership or chatbot? This is the existential risk for on-demand. Mitigation: validate Module 1 conversation with real participants before building remaining modules. If it doesn't pass validation, options are: iterate on prompts, reduce AI scope, or pivot to facilitator-supported hybrid. See TECHNICAL-SPEC.md for validation protocol.
Industry average for on-demand L&D is 15-25%. This product needs 50%+. Mitigations: sessions under 40 min, AI variety prevents fatigue, progress visualization, cross-module memory creates investment, tangible artifacts create momentum. Each completed module delivers standalone value.
| Course Connection | How It Links | Direction |
|---|---|---|
| The 4 Stages of Psychological Safety | Module 4 (Develop) is explicitly built on psychological safety. The Readiness Gaps extend the 4 Stages into AI adoption. | 5D → 4 Stages (deepening) or 4 Stages → 5D (AI application) |
| EQ Index | Module 1 requires self-awareness. Module 4 requires empathy. Both EQ competencies. | 5D → EQ (personal development) |
| Coaching & Accountability | Module 4 is essentially coaching through change. | 5D → Coaching (skill development) |
| EPIC Change | The entire course is about leading AI-specific change. EPIC provides the broader toolkit. | 5D → EPIC (scaling the transformation) |
Natural sequences: - New customer: 5D Model → 4 Stages → Coaching → EPIC Change - Existing customer: 4 Stages → 5D Model (AI application of what they know) - Enterprise rollout: 5D (leadership layer) → 4 Stages (team layer) → Coaching (manager layer)
| Element | v2 | v3 | Why |
|---|---|---|---|
| Framework | 4 Demands: Clarify → Calibrate → Cultivate → Configure | 5D: Define → Discover → Design → Develop → Demonstrate | Completes the loop, more intuitive progression, cleaner three-act structure |
| Modules | 4 modules + closing | 5 modules (45 min each) | Uniform timing, 5th module is the differentiator |
| Duration | 4 hours | 3h 45m + break | Leaner. Each module tighter. |
| Progression | Self → Mind → Team → System | Work (×3) → People → Evidence | Separates the human problem cleanly |
| Module 5 | Configure (design the work) | Demonstrate (prove the value) | Biggest structural addition. No other AI course teaches proof. |
| Assessment | 4 dimensions (25 items) | 5 dimensions (30 items) | Maps to five steps |
| Reinforcement | 12 weeks | 8 weeks + optional monthly continuation | More realistic engagement; scaffolding removal prevents AI dependency |
What did NOT change: The Great Distillation, the ALI concept, the Partnership Map, the Companion Resource strategy, facilitator-as-coach design, the redirect framework, pricing architecture, cross-sell architecture, the front door/foundation strategy, pre-work structure, and the three AI-specificity concepts.
| Question | Resolution | Date |
|---|---|---|
| Course name | Leading Through AI™ | March 2, 2026 |
| 8-week system ships in v1 | Yes | March 2, 2026 |
| Physical vs. digital artifacts | Digital only for both modalities at launch | March 2, 2026 |
| AI in the course | AI Thinking Partner present in both modalities | March 2, 2026 |
| Relationship to "The 4 Demands" | 5D Model replaces it. 4 Demands / 4 C's retired Feb 27, 2026. | Feb 27, 2026 |
Book / Field Guide Active exploration. Potential parallel project shipping close to course launch. Core line: "You're not being replaced. You're being returned to yourself." Format: ~100-120 page field guide via Amazon KDP. See project plan for status.
This document is the single source of truth for Leading Through AI™. The deck, videos, app, facilitator guide, and all marketing reference back to this file. Technical architecture, enterprise features, and engineering specs live in TECHNICAL-SPEC.md.
Created: February 27, 2026 (as Course Architecture v3) Unified: March 2, 2026 (merged with On-Demand Spec v2) Authors: Tim Clark Sr. & Tim Clark Jr.